John von Neumann

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Turing's Cathedral by George Dyson

1919 Motor Transport Corps convoy, Abraham Wald, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, Benoit Mandelbrot, Bletchley Park, British Empire, Brownian motion, cellular automata, Charles Babbage, cloud computing, computer age, Computing Machinery and Intelligence, Danny Hillis, dark matter, double helix, Dr. Strangelove, fault tolerance, Fellow of the Royal Society, finite state, Ford Model T, Georg Cantor, Henri Poincaré, Herman Kahn, housing crisis, IFF: identification friend or foe, indoor plumbing, Isaac Newton, Jacquard loom, John von Neumann, machine readable, mandelbrot fractal, Menlo Park, Murray Gell-Mann, Neal Stephenson, Norbert Wiener, Norman Macrae, packet switching, pattern recognition, Paul Erdős, Paul Samuelson, phenotype, planetary scale, RAND corporation, random walk, Richard Feynman, SETI@home, social graph, speech recognition, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Turing complete, Turing machine, Von Neumann architecture

Mariette von Neumann to John von Neumann, September 22, 1937, in Frank Tibor, “Double Divorce: The Case of Mariette and John von Neumann,” Nevada Historical Society Quarterly 34, no. 2 (1991): 361. 12. Mariette von Neumann to John von Neumann, n.d., 1937, in ibid. 13. Klára von Neumann to John von Neumann, November 11, 1937, KVN. 14. John von Neumann to Stanislaw Ulam, April 22, 1938, SFU. 15. Klára von Neumann, Two New Worlds. 16. John von Neumann to Klára von Neumann, September 14, 1938, KVN. 17. John von Neumann to Klára von Neumann, September 6, 1938, KVN. 18. John von Neumann to Klára von Neumann, September 5, 1938, KVN; John von Neumann to Klára von Neumann, September 13, 1938, KVN. 19.

Nicholas Vonneumann, interview with author. 10. Vonneumann, John von Neumann as Seen by His Brother, pp. 23, 16. 11. Ibid., p. 24. 12. Nicholas Vonneumann, interview with author. 13. Stanislaw Ulam, “John von Neumann: 1903–1957,” Bulletin of the American Mathematical Society 64, no. 3, part 2 (May 1958): 1. 14. Klára von Neumann, Johnny, ca. 1963, KVN; Ulam, “John von Neumann: 1903–1957,” 2:37. 15. John von Neumann to Stan Ulam, December 9, 1939, SFU; Oskar Morgenstern, in John von Neumann, documentary produced by the Mathematical Association of America, 1966. 16. Klára von Neumann, Johnny. 17. John von Neumann and Oskar Morgenstern, Theory of Games and Economic Behavior (Princeton, N.J.: Princeton University Press, 1944), p. 2; Samuelson, “A Revisionist View of Von Neumann’s Growth Model,” in M.

Jack Rosenberg, interview with author, February 12, 2005; Marina von Neumann Whitman, interview with author, February 9, 2006. 29. Klára von Neumann to John von Neumann, n.d., ca. 1949, KVN. 30. Klára von Neumann, Johnny. 31. Ibid. 32. John von Neumann and Oswald Veblen to Frank Aydelotte, March 23, 1940, IAS. 33. Ibid. 34. Klára von Neumann, Johnny. 35. John von Neumann to Stanislaw Ulam, April 2, 1942, VNLC; John von Neumann to Clara [Klára] von Neumann, April 13, 1943, KVN; S. W. Hubbel [Office of Censorship] to Clara [Klára] von Neumann, April 13, 1943, IAS. 36. Klára von Neumann, Johnny. 37. John von Neumann to Klára von Neumann, May 8, 1945, KVN; John von Neumann to Klára von Neumann, May 11, 1945, KVN. 38.


pages: 476 words: 121,460

The Man From the Future: The Visionary Life of John Von Neumann by Ananyo Bhattacharya

Ada Lovelace, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Alvin Roth, Andrew Wiles, Benoit Mandelbrot, business cycle, cellular automata, Charles Babbage, Claude Shannon: information theory, clockwork universe, cloud computing, Conway's Game of Life, cuban missile crisis, Daniel Kahneman / Amos Tversky, DeepMind, deferred acceptance, double helix, Douglas Hofstadter, Dr. Strangelove, From Mathematics to the Technologies of Life and Death, Georg Cantor, Greta Thunberg, Gödel, Escher, Bach, haute cuisine, Herman Kahn, indoor plumbing, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, Jacquard loom, Jean Tirole, John Conway, John Nash: game theory, John von Neumann, Kenneth Arrow, Kickstarter, linear programming, mandelbrot fractal, meta-analysis, mutually assured destruction, Nash equilibrium, Norbert Wiener, Norman Macrae, P = NP, Paul Samuelson, quantum entanglement, RAND corporation, Ray Kurzweil, Richard Feynman, Ronald Reagan, Schrödinger's Cat, second-price auction, side project, Silicon Valley, spectrum auction, Steven Levy, Strategic Defense Initiative, technological singularity, Turing machine, Von Neumann architecture, zero-sum game

Fellner would initially study the subject for similar reasons. All three would drop it quite soon after finishing their degrees to pursue their true passions. 23. Quoted in Stanisław Ulam, ‘John von Neumann 1903–1957’, Bulletin of the American Mathematical Society, 64 (1958), pp. 1–49. 24. John von Neumann, ‘Eine Axiomatisierung der Mengenlehre’, Journal für die reine und angewandte Mathematik, 154 (1925), pp. 219–40. 25. John von Neumann, ‘Die Axiomatisierung der Mengenlehre’, Mathematische Zeitschrift, 27 (1928), pp. 669–752. 26. Quoted in Dyson, Turing’s Cathedral. CHAPTER 3: THE QUANTUM EVANGELIST 1.

Quoted in Dyson, Turing’s Cathedral. 18. https://libertyellisfoundation.org/passenger-details/czoxMzoiOTAxMTk4OTg3MDU0MSI7/czo4OiJtYW5pZmVzdCI7. 19. Details of Meitner’s life drawn from Ruth Lewin Sime, 1996, Lise Meitner: A Life in Physics, University of California Press, Berkeley. 20. John von Neumann, 2005, John von Neumann: Selected Letters, ed. Miklós Rédei, American Mathematical Society, Providence, R.I. 21. Subrahmanyan Chandrasekhar and John von Neumann, 1942, ‘The Statistics of the Gravitational Field Arising from a Random Distribution of Stars. I. The Speed of Fluctuations’, Astrophysical Journal, 95 (1942), pp. 489–531. 22. Thomas Haigh and Mark Priestly have recently made the case that von Neumann was not much influenced by Turing when it came to computer design, based on the text of three lectures they discovered: ‘Von Neumann Thought Turing’s Universal Machine Was “Simple and Neat”.

., and William Aspray, 1990, John von Neumann and the Origins of Modern Computing, MIT Press, Cambridge, Mass. 2. A slightly longer excerpt is quoted in Leonard, Von Neumann, Morgenstern, and the Creation of Game Theory Cambridge University Press, Cambridge. 3. See Macrae, John von Neumann. 4. Earl of Halsbury, ‘Ten Years of Computer Development’, Computer Journal, 1 (1959), pp. 153–9. 5. Brian Randell, 1972, On Alan Turing and the Origins of Digital Computers, University of Newcastle upon Tyne Computing Laboratory, Technical report series. 6. Quoted in Aspray, John von Neumann and the Origins of Modern Computing. 7.


pages: 463 words: 118,936

Darwin Among the Machines by George Dyson

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, backpropagation, Bletchley Park, British Empire, carbon-based life, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, computer age, Computing Machinery and Intelligence, Danny Hillis, Donald Davies, fault tolerance, Fellow of the Royal Society, finite state, IFF: identification friend or foe, independent contractor, invention of the telescope, invisible hand, Isaac Newton, Jacquard loom, James Watt: steam engine, John Nash: game theory, John von Neumann, launch on warning, low earth orbit, machine readable, Menlo Park, Nash equilibrium, Norbert Wiener, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, phenotype, RAND corporation, Richard Feynman, spectrum auction, strong AI, synthetic biology, the scientific method, The Wealth of Nations by Adam Smith, Turing machine, Von Neumann architecture, zero-sum game

Berkeley, Giant Brains (New York: John Wiley, 1949), 5. 45.John von Neumann, 1948, “The General and Logical Theory of Automata,” in Lloyd A. Jeffress, ed., Cerebral Mechanisms in Behavior: The Hixon Symposium (New York: Hafner, 1951), 31. 46.Stanislaw Ulam, Adventures of a Mathematician (New York: Scribner’s, 1976), 242. 47.John von Neumann, 1948, response to W. S. McCulloch’s paper “Why the Mind Is in the Head,” Hixon Symposium, September 1948, in Jeffress, Cerebral Mechanisms, 109–111. 48.John von Neumann to Oswald Veblen, memorandum, 26 March 1945, “On the Use of Variational Methods in Hydrodynamics,” reprinted in John von Neumann, Theory of Games, Astrophysics, Hydrodynamics and Meteorology, vol. 6 of Collected Works, ed.

Dyson, Disturbing the Universe (New York: Harper & Row, 1979), 194. 2.Stanislaw Ulam, Adventures of a Mathematician (New York: Scribner’s, 1976), 231. 3.Nicholas Vonneumann, “John von Neumann: Formative Years,” Annals of the History of Computing 11, no. 3 (1989): 172. 4.Eugene P. Wigner, “John von Neumann—A Case Study of Scientific Creativity,” Annals of the History of Computing. 11, no. 3 (1989): 168. 5.Edward Teller, in Jean R. Brink and Roland Haden, “Interviews with Edward Teller and Eugene P. Wigner,” Annals of the History of Computing 11, no. 3 (1989): 177. 6.Stanislaw Ulam, “John von Neumann, 1903–1957,” Bulletin of the American Mathematical Society 64, no. 3 (May 1958): 1. 7.Eugene Wigner, “Two Kinds of Reality,” The Monnist 49, no. 2 (April 1964); reprinted in Symmetries and Reflections (Cambridge: MIT Press, 1967), 198. 8.John von Neumann, statement on nomination to membership in the AEC, 8 March 1955, von Neumann Papers, Library of Congress; in William Aspray, John von Neumann and the Origins of Modern Computing (Cambridge: MIT Press, 1990), 247. 9.John von Neumann, as quoted by J.

Wigner,” Annals of the History of Computing 11, no. 3 (1989): 177. 6.Stanislaw Ulam, “John von Neumann, 1903–1957,” Bulletin of the American Mathematical Society 64, no. 3 (May 1958): 1. 7.Eugene Wigner, “Two Kinds of Reality,” The Monnist 49, no. 2 (April 1964); reprinted in Symmetries and Reflections (Cambridge: MIT Press, 1967), 198. 8.John von Neumann, statement on nomination to membership in the AEC, 8 March 1955, von Neumann Papers, Library of Congress; in William Aspray, John von Neumann and the Origins of Modern Computing (Cambridge: MIT Press, 1990), 247. 9.John von Neumann, as quoted by J. Robert Oppenheimer in testimony before the AEC Personnel Security Board, 16 April 1954, In the Matter of J. Robert Oppenheimer (Washington, D.C.: Government Printing Office, 1954; reprint, Cambridge: MIT Press, 1970), 246 (page citation is to the reprint edition). 10.Nicholas Metropolis, “The MANIAC,” in Nicholas Metropolis, J.


pages: 323 words: 100,772

Prisoner's Dilemma: John Von Neumann, Game Theory, and the Puzzle of the Bomb by William Poundstone

90 percent rule, Albert Einstein, anti-communist, cuban missile crisis, Douglas Hofstadter, Dr. Strangelove, Frank Gehry, From Mathematics to the Technologies of Life and Death, Herman Kahn, Jacquard loom, John Nash: game theory, John von Neumann, Kenneth Arrow, means of production, Monroe Doctrine, mutually assured destruction, Nash equilibrium, Norbert Wiener, RAND corporation, Richard Feynman, seminal paper, statistical model, the market place, zero-sum game

The Anchor Books edition is published by arrangement with Doubleday, a division of Random House, Inc. Anchor Books and colophon are registered trademarks of Random House, Inc. The quotes from letters of John von Neumann on pp. 22, 65, 75, 140–41, and 180 are from materials in the John von Neumann archives, Library of Congress, and are used with permission of Marina von Neumann Whitman. The excerpts from “The Mathematician” by John von Neumann on pp. 28–29 are used with permission of the University of Chicago Press. Copyright © 1950. The quotations from letters of J. D. Williams on pp. 94–95 are used with permission of Evelyn Williams Snow.

Thanks for recollections, assistance, or advice must also go to Paul Armer, Robert Axelrod, Sally Beddow, Raoul Bott, George B. Dantzig, Paul Halmos, Jeane Holiday, Cuthbert Hurd, Martin Shubik, John Tchalenko, Edward Teller, and Nicholas A. Vonneuman. CONTENTS Cover Other Books by this Author Title Page Dedication Acknowledgments 1 DILEMMAS The Nuclear Dilemma John von Neumann Prisoner’s Dilemma 2 JOHN VON NEUMANN The Child Prodigy Kun’s Hungary Early Career The Institute Klara Personality The Sturm und Drang Period The Best Brain in the World 3 GAME THEORY Kriegspiel Who Was First? Theory of Games and Economic Behavior Cake Division Rational Players Games as Trees Games as Tables Zero-Sum Games Minimax and Cake Mixed Strategies Curve Balls and Deadly Genes The Minimax Theorem N-Person Games 4 THE BOMB Von Neumann at Los Alamos Game Theory in Wartime Bertrand Russell World Government Operation Crossroads The Computer Preventive War 5 THE RAND CORPORATION History Thinking About the Unthinkable Surfing, Semantics, Finnish Phonology Von Neumann at RAND John Nash The Monday-Morning Quarterback 6 PRISONER’S DILEMMA The Buick Sale Honor Among Thieves The Flood-Dresher Experiment Tucker’s Anecdote Common Sense Prisoner’s Dilemmas in Literature Free Rider Nuclear Rivalry 7 1950 The Soviet Bomb The Man from Mars Urey’s Speech The Fuchs Affair The Korean War The Nature of Technical Surprise Aggressors for Peace Francis Matthews Aftermath Public Reaction Was It a Trial Balloon?

Today, with East-West tensions relaxing, preventive war seems a curious aberration of cold-war mentality. Yet the same sorts of issues are very much with us today. What should a nation do when its security conflicts with the good of all humanity? What should a person do when his or her interests conflict with the common good? JOHN VON NEUMANN Perhaps no one exemplifies the agonizing dilemma of the bomb better than John von Neumann (1903–1957). That name does not mean much to most people. The celebrity mathematician is almost a nonexistent species. Those few laypersons who recognize the name are most likely to place him as a pioneer of the electronic digital computer, or as one of the crowd of scientific luminaries who worked on the Manhattan Project.


pages: 253 words: 80,074

The Man Who Invented the Computer by Jane Smiley

1919 Motor Transport Corps convoy, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, Arthur Eddington, Bletchley Park, British Empire, c2.com, Charles Babbage, computer age, Computing Machinery and Intelligence, Fellow of the Royal Society, Ford Model T, Henri Poincaré, IBM and the Holocaust, Isaac Newton, John von Neumann, Karl Jansky, machine translation, Norbert Wiener, Norman Macrae, Pierre-Simon Laplace, punch-card reader, RAND corporation, Turing machine, Vannevar Bush, Von Neumann architecture

Presper Eckert, only eighteen, was applying to college at MIT, though in the end he went to business school at the University of Pennsylvania. Konrad Zuse, in Berlin, had already built one computer (the Z1) in his parents’ apartment. He later said that if the building had not been bombed, he would not have been able to get his machine out of the apartment. John von Neumann, born in Hungary but living in Princeton, New Jersey, had become so convinced that war in Europe was inevitable that he had applied for U.S. citizenship. He received his naturalization papers in December 1937. Von Neumann was one of the most talented mathematicians of his day, but he wasn’t yet involved with computers.

In some ways, Alan Turing was Atanasoff’s precise opposite, drawn to pure mathematics rather than practical physics, educated to think rather than to tinker, disorganized in his approach rather than systematic, never a family man and required by his affections and his war work to be utterly secretive. His figure is now so mysterious and tragically evocative that he has become the most famous of our inventors. The man who was best known in his own lifetime, John von Neumann, has retreated into history, more associated with the atomic bomb and the memory of the cold war than with the history of the computer, but it was von Neumann who made himself the architect of that history without, in some sense, ever lifting a screwdriver (in fact, his wife said that he was not really capable of lifting a screwdriver).

If, at the University of Florida and Iowa State, and even at the University of Wisconsin, Atanasoff was always more or less at the periphery of both the mathematics and physics establishments, at King’s College Turing was at the exact heart, especially of mathematics. He took courses from astrophysicist Arthur Eddington and mathematicians G. H. Hardy and Max Born. He met John von Neumann there—many mathematicians fleeing conditions in Germany and the East passed through Cambridge on their way to settling elsewhere. And it was Max Newman, who was lecturing on topology—the study of relationships between geometric spaces as they are transformed by such operations as stretching, but not such operations as cutting—who introduced him to the Hilbert problem that would make his career.


pages: 998 words: 211,235

A Beautiful Mind by Sylvia Nasar

Al Roth, Albert Einstein, Andrew Wiles, Bletchley Park, book value, Brownian motion, business cycle, cognitive dissonance, Columbine, Dr. Strangelove, experimental economics, fear of failure, Gunnar Myrdal, Henri Poincaré, Herman Kahn, invisible hand, Isaac Newton, John Conway, John Nash: game theory, John von Neumann, Kenneth Arrow, Kenneth Rogoff, linear programming, lone genius, longitudinal study, market design, medical residency, Nash equilibrium, Norbert Wiener, Paul Erdős, Paul Samuelson, prisoner's dilemma, RAND corporation, Robert Solow, Ronald Coase, second-price auction, seminal paper, Silicon Valley, Simon Singh, spectrum auction, Suez canal 1869, The Wealth of Nations by Adam Smith, Thorstein Veblen, upwardly mobile, zero-sum game

Kuhn, interview. 27. Ibid. 28. Milnor, interview, 9.26.95. 7: John von Neumann 1. See, for example, Stanislaw Ulam, “John von Neumann, 1903–1957,” Bulletin of the American Mathematical Society, vol. 64, no. 3, part 2 (May 1958); Stanislaw Ulam, Adventures of a Mathematician (New York: Scribner’s, 1983); Paul R. Halmos, “The Legend of John von Neumann,” American Mathematical Monthly, vol. 80 (1973); William Poundstone, Prisoner’s Dilemma, op. cit.; Ed Regis, Who Got Einstein’s Office?, op. cit. 2. Poundstone, op. cit. 3. Ulam, “John von Neumann,” op. cit.; Poundstone, op. cit., pp. 94–96. 4. Harold Kuhn, interview, 1.10.96. 5.

Nash shared von Neumann’s interest in game theory, quantum mechanics, real algebraic variables, hydrodynamic turbulence, and computer architecture. 6. See, for example, Ulam, “John von Neumann,” op. cit. 7. Norman McRae, John von Neumann (New York: Pantheon Books, 1992), pp. 350–56. 8. John von Neumann, The Computer and the Brain (New Haven: Yale University Press, 1959). 9. See, for example, G. H. Hardy, A Mathematician’s Apology (Cambridge, U.K.: Cambridge University Press, 1967), with a foreword by C. P. Snow. 10. Ulam, “John von Neumann,” op. cit. 11. Poundstone, op. cit. 12. Poundstone, Prisoner’s Dilemma, p. 190. 13. Clay Blair, Jr., “Passing of a Great Mind,” Life (February 1957), pp. 89–90, as quoted by Poundstone, op. cit., p. 143. 14.

., “Passing of a Great Mind,” Life (February 1957), pp. 89–90, as quoted by Poundstone, op. cit., p. 143. 14. Poundstone, op. cit. 15. Ulam, “John von Neumann,” op. cit. 16. Harold Kuhn, interview, 3.97. 17. Paul R. Halmos, “The Legend of John von Neumann,” op. cit. 18. Ibid. 19. Poundstone, op. cit. 20. Halmos, op. cit. 21. Ibid. 22. Poundstone, op. cit. 23. Ulam, Adventures of a Mathematician, op. cit. 24. Ulam, “John von Neumann,” op. cit. 25. Ibid. 26. Ibid., p. 10; Robert J. Leonard, “From Parlor Games to Social Science,” op. cit. 27. Richard Duffin, interview, 10.94. 28. Halmos, op. cit. 29. Ulam, “John von Neumann,” op. cit., pp. 35–39. 30. Interviews with Donald Spencer, 11.18.95; David Gale, 9.20.95; and Harold Kuhn, 9.23.95. 31.


pages: 377 words: 97,144

Singularity Rising: Surviving and Thriving in a Smarter, Richer, and More Dangerous World by James D. Miller

23andMe, affirmative action, Albert Einstein, artificial general intelligence, Asperger Syndrome, barriers to entry, brain emulation, cloud computing, cognitive bias, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, David Brooks, David Ricardo: comparative advantage, Deng Xiaoping, en.wikipedia.org, feminist movement, Flynn Effect, friendly AI, hive mind, impulse control, indoor plumbing, invention of agriculture, Isaac Newton, John Gilmore, John von Neumann, knowledge worker, Larry Ellison, Long Term Capital Management, low interest rates, low skilled workers, Netflix Prize, neurotypical, Nick Bostrom, Norman Macrae, pattern recognition, Peter Thiel, phenotype, placebo effect, prisoner's dilemma, profit maximization, Ray Kurzweil, recommendation engine, reversible computing, Richard Feynman, Rodney Brooks, Silicon Valley, Singularitarianism, Skype, statistical model, Stephen Hawking, Steve Jobs, sugar pill, supervolcano, tech billionaire, technological singularity, The Coming Technological Singularity, the scientific method, Thomas Malthus, transaction costs, Turing test, twin studies, Vernor Vinge, Von Neumann architecture

Von Neumann made Stalin unwilling to risk war because von Neumann shaped U.S. weapons policy—in part by pushing the United States to develop hydrogen bombs—to let Stalin know that the only human life Stalin actually valued would almost certainly perish in World War III. 20 Johnny helped develop a superweapon, played a key role in integrating it into his nation’s military, advocated that it be used, and then made sure that his nation’s enemies knew that in a nuclear war they would be personally struck by this superweapon. John von Neumann could himself reasonably be considered the most powerful weapon ever to rest on American soil. Now consider the strategic implications if the Chinese high-tech sector and military acquired a million computers with the brilliance of John von Neumann, or if, through genetic manipulation, they produced a few thousand von Neumann-ish minds every year. Contemplate the magnitude of the resources the US military would pour into artificial intelligence if it thought that a multitude of digital or biological von Neumanns would someday power the Chinese economy and military.

But whole brain emulation is still a path to the Singularity that could work, even if a Kurzweilian merger proves beyond the capacity of bioengineers. If we had whole brain emulations, Moore’s Law would eventually give us some kind of Singularity. Imagine we just simulated the brain of John von Neumann. If the (software adjusted) speed of computers doubled every year, then in twenty years we could run this software on computers that were a million times faster and in forty years on computers that were a trillion times faster. The innovations that a trillion John von Neumanns could discover in one year would change the world beyond our current ability to imagine. 3.Clues from the Brain Even if we never figure out how to emulate our brains or merge them with machines, clues to how our brains work could help scientists figure out how to create other kinds of human-level artificial intelligence.

If the following diagram is right, we would likely have a lot of warning time between when AIs reach chimp level and when they become ultra-intelligent. But this first diagram might overstate differences in intelligence. The basic structure of my brain is pretty close to that of chimps and shockingly similar to John von Neumann’s. Perhaps, under some grand theory of intelligence, once you’ve reached chimp level it doesn’t take all that many more tweaks to go well past John von Neumann. If this next diagram has the relative sizes of intelligences right, then it might take very little time for an AI to achieve superintelligence once it becomes as smart as a chimp. As I’ll discuss in Chapter 7, there are a huge number of genes, each of which slightly contributes to a person’s intelligence.


pages: 558 words: 164,627

The Pentagon's Brain: An Uncensored History of DARPA, America's Top-Secret Military Research Agency by Annie Jacobsen

Albert Einstein, Berlin Wall, Boston Dynamics, colonial rule, crowdsourcing, cuban missile crisis, Dean Kamen, disinformation, Dr. Strangelove, drone strike, Edward Snowden, Fall of the Berlin Wall, game design, GPS: selective availability, Herman Kahn, Ivan Sutherland, John Markoff, John von Neumann, license plate recognition, Livingstone, I presume, low earth orbit, megacity, Menlo Park, meta-analysis, Mikhail Gorbachev, military-industrial complex, Murray Gell-Mann, mutually assured destruction, Neil Armstrong, Norman Mailer, operation paperclip, place-making, RAND corporation, restrictive zoning, Ronald Reagan, Ronald Reagan: Tear down this wall, social intelligence, stem cell, Stephen Hawking, Strategic Defense Initiative, traumatic brain injury, zero-sum game

The computer designed by John von Neumann played an important role in allowing Livermore scientists to model new nuclear weapons designs before building them. In the summer of 1955, John von Neumann was diagnosed with cancer. He had slipped and fallen, and when doctors examined him, they discovered that he had an advanced, metastasizing cancerous tumor in his collarbone. By November his spine was affected, and in January 1956 von Neumann was confined to a wheelchair. In March he entered a guarded room at Walter Reed Hospital, the U.S. Army’s flagship medical center, outside Washington, D.C. John von Neumann, at the age of fifty-four, racked with pain and riddled with terror, was dying of a cancer he most likely developed because of a speck of plutonium he inhaled at Los Alamos during the war.

Air Force brawn: Abella, photographs, (unpaginated). 2 game pieces scattered: Leonard, 339. 3 “credibility”: York, Making Weapons, 89. 4 remarkable child prodigy: S. Bochner, John Von Neumann, 1903–1957, National Academy of Sciences, 442–450. 5 “unsolved problem”: P. R. Halmos, “The Legend of John Von Neumann,” Mathematical Association of America, Vol. 80, No. 4, April 1973, 386. 6 “He was pleasant”: York, Making Weapons, 89. 7 “I think”: Kaplan, Wizards of Armageddon, 63. 8 “all-out atomic war”: Whitman, 52. 9 maximum kill rate: “Citation to Accompany the Award of the Medal of Merit to Dr. John von Neumann,” October 1946, Von Neumann Papers, LOC. 10 “a mentally superhuman race”: Dyson, Turing’s Cathedral, 45. 11 Prisoner’s Dilemma: Poundstone, 8-9, 103-106. 12 something unexpected: Abella, 55–56; Poundstone, 121-123. 13 “How can you persuade”: McCullough, 758. 14 Goldstine explained: Information on Goldstine comes from Jon Edwards, “A History of Early Computing at Princeton,” Princeton Alumni Weekly, August 27, 2012. 15 von Neumann declared: Dyson, Turing’s Cathedral, 73. 16 “Our universe”: George Dyson, “‘An Artificially Created Universe’: The Electronic Computer Project at IAS,” Institute for Advanced Study, Princeton (Spring 2012), 8-9. 17 secured funding: Maynard, “Daybreak of the Digital Age,” Princeton Alumni Weekly, April 4, 2012. 18 he erred: Jon Edwards, “A History of Early Computing at Princeton,” Princeton Alumni Weekly, August 27, 2012, 4. 19 Wohlstetter’s famous theory: Wohlstetter, “The Delicate Balance of Terror,” 1-12. 20 Debris: Descriptions of shock wave and blast effects are described in Garrison, 23-29. 21 Georg Rickhey: Information on Rickhey comes from Bundesarchiv Ludwigsburg and RG 330 JIOA Foreign Scientist Case Files, NACP.

Competition was valued and encouraged at RAND, with scientists and analysts always working to outdo one another. Lunchtime war games included at least one person in the role of umpire, which usually prevented competitions from getting out of hand. Still, tempers flared, and sometimes game pieces scattered. Other times there was calculated calm. Lunch could last for hours, especially if John von Neumann was in town. In the 1950s, von Neumann was the superstar defense scientist. No one could compete with his brain. At the Pentagon, the highest-ranking members of the U.S. armed services, the secretary of defense and the Joint Chiefs of Staff, all saw von Neumann as an infallible authority. “If anyone during that crucial period in the early and middle-fifties can be said to have enjoyed more ‘credibility’ in national defense circles than all the others, that person was surely Johnny,” said Herb York, von Neumann’s close friend.


pages: 406 words: 108,266

Journey to the Edge of Reason: The Life of Kurt Gödel by Stephen Budiansky

Abraham Wald, Albert Einstein, anti-communist, business cycle, Douglas Hofstadter, fear of failure, Fellow of the Royal Society, four colour theorem, Georg Cantor, Gregor Mendel, Gödel, Escher, Bach, John von Neumann, laissez-faire capitalism, P = NP, P vs NP, Paul Erdős, rent control, scientific worldview, the scientific method, Thorstein Veblen, Turing machine, urban planning

., Notizbücher, 376, 390. 20.Enzensberger, “Hommage à Gödel,” reprinted in W&B, 25 (my translation). 21.KG, “Existence of Undecidable Propositions,” 6. 22.KG, “Existence of Undecidable Propositions,” 6–7. 23.KG, “Situation in Foundations of Mathematics,” CW, 3:50–51. 24.KG, “Existence of Undecidable Propositions,” 8–9. 25.KG, “Undecidable Propositions of Formal Systems,” CW, 1:355. 26.KG, “Existence of Undecidable Propositions,” 14. 27.KG, “Undecidable Propositions of Formal Systems,” CW, 1:359. 28.Kleene, “Kurt Gödel,” 154. 29.Vinnikov, “Hilbert’s Apology.” 30.Heinrich Scholz to Rudolf Carnap, 16 April 1931, quoted in Mancosu, “Reception of Gödel’s Theorem,” 33; Marcel Natkin to KG, 27 June 1931, KGP, 2c/114. 31.Goldstine, Pascal to von Neumann, 167–68. 32.John von Neumann to KG, 20 November 1930, CW, 5:336–39. 33.Drafts of KG to John von Neumann, late November 1930, quoted in von Plato, “Sources of Incompleteness,” 4050–51. 34.John von Neumann to KG, 29 November 1930, CW, 5:338. 35.Von Plato, “Sources of Incompleteness,” 4054. 36.Ulam, Adventures of a Mathematician, 80; Goldstine, Pascal to von Neumann, 174. 37.Statement in Connection with the First Presentation of the Albert Einstein Award to Dr.

., 1938], Veblen, Papers, 8/10; Karl Menger to KG, [December 1938], CW, 5:125. 53.KG to Karl Menger, 25 June, 19 October, and 11 November 1938, quoted in Menger, Reminiscences, 218–19. 54.Menger, Reminiscences, 220–21. 55.Menger, Reminiscences, 224. 56.Menger, Reminiscences, 224–25; KG to Karl Menger, 30 August 1939, CW, 5:124–26; OMD, 19 March 1972. 57.KG to Oswald Veblen, draft letter, November 1939, KGP, 13c/197. 58.John von Neumann to Abraham Flexner, 27 September 1939, quoted in Dyson, Turing’s Cathedral, 96; von Neumann to KG, telegram, 5 October 1939, IAS, Faculty Files, Pre-1953. 59.John von Neumann to Abraham Flexner, 16 October 1939, IAS, Visa-Immigration. 60.Ash, “Universität Wien,” 124–25; Friedrich Plattner to Rektor der Universität, 12 August 1939, reproduced in GA, 67–68. 61.Arthur Marchet to Rektor der Universität, 30 September 1939, reproduced in GA, 72. 62.Dawson, Logical Dilemmas, 140; KG to Devisenstelle Wien, 29 July 1939, reproduced in GA, 65–66. 63.KG to Oswald Veblen, draft letter, November 1939, KGP, 3c/197; Menger, Reminiscences, 224; Kreisel, “Kurt Gödel,” 155. 64.Frank Aydelotte to Chargé d’Affaires, German Embassy, 1 December 1939, IAS, Faculty Files, Pre-1953. 65.Der Dekan to Rektor der Universität, 27 November 1939, reproduced in GA, 71. 66.KG to Frank Aydelotte, 5 January 1940, IAS, Faculty Files, Pre-1953; KG to Institute for Advanced Study, telegram, 15 January 1940, ibid.; KG passport, KGP, 13a/8. 67.KG to MG, 29 November 1965 (“I still recall the suitcase of things that Adele brought back from there in 1940”). 68.KG to RG, 31 March 1940; KG to Institute for Advanced Study, telegram, 5 March 1940, IAS, Faculty Files, Pre-1953. 69.OMD, 10 March 1940.

Philip Erlich Walking with Einstein Railroad line to Brünn, 1838 Brünn’s city theater Austro-Hungarian Monarchy, 1906 (map) Vienna’s medieval glacis The Ringstraße, nearing completion Vienna’s prototype anti-Semite, Karl Lueger Portrait of Margaret Stonborough-Wittgenstein by Gustav Klimt, 1905 Self-portrait of Ernst Mach Brünn’s textile mills, 1915 Brünn (map) Gödel as a baby The Gödel family Gödel Villa in Brünn Realgymnasium, Brünn Gödel’s school report card Gödel’s Vienna (map) Café Arkaden Albert Einstein in Vienna, 1921 University of Vienna Olga Taussky Philipp Furtwängler Gödel as a student Hans Hahn Anti-Semitic attacks at the university The Bärenhöhle Justizpalast attack, 1927 Moritz Schlick Café Josephinum Karl Menger Rudolf Carnap Ludwig Wittgenstein At tea with Olga Taussky and foreign visitors With Adele in Vienna Adele on stage, age nineteen Marked-up proof page of the Incompleteness Theorem Gödel’s lecture fees, 1937 Hiking near the Rax Josefstädter Straße Oswald Veblen Princeton, 1930s John von Neumann Nazi students and faculty at the University of Vienna, 1931 With Alfred Tarski, 1935 Purkersdorf Sanatorium Receipt for stay at Purkersdorf Rekawinkel Sanatorium Portrait of Adele, 1932 Moritz Schlick’s murder Hans Nelböck on trial Gödel’s 1937–38 shorthand diary Grinzing, 1938 Nazi takeover at the University of Vienna, 1938 Adele’s NSDAP application Wedding portrait, September 1938 Passport and cables, 1940 Crossing the Pacific with Adele Fuld Hall Verena Huber-Dyson With Albert Einstein With Oskar Morgenstern Receiving the Einstein Award, 1951 With Adele at Linden Lane Working outdoors With the flamingo With Rudi and Marianne Gödel in Princeton Gödel’s office in the new library Student protests in Princeton, 1969 At the Institute for Advanced Study garden party, 1973 JOURNEY to the EDGE of REASON At the Institute for Advanced Study, 1956 PROLOGUE MARCH 1970.


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Complexity: A Guided Tour by Melanie Mitchell

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Albert Michelson, Alfred Russel Wallace, algorithmic management, anti-communist, Arthur Eddington, Benoit Mandelbrot, bioinformatics, cellular automata, Claude Shannon: information theory, clockwork universe, complexity theory, computer age, conceptual framework, Conway's Game of Life, dark matter, discrete time, double helix, Douglas Hofstadter, Eddington experiment, en.wikipedia.org, epigenetics, From Mathematics to the Technologies of Life and Death, Garrett Hardin, Geoffrey West, Santa Fe Institute, Gregor Mendel, Gödel, Escher, Bach, Hacker News, Hans Moravec, Henri Poincaré, invisible hand, Isaac Newton, John Conway, John von Neumann, Long Term Capital Management, mandelbrot fractal, market bubble, Menlo Park, Murray Gell-Mann, Network effects, Norbert Wiener, Norman Macrae, Paul Erdős, peer-to-peer, phenotype, Pierre-Simon Laplace, power law, Ray Kurzweil, reversible computing, scientific worldview, stem cell, Stuart Kauffman, synthetic biology, The Wealth of Nations by Adam Smith, Thomas Malthus, Tragedy of the Commons, Turing machine

“When his mother once stared rather aimlessly”: Macrae, N., John von Neumann. New York: Pantheon, 1992, p. 52. “the greatest paper on mathematical economics”: Quoted in Macrae, N., John von Neumann. New York: Pantheon, 1992, p. 23. “the most important document ever written on computing and computers”: Goldstine, H. H., The Computer, from Pascal to von Neumann. Princeton, NJ: Princeton University Press, first edition, 1972, p. 191. “Five of Hungary’s six Nobel Prize winners”: Macrae, N., John von Neumann. New York: Pantheon, 1992, p. 32. “The [IAS] School of Mathematics”: Quoted in Macrae, N., John von Neumann. New York: Pantheon, 1992, p. 324.

In fact, it is one of the simplest systems to capture the essence of chaos: sensitive dependence on initial conditions. The logistic map was brought to the attention of population biologists in a 1971 article by the mathematical biologist Robert May in the prestigious journal Nature. It had been previously analyzed in detail by several mathematicians, including Stanislaw Ulam, John von Neumann, Nicholas Metropolis, Paul Stein, and Myron Stein. But it really achieved fame in the 1980s when the physicist Mitchell Feigenbaum used it to demonstrate universal properties common to a very large class of chaotic systems. Because of its apparent simplicity and rich history, it is a perfect vehicle to introduce some of the major concepts of dynamical systems theory and chaos.

This simple-sounding problem turns out to have echos in the work of Kurt Gödel and Alan Turing, which I described in chapter 4. The solution also contains an essential means by which biological systems themselves get around the infinite regress. The solution was originally found, in the context of a more complicated problem, by the twentieth-century Hungarian mathematician John von Neumann. Von Neumann was a pioneer in fields ranging from quantum mechanics to economics and a designer of one of the earliest electronic computers. His design consisted of a central processing unit that communicates with a random access memory in which both programs and data can be stored. It remains the basic design of all standard computers today.


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Tools for Thought: The History and Future of Mind-Expanding Technology by Howard Rheingold

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Bletchley Park, card file, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, Compatible Time-Sharing System, computer age, Computer Lib, Computing Machinery and Intelligence, conceptual framework, Conway's Game of Life, Douglas Engelbart, Dynabook, experimental subject, Hacker Ethic, heat death of the universe, Howard Rheingold, human-factors engineering, interchangeable parts, invention of movable type, invention of the printing press, Ivan Sutherland, Jacquard loom, John von Neumann, knowledge worker, machine readable, Marshall McLuhan, Menlo Park, Neil Armstrong, Norbert Wiener, packet switching, pattern recognition, popular electronics, post-industrial society, Project Xanadu, RAND corporation, Robert Metcalfe, Silicon Valley, speech recognition, Steve Jobs, Steve Wozniak, Stewart Brand, Ted Nelson, telemarketer, The Home Computer Revolution, Turing machine, Turing test, Vannevar Bush, Von Neumann architecture

At the age of forty-two, he committed suicide, hounded cruelly by the same government he helped save. John von Neumann spoke five languages and knew dirty limericks in all of them. His colleagues, famous thinkers in their own right, all agreed that the operations of Johnny's mind were too deep and far too fast to be entirely human. He was one of history's most brilliant physicists, logicians, and mathematicians, as well as the software genius who invented the first electronic digital computer. John von Neumann was the center of the group who created the "stored program" concept that made truly powerful computers possible, and he specified a template that is still used to design almost all computers--the "von Neumann architecture."

Turing, "Computing Machinery and intelligence," Mind, vol. 59, no. 236 (1950). [7] Ibid. [8] Hodges, Turing, 488. Chapter Four: Johnny Builds Bombs and Johnny Builds Brains [1] Steve J. Heims, John von Neumann and Norbert Wiener (Cambridge, Mass.: MIT Press, 1980), 371. [2] C. Blair, "Passing of a great Mind," Life,, February 25, 1957, 96. [3] Stanislaw Ulam, "John von Neumann, 1903-1957," Bulletin of the American Mathematical Society, vol. 64, (1958), 4. [4] Goldstine, The Computer, 182. [5] Daniel Bell, The coming of Post-Industrial Society (New York: Basic Books. 1973), 31

They built a tic-tac-toe machine, but gave up on it as a moneymaking venture when an adviser assured them that P. T. Barnum's General Tom Thumb had sewn up the market for traveling novelties. Ironically, although Babbage's game-playing machines were commercial failures, his theoretical approach created a foundation for the future science of game theory, scooping even that twentieth-century genius John von Neumann by about a hundred years. It was Charley and Ada's attempt to develop an infallible system for betting on the ponies that brought Ada to the sorry pass of twice pawning her husband's family jewels, without his knowledge, to pay off blackmailing bookies. At one point, Ada and Babbage--never one to turn down a crazy scheme--used the existing small scale working model of the Difference Engine to perform the calculations required by their complex handicapping scheme.


The Fractalist by Benoit Mandelbrot

Albert Einstein, Benoit Mandelbrot, Brownian motion, business cycle, Claude Shannon: information theory, discrete time, double helix, financial engineering, Georg Cantor, Henri Poincaré, Honoré de Balzac, illegal immigration, Isaac Newton, iterative process, Johannes Kepler, John von Neumann, linear programming, Louis Bachelier, Louis Blériot, Louis Pasteur, machine translation, mandelbrot fractal, New Journalism, Norbert Wiener, Olbers’ paradox, Paul Lévy, power law, Richard Feynman, statistical model, urban renewal, Vilfredo Pareto

Am I describing a nightmare? No, but I wish I was. Having left MIT, I was spending the year 1953–54 at IAS as the last postdoctoral fellow that von Neumann sponsored. That lecture came about one day during a chat with Oppie on the commuter train. John von Neumann Many pure mathematicians I knew well—like Szolem or Paul Lévy—were not attuned to other fields. John von Neumann (1903–57) was a man of many trades—all sought after—and a known master of each. He continually stunned the mathematical sciences by zeroing in on problems acknowledged as the most challenging of the day, and with his speed, intellectual flexibility, and unsurpassed power, he arrived at solutions that encountered instant acclaim.

French Air Force Engineers Reserve Officer in Training, 1949–50 12. Growing Addiction to Classical Music, Voice, and Opera 13. Life as a Grad Student and Philips Electronics Employee, 1950–52 14. First Kepler Moment: The Zipf-Mandelbrot Distribution of Word Frequencies, 1951 15. Postdoctoral Grand Tour Begins at MIT, 1953 16. Princeton: John von Neumann’s Last Postdoc, 1953–54 17. Paris, 1954–55 18. Wooing and Marrying Aliette, 1955 19. In Geneva with Jean Piaget, Mark Kac, and Willy Feller, 1955–57 20. An Underachieving and Restless Maverick Pulls Up Shallow Roots, 1957–58 Part Three: My Life’s Fruitful Third Stage 21. At IBM Research Through Its Golden Age in the Sciences, 1958–93 22.

To help the biologist Jacques Monod decide between biology and music, his influential father appointed a committee. It reported that as a biologist he would match Pasteur and as a musician he would match Mozart. He chose biology and won a Nobel Prize. More important for me was the great mathematician John von Neumann, to be introduced later. Around 1920, Hungary, his motherland, was under a cloud of uncertainty far worse than Poland in 1920 and France in 1945. His rich father wanted him to play it safe and study chemical engineering, but agreed to hire a young Budapest professor named Michael Fekete to determine whether “Janos” should also be allowed to seek a Ph.D. in mathematics.


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The Rise of the Quants: Marschak, Sharpe, Black, Scholes and Merton by Colin Read

Abraham Wald, Albert Einstein, Bayesian statistics, Bear Stearns, Black-Scholes formula, Bretton Woods, Brownian motion, business cycle, capital asset pricing model, collateralized debt obligation, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, David Ricardo: comparative advantage, discovery of penicillin, discrete time, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, financial engineering, financial innovation, fixed income, floating exchange rates, full employment, Henri Poincaré, implied volatility, index fund, Isaac Newton, John Meriwether, John von Neumann, Joseph Schumpeter, Kenneth Arrow, Long Term Capital Management, Louis Bachelier, margin call, market clearing, martingale, means of production, moral hazard, Myron Scholes, Paul Samuelson, price stability, principal–agent problem, quantitative trading / quantitative finance, RAND corporation, random walk, risk free rate, risk tolerance, risk/return, Robert Solow, Ronald Reagan, shareholder value, Sharpe ratio, short selling, stochastic process, Thales and the olive presses, Thales of Miletus, The Chicago School, the scientific method, too big to fail, transaction costs, tulip mania, Works Progress Administration, yield curve

Nevertheless, the necessity for action and for decision compels us as practical men to do our best to overlook this awkward fact and to behave exactly as we should if we had behind us a good Benthamite calculation of a series of prospective advantages and disadvantages, each multiplied by its appropriate probability waiting to be summed.1 The finance literature further clarified that there are calculable risks and that there are uncertainties that cannot be quantified. In the 1930s, John von Neumann set about producing a model of expected utility that permitted the inclusion of risk. Then, Leonard Jimmie Savage described how our individual perceptions affect the probability of uncertainty, and Kenneth Arrow was able to include these probabilities of uncertainty in a model that established the existence of equilibrium in a market for financial securities.

These are the questions that the pricing analysts sought to resolve. 2 A Roadmap to Resolve the Big Questions In the first half of the twentieth century, Irving Fischer described why people save. John Maynard Keynes then showed how individuals adjust their portfolios between cash and less liquid assets, while Franco Modigliani demonstrated how all these personal financial decisions evolve over one’s lifetime. John von Neumann, Leonard Jimmie Savage, and Kenneth Arrow then incorporated uncertainty into the mix, and Harry Markowitz packaged the state of financial science into Modern Portfolio Theory. However, none of these great minds provided a satisfactory explanation for how the price of individual securities evolve over time.

This page intentionally left blank 3 The Early Years Jacob Marschak was not at all unusual among the cadre of great minds that formed the discipline of finance in the first half of the twentieth century. Like the families of Milton Friedman, Franco Modigliani, Leonard Jimmie Savage, Kenneth Arrow, John von Neumann, and Harry Markowitz, Marschak’s family tree was originally rooted in the Jewish culture and derived from the intellectually stimulating region of Eastern, Central and Southern Europe at the beginning of the twentieth century. This region, comprising what is now Ukraine, Hungary, Poland, Romania, and parts of Italy, was under the influence of the AustroHungarian Empire in the late nineteenth and early twentieth centuries.


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The Innovators: How a Group of Inventors, Hackers, Geniuses and Geeks Created the Digital Revolution by Walter Isaacson

1960s counterculture, Ada Lovelace, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AltaVista, Alvin Toffler, Apollo Guidance Computer, Apple II, augmented reality, back-to-the-land, beat the dealer, Bill Atkinson, Bill Gates: Altair 8800, bitcoin, Bletchley Park, Bob Noyce, Buckminster Fuller, Byte Shop, c2.com, call centre, Charles Babbage, citizen journalism, Claude Shannon: information theory, Clayton Christensen, commoditize, commons-based peer production, computer age, Computing Machinery and Intelligence, content marketing, crowdsourcing, cryptocurrency, Debian, desegregation, Donald Davies, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, driverless car, Dynabook, El Camino Real, Electric Kool-Aid Acid Test, en.wikipedia.org, eternal september, Evgeny Morozov, Fairchild Semiconductor, financial engineering, Firefox, Free Software Foundation, Gary Kildall, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Hacker Ethic, Haight Ashbury, Hans Moravec, Howard Rheingold, Hush-A-Phone, HyperCard, hypertext link, index card, Internet Archive, Ivan Sutherland, Jacquard loom, Jaron Lanier, Jeff Bezos, jimmy wales, John Markoff, John von Neumann, Joseph-Marie Jacquard, Leonard Kleinrock, Lewis Mumford, linear model of innovation, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Mitch Kapor, Mother of all demos, Neil Armstrong, new economy, New Journalism, Norbert Wiener, Norman Macrae, packet switching, PageRank, Paul Terrell, pirate software, popular electronics, pre–internet, Project Xanadu, punch-card reader, RAND corporation, Ray Kurzweil, reality distortion field, RFC: Request For Comment, Richard Feynman, Richard Stallman, Robert Metcalfe, Rubik’s Cube, Sand Hill Road, Saturday Night Live, self-driving car, Silicon Valley, Silicon Valley startup, Skype, slashdot, speech recognition, Steve Ballmer, Steve Crocker, Steve Jobs, Steve Wozniak, Steven Levy, Steven Pinker, Stewart Brand, Susan Wojcicki, technological singularity, technoutopianism, Ted Nelson, Teledyne, the Cathedral and the Bazaar, The Coming Technological Singularity, The Nature of the Firm, The Wisdom of Crowds, Turing complete, Turing machine, Turing test, value engineering, Vannevar Bush, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, Whole Earth Review, wikimedia commons, William Shockley: the traitorous eight, Yochai Benkler

In addition to specific notes below, this section draws on William Aspray, John von Neumann and the Origins of Modern Computing (MIT, 1990); Nancy Stern, “John von Neumann’s Influence on Electronic Digital Computing, 1944–1946,” IEEE Annals of the History of Computing, Oct.–Dec. 1980; Stanislaw Ulam, “John von Neumann,” Bulletin of the American Mathematical Society, Feb. 1958; George Dyson, Turing’s Cathedral (Random House, 2012; locations refer to Kindle edition); Herman Goldstine, The Computer from Pascal to von Neumann (Princeton, 1972; locations refer to Kindle edition). 41. Dyson, Turing’s Cathedral, 41. 42. Nicholas Vonneumann, “John von Neumann as Seen by His Brother” (Privately printed, 1987), 22, excerpted as “John von Neumann: Formative Years,” IEEE Annals, Fall 1989. 43.

, 161; Norman Macrae, John von Neumann (American Mathematical Society, 1992), 281. 58. Ritchie, The Computer Pioneers, 178. 59. Presper Eckert oral history, conducted by Nancy Stern, Charles Babbage Institute, Oct. 28, 1977; Dyson, Turing’s Cathedral, 1952. 60. John von Neumann, “First Draft of a Report on the EDVAC,” U.S. Army Ordnance Department and the University of Pennsylvania, June 30, 1945. The report is available at http://www.virtualtravelog.net/wp/wp-content/media/2003-08-TheFirstDraft.pdf. 61. Dyson, Turing’s Cathedral, 1957. See also Aspray, John von Neumann and the Origins of Modern Computing. 62.

Each tube could handle approximately a thousand bits of data at one-hundredth the cost of using a circuit of vacuum tubes. The next-generation ENIAC successor, Eckert and Mauchly wrote in a memo in the summer of 1944, should have racks of these mercury delay line tubes to store both data and rudimentary programming information in digital form. JOHN VON NEUMANN At this point, one of the most interesting characters in the history of computing reenters the tale: John von Neumann, the Hungarian-born mathematician who was a mentor to Turing in Princeton and offered him a job as an assistant. An enthusiastic polymath and urbane intellectual, he made major contributions to statistics, set theory, geometry, quantum mechanics, nuclear weapons design, fluid dynamics, game theory, and computer architecture.


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A Fiery Peace in a Cold War: Bernard Schriever and the Ultimate Weapon by Neil Sheehan

Albert Einstein, anti-communist, Berlin Wall, Boeing 747, Bretton Woods, British Empire, Charles Lindbergh, cuban missile crisis, disinformation, double helix, Dr. Strangelove, European colonialism, it's over 9,000, John von Neumann, Menlo Park, Mikhail Gorbachev, military-industrial complex, mutually assured destruction, Neil Armstrong, Norman Macrae, nuclear winter, operation paperclip, RAND corporation, Ronald Reagan, social contagion, undersea cable, uranium enrichment

BOOK IV STARTING A RACE Chapters 29–31: Schriever interviews; also interviews with Marina von Neumann Whitman and Françoise Ulam and their reminiscences at Hofstra University conference on von Neumann, May 29-June 3, 1988; interviews with Foster Evans and Jacob Wechsler; also Evans’s lecture, “Early Super Work,” published in the Los Alamos Historical Society’s 1996 Behind Tall Fences; interview with Nicholas Vonneuman and his unpublished biography of his brother, “The Legacy of John von Neumann”; John von Neumann Papers in the Manuscript Division of the Library of Congress; Rhodes’s The Making of the Atomic Bomb and Dark Sun; Herman Goldstine’s 1972 The Computer from Pascal to von Neumann; Stanislaw Ulam’s 1976 Adventures of a Mathematician; William Poundstone’s 1992 Prisoner’s Dilemma; Norman Macrae’s 1992 John von Neumann; and Kati Marton’s 2006 The Great Escape: Nine Jews Who Fled Hitler and Changed the World. Chapter 32: Interviews with General Schriever, Col.

Both Schriever and Gardner knew Ramo was indispensable for assembling the array of engineering and scientific talent needed to overcome the technological obstacles. COURTESY OF GENERAL BERNARD SCHRIEVER Cold War forgiveness: John von Neumann (right), a Jewish exile from Hitler’s Europe, conferring with Wernher von Braun, a former SS officer, Nazi Party member, and the führer’s V-2 missile man, during a visit to the Army’s Redstone Arsenal in Alabama. A mathematician and mathematical physicist with a mind second only to Albert Einstein’s, von Neumann headed the scientific advisory committee for the ICBM and lent the project his prestige. JOHN VON NEUMANN PAPERS, MANUSCRIPT DIVISION, LIBRARY OF CONGRESS The heartlessness of an early end: Seven months after immensely impressing Eisenhower at the July 28, 1955, White House briefing on the missile project, “Johnny” von Neumann had been driven to a wheelchair by the ravages of his cancer.

Chapters 72–77: Neufeld, Ballistic Missiles in the United States Air Force, 1945–1960; Heppenheimer’s Countdown; Zubok and Pleshakov, Inside the Kremlin’s Cold War; Taubman’s Khrushchev; Robert Kennedy’s 1968 Thirteen Days: A Memoir of the Cuban Missile Crisis; Fred Kaplan’s 1983 The Wizards of Armageddon; Anatoly Dobrynin’s 1995 In Confidence; Aleksandr Fursenko and Timothy Naftali’s 1997 One Hell of a Gamble: Khrushchev, Castro, and Kennedy, 1958–1964; The Kennedy Tapes: Inside the White House During the Cuban Missile Crisis, Ernest May and Philip Zelikow’s 1997 editing of the tapes of the White House meetings during the crisis; Max Frankel’s 2004 High Noon in the Cold War: Kennedy, Khrushchev and the Cuban Missile Crisis; Fursenko and Naftali’s 2006 Khrushchev’s Cold War; Michael Dobbs’s 2008 One Minute to Midnight: Kennedy, Khrushchev, and Castro on the Brink of Nuclear War; the official SAC history, The Development of Strategic Air Command; Wynn’s RAF Nuclear Deterrent Forces. Chapter 78: Leonid Brezhnev’s cynical remark to his brother is recounted in the 1995 memoir by his niece, Luba Brezhneva’s The World I Left Behind: Pieces of a Past. EPILOGUE THE SCHRIEVER LUCK Chapter 79: The John von Neumann Papers, Manuscript Division of the Library of Congress; Col. Vincent Ford’s memoir; Macrae’s John von Neumann; Pound-stone’s Prisoner’s Dilemma. Chapter 80: Schriever interviews; Col. Vincent Ford’s memoir; interview with Trevor Gardner, Jr. Chapter 81: November 1, 1968, historical monograph on Army Ballistic Missile Agency; Edward Hall interview.


The Dream Machine: J.C.R. Licklider and the Revolution That Made Computing Personal by M. Mitchell Waldrop

Ada Lovelace, air freight, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, Apple II, battle of ideas, Berlin Wall, Bill Atkinson, Bill Duvall, Bill Gates: Altair 8800, Bletchley Park, Boeing 747, Byte Shop, Charles Babbage, Claude Shannon: information theory, Compatible Time-Sharing System, computer age, Computing Machinery and Intelligence, conceptual framework, cuban missile crisis, Dennis Ritchie, do well by doing good, Donald Davies, double helix, Douglas Engelbart, Douglas Engelbart, Dynabook, experimental subject, Fairchild Semiconductor, fault tolerance, Frederick Winslow Taylor, friendly fire, From Mathematics to the Technologies of Life and Death, functional programming, Gary Kildall, Haight Ashbury, Howard Rheingold, information retrieval, invisible hand, Isaac Newton, Ivan Sutherland, James Watt: steam engine, Jeff Rulifson, John von Neumann, Ken Thompson, Leonard Kleinrock, machine translation, Marc Andreessen, Menlo Park, Multics, New Journalism, Norbert Wiener, packet switching, pink-collar, pneumatic tube, popular electronics, RAND corporation, RFC: Request For Comment, Robert Metcalfe, Silicon Valley, Skinner box, Steve Crocker, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Ted Nelson, The Soul of a New Machine, Turing machine, Turing test, Vannevar Bush, Von Neumann architecture, Wiener process, zero-sum game

.: Research Laboratory for Electronics, MIT, 1966), 12. 4. Steve Helms, John von Neumann and Norbert Wiener: From Mathematics to the Technologies of Life and Death (Cambridge, Mass.: MIT Press, 1980), 206. 5. Norbert Wiener, Cybernetics, or Control and CommunicatiOn in the Animal and the Machine, 2d ed. (Cambndge, Mass.: MIT Press, 1961),23. 6. Heims, Von Neumann/Wiener, 189. 7. Norbert Wiener, "A Scientist Rebels," Atlantic Monthly, January 1947, and Bulletin of the Atomic Sci- entlSts, January 1947. 8. Helms, Von Neumann/Wiener, 334-35. 9. John von Neumann and Oskar Morgenstern, Theory of Games and Economic BehaviOr (Princeton, N.J.: Pnnceton University Press, 1944). 10.

Winston, OH 196. 484 BIBLIOGRAPHY BOOKS AND ARTICLES Again, the written matenals listed below are only a tiny fraction of what's avaIlable on the history of computing, but they were partICularly helpful to me in telling the story of LICk and the ARPA com- munity. Aspray, Wilham. "The SCientific ConceptualIzation of Information: A Survey." Annals of the H15tory of Computing 7 (1985). -. "John von Neumann's Contributions to Computing and Computer Science." Annals of the H15- tory of ComputIng 11, no. 3 (1989). -.John von Neumann and the Orzglns of Modern ComputIng. Cambridge, Mass.: MIT Press, 1990. -. "The Intel 4004 MIcroprocessor: What Constituted Invention?" IEEE Annals of the H15tory of Computing 19, no. 3 (1997). Augarten, Stan. BIt by BIt: An Illustrated H15tory of Computers.

Goldstine was awestruck. Before his current incarnation-he was liaison officer for the army's computing substation at the University of Pennsylvania's Moore School of Engineering-Goldstine had been a Ph.D. mathematics instructor at the University of Michigan. So he already knew the legends. At age forty, John von Neumann (pronounced fon NaY-man) held a place in mathematics that could be compared only to that of Albert Einstein in physics. In the single year of 1927, for example, while still a mere instructor at the University of Berlin, von Neumann had put the newly emerging theory of quantum mechanics on a rigorous mathematical footing; established new links between formal logical systems and the foundations of mathematics; and cre- ated a whole new branch of mathematics known as game theory, a way of ana- lyzing how people make decisions when they are competing with each other (among other things, this field gave us the term "zero-sum game").


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Possible Minds: Twenty-Five Ways of Looking at AI by John Brockman

AI winter, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alignment Problem, AlphaGo, artificial general intelligence, Asilomar, autonomous vehicles, basic income, Benoit Mandelbrot, Bill Joy: nanobots, Bletchley Park, Buckminster Fuller, cellular automata, Claude Shannon: information theory, Computing Machinery and Intelligence, CRISPR, Daniel Kahneman / Amos Tversky, Danny Hillis, data science, David Graeber, deep learning, DeepMind, Demis Hassabis, easy for humans, difficult for computers, Elon Musk, Eratosthenes, Ernest Rutherford, fake news, finite state, friendly AI, future of work, Geoffrey Hinton, Geoffrey West, Santa Fe Institute, gig economy, Hans Moravec, heat death of the universe, hype cycle, income inequality, industrial robot, information retrieval, invention of writing, it is difficult to get a man to understand something, when his salary depends on his not understanding it, James Watt: steam engine, Jeff Hawkins, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, Kickstarter, Laplace demon, Large Hadron Collider, Loebner Prize, machine translation, market fundamentalism, Marshall McLuhan, Menlo Park, military-industrial complex, mirror neurons, Nick Bostrom, Norbert Wiener, OpenAI, optical character recognition, paperclip maximiser, pattern recognition, personalized medicine, Picturephone, profit maximization, profit motive, public intellectual, quantum cryptography, RAND corporation, random walk, Ray Kurzweil, Recombinant DNA, Richard Feynman, Rodney Brooks, self-driving car, sexual politics, Silicon Valley, Skype, social graph, speech recognition, statistical model, Stephen Hawking, Steven Pinker, Stewart Brand, strong AI, superintelligent machines, supervolcano, synthetic biology, systems thinking, technological determinism, technological singularity, technoutopianism, TED Talk, telemarketer, telerobotics, The future is already here, the long tail, the scientific method, theory of mind, trolley problem, Turing machine, Turing test, universal basic income, Upton Sinclair, Von Neumann architecture, Whole Earth Catalog, Y2K, you are the product, zero-sum game

The history of computing can be divided into an Old Testament and a New Testament: before and after electronic digital computers and the codes they spawned proliferated across the Earth. The Old Testament prophets, who delivered the underlying logic, included Thomas Hobbes and Gottfried Wilhelm Leibniz. The New Testament prophets included Alan Turing, John von Neumann, Claude Shannon, and Norbert Wiener. They delivered the machines. Alan Turing wondered what it would take for machines to become intelligent. John von Neumann wondered what it would take for machines to self-reproduce. Claude Shannon wondered what it would take for machines to communicate reliably, no matter how much noise intervened. Norbert Wiener wondered how long it would take for machines to assume control.

Since the original of The Human Use of Human Beings is now out of print, lost to us is Wiener’s cri de coeur, more relevant today than when he wrote it sixty-eight years ago: “We must cease to kiss the whip that lashes us.” MIND, THINKING, INTELLIGENCE Among the reasons we don’t hear much about cybernetics today, two are central: First, although The Human Use of Human Beings was considered an important book in its time, it ran counter to the aspirations of many of Wiener’s colleagues, including John von Neumann and Claude Shannon, who were interested in the commercialization of the new technologies. Second, computer pioneer John McCarthy disliked Wiener and refused to use Wiener’s term “Cybernetics.” McCarthy, in turn, coined the term “artificial intelligence” and became a founding father of that field.

In my own work with experimentalists on building quantum computers, I typically find that some of the technological steps I expect to be easy turn out to be impossible, whereas some of the tasks I imagine to be impossible turn out to be easy. You don’t know until you try. In the 1950s, partly inspired by conversations with Wiener, John von Neumann introduced the notion of the “technological singularity.” Technologies tend to improve exponentially, doubling in power or sensitivity over some interval of time. (For example, since 1950, computer technologies have been doubling in power roughly every two years, an observation enshrined as Moore’s Law.)


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The Perfect Bet: How Science and Math Are Taking the Luck Out of Gambling by Adam Kucharski

Ada Lovelace, Albert Einstein, Antoine Gombaud: Chevalier de Méré, beat the dealer, behavioural economics, Benoit Mandelbrot, Bletchley Park, butterfly effect, call centre, Chance favours the prepared mind, Claude Shannon: information theory, collateralized debt obligation, Computing Machinery and Intelligence, correlation does not imply causation, diversification, Edward Lorenz: Chaos theory, Edward Thorp, Everything should be made as simple as possible, Flash crash, Gerolamo Cardano, Henri Poincaré, Hibernia Atlantic: Project Express, if you build it, they will come, invention of the telegraph, Isaac Newton, Johannes Kepler, John Nash: game theory, John von Neumann, locking in a profit, Louis Pasteur, Nash equilibrium, Norbert Wiener, p-value, performance metric, Pierre-Simon Laplace, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, random walk, Richard Feynman, Ronald Reagan, Rubik’s Cube, statistical model, The Design of Experiments, Watson beat the top human players on Jeopardy!, zero-sum game

Review of Economic Studies 70 (2003): 395–415. 147Von Neumann completed his solution: Details of the dispute were given in: Kjedldsen, T. H. “John von Neumann’s Conception of the Minimax Theorem: A Journey Through Different Mathematical Contexts.” Archive for History of Exact Science 56 (2001). 149While earning his master’s degree in 2003: Follek, Robert. “Soar-Bot: A Rule-Based System for Playing Poker” (MSc diss., School of Computer Science and Information Systems, Pace University, 2003). 150Led by David Hilbert: O’Connor, J. J., and E. F. Robertson. “Biography of John von Neumann.” JOC/EFR, October 2003. http://www-history.mcs.st-and.ac.uk/Biographies/Von_Neumann.html. 150some inconsistencies in the US Constitution: “Kurt Gödel.”

Faced with having to calculate a vast set of possibilities—the sort of monotonous work he usually tried to avoid—Ulam realized it might be quicker just to lay out the cards several times and watch what happened. If he repeated the experiment enough times, he would end up with a good idea of the answer without doing a single calculation. Wondering whether the same technique could also help with the neutron problem, Ulam took the idea to one of his closest colleagues, a mathematician by the name of John von Neumann. The two had known each other for over a decade. It was von Neumann who’d suggested Ulam leave Poland for America in the 1930s; he’d also been the one who invited Ulam to join Los Alamos in 1943. They made quite the pair, portly von Neumann in his immaculate suits—jacket always on—and Ulam with his absent-minded fashion sense and dazzling green eyes.

Substitute talking and silence for advertising and cutting promotions, and it is the same problem the advertising firms faced. Nash received his PhD in 1950, for a twenty-seven-page thesis describing how his equilibrium can sometimes thwart seemingly beneficial outcomes. But Nash wasn’t the first person to take a mathematical hammer to the problem of competitive games. History has given that accolade to John von Neumann. Although later known for his time at Los Alamos and Princeton, in 1926 von Neumann was a young lecturer at the University of Berlin. In fact, he was the youngest in its history. Despite his prodigious academic record, however, there were still some things he wasn’t very good at. One of them was poker.


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Thinking in Bets by Annie Duke

banking crisis, behavioural economics, Bernie Madoff, Cass Sunstein, cognitive bias, cognitive dissonance, cognitive load, Daniel Kahneman / Amos Tversky, delayed gratification, Demis Hassabis, disinformation, Donald Trump, Dr. Strangelove, en.wikipedia.org, endowment effect, Estimating the Reproducibility of Psychological Science, fake news, Filter Bubble, Herman Kahn, hindsight bias, Jean Tirole, John Nash: game theory, John von Neumann, loss aversion, market design, mutually assured destruction, Nate Silver, p-value, phenotype, prediction markets, Richard Feynman, ride hailing / ride sharing, Stanford marshmallow experiment, Stephen Hawking, Steven Pinker, systematic bias, TED Talk, the scientific method, The Signal and the Noise by Nate Silver, urban planning, Walter Mischel, Yogi Berra, zero-sum game

The information about von Neumann, in addition to the sources mentioned in the section (which are cited in the Selected Bibliography and Recommendations for Further Reading), are from the following sources: Boston Public Library, “100 Most Influential Books of the Century,” posted on TheGreatestBooks.org; Tim Hartford, “A Beautiful Theory,” Forbes, December 10, 2006; Institute for Advanced Study, “John von Neumann’s Legacy,” IAS.edu; Alexander Leitch, “von Neumann, John,” A Princeton Companion (1978); Robert Leonard, “From Parlor Games to Social Science: von Neumann, Morgenstern, and the Creation of Game Theory 1928–1944,” Journal of Economic Literature (1995). The quotes from reviews that greeted Theory of Games are from Harold W. Kuhn’s introduction to the sixtieth anniversary edition. The influences behind the title character in Dr. Strangelove either are alluringly vague or differ based on who’s telling (or speculating). John von Neumann shared a number of physical characteristcs with the character and is usually cited as an influence.

That makes poker a great place to find innovative approaches to overcoming this struggle. And the value of poker in understanding decision-making has been recognized in academics for a long time. Dr. Strangelove It’s hard for a scientist to become a household name. So it shouldn’t be surprising that for most people the name John von Neumann doesn’t ring a bell. That’s a shame because von Neumann is a hero of mine, and should be to anyone committed to making better decisions. His contributions to the science of decision-making were immense, and yet they were just a footnote in the short life of one of the greatest minds in the history of scientific thought.

Strangelove: a heavily accented, crumpled, wheelchair-bound genius whose strategy of relying on mutually assured destruction goes awry when an insane general sends a single bomber on an unauthorized mission that could trigger the automated firing of all American and Soviet nuclear weapons. In addition to everything else he accomplished, John von Neumann is also the father of game theory. After finishing his day job on the Manhattan Project, he collaborated with Oskar Morgenstern to publish Theory of Games and Economic Behavior in 1944. The Boston Public Library’s list of the “100 Most Influential Books of the Century” includes Theory of Games.


pages: 518 words: 107,836

How Not to Network a Nation: The Uneasy History of the Soviet Internet (Information Policy) by Benjamin Peters

Albert Einstein, American ideology, Andrei Shleifer, Anthropocene, Benoit Mandelbrot, bitcoin, Brownian motion, Charles Babbage, Claude Shannon: information theory, cloud computing, cognitive dissonance, commons-based peer production, computer age, conceptual framework, continuation of politics by other means, crony capitalism, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Graeber, disinformation, Dissolution of the Soviet Union, Donald Davies, double helix, Drosophila, Francis Fukuyama: the end of history, From Mathematics to the Technologies of Life and Death, Gabriella Coleman, hive mind, index card, informal economy, information asymmetry, invisible hand, Jacquard loom, John von Neumann, Kevin Kelly, knowledge economy, knowledge worker, Lewis Mumford, linear programming, mandelbrot fractal, Marshall McLuhan, means of production, megaproject, Menlo Park, Mikhail Gorbachev, military-industrial complex, mutually assured destruction, Network effects, Norbert Wiener, packet switching, Pareto efficiency, pattern recognition, Paul Erdős, Peter Thiel, Philip Mirowski, power law, RAND corporation, rent-seeking, road to serfdom, Ronald Coase, scientific mainstream, scientific management, Steve Jobs, Stewart Brand, stochastic process, surveillance capitalism, systems thinking, technoutopianism, the Cathedral and the Bazaar, the strength of weak ties, The Structural Transformation of the Public Sphere, transaction costs, Turing machine, work culture , Yochai Benkler

Wiener, Cybernetics, 1–25, 155–168. 8. Ibid., 16. 9. Dupuy, Mechanization of the Mind. See also John von Neumann, The Computer and the Brain, 2nd ed. (New Haven: Yale University Press, [1958] 2000). 10. Quoted in Claus Pias, “Analog, Digital, and the Cybernetic Illusion,” Kybernetes 34 (3–4) (2005): 544. 11. Claus Pias, ed., Cybernetics-Kybernetik 2: The Macy-Conferences 1946–1953 (Berlin: Diaphanes, 2004). 12. Steve J. Heims, The Cybernetics Group (Cambridge: MIT Press, 1991). 13. Ibid., 52–53, 207. 14. William Aspray, John von Neumann and the Origins of Modern Computing (Cambridge: MIT Press, 1990). 15. David Lipset, Gregory Bateson: The Legacy of a Scientist (New York: Prentice Hall, 1980).

Borrowing from the language of Hannah Arendt, it recasts the Soviet network experience in light of other national network projects in the latter half of the twentieth century, suggesting the ways that the Soviet experience may appear uncomfortably close to our modern network situation. A few other summary observations for scholar and general-interest reader are offered in close. 1 A Global History of Cybernetics I am thinking about something much more important than bombs. I am thinking about computers. —John von Neumann, 1946 Cybernetics nursed early national computer network projects on both sides of the cold war. Cybernetics was a postwar systems science concerned with communication and control—and although its significance has been well documented in the history of science and technology, its implications as a carrier of early ideas about and language for computational communication have been largely neglected by communication and media scholars.1 This chapter discusses how cybernetics became global early in the cold war, coalescing first in postwar America before diffusing to other parts of the world, especially Soviet Union after Stalin’s death in 1953, as well as how Soviet cybernetics shaped the scientific regime for governing economics that eventually led to the nationwide network projects imagined in the late 1950s and early 1960s.

Foundation in New York City. The Macy Conferences, as they were informally known, staked out a spacious interdisciplinary purview for cybernetic research.11 In addition to McCulloch, who directed the conferences, a few noted participants included Wiener himself, the mathematician and game theorist John von Neumann, leading anthropologist Margaret Mead and her then husband Gregory Bateson, founding information theorist and engineer Claude Shannon, sociologist-statistician and communication theorist Paul Lazarsfeld, psychologist and computer scientist J.C.R. Licklider, as well as influential psychiatrists, psychoanalysts, and philosophers such as Kurt Lewin, F.S.C.


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Computer: A History of the Information Machine by Martin Campbell-Kelly, William Aspray, Nathan L. Ensmenger, Jeffrey R. Yost

Ada Lovelace, air freight, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Apple's 1984 Super Bowl advert, barriers to entry, Bill Gates: Altair 8800, Bletchley Park, borderless world, Buckminster Fuller, Build a better mousetrap, Byte Shop, card file, cashless society, Charles Babbage, cloud computing, combinatorial explosion, Compatible Time-Sharing System, computer age, Computer Lib, deskilling, don't be evil, Donald Davies, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Jenner, Evgeny Morozov, Fairchild Semiconductor, fault tolerance, Fellow of the Royal Society, financial independence, Frederick Winslow Taylor, game design, garden city movement, Gary Kildall, Grace Hopper, Herman Kahn, hockey-stick growth, Ian Bogost, industrial research laboratory, informal economy, interchangeable parts, invention of the wheel, Ivan Sutherland, Jacquard loom, Jeff Bezos, jimmy wales, John Markoff, John Perry Barlow, John von Neumann, Ken Thompson, Kickstarter, light touch regulation, linked data, machine readable, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Mitch Kapor, Multics, natural language processing, Network effects, New Journalism, Norbert Wiener, Occupy movement, optical character recognition, packet switching, PageRank, PalmPilot, pattern recognition, Pierre-Simon Laplace, pirate software, popular electronics, prediction markets, pre–internet, QWERTY keyboard, RAND corporation, Robert X Cringely, Salesforce, scientific management, Silicon Valley, Silicon Valley startup, Steve Jobs, Steven Levy, Stewart Brand, Ted Nelson, the market place, Turing machine, Twitter Arab Spring, Vannevar Bush, vertical integration, Von Neumann architecture, Whole Earth Catalog, William Shockley: the traitorous eight, women in the workforce, young professional

Licklider was a consummate political operator who motivated a generation of computer scientists and obtained government funding for them to work in the fields of human-computer interaction and networked computing. COURTESY OF MIT MUSEUM. Working at the Institute for Advanced Study, Princeton, Herman Goldstine and John von Neumann introduced the “flow diagram” (above) as a way of managing the complexity of programs and communicating them to others. COURTESY OF INSTITUTE FOR ADVANCED STUDY, PRINCETON: Herman H. Goldstine and John von Neumann, Planning and Coding of Problems for an Electronic Computing Instrument, Part II, Volume 2 (1948), p. 28. Programming languages, such as FORTRAN, COBOL, and BASIC, improved the productivity of programmers and enabled nonexperts to write programs.

Other electrical manufacturers and business-machine companies, including IBM, also turned to this enterprise. The computer makers found a ready market in government agencies, insurance companies, and large manufacturers. The basic functional specifications of the computer were set out in a report written by John von Neumann in 1945, and these specifications are still largely followed today. However, decades of continuous innovation have followed the original conception. These innovations are of two types. One is the improvement in components, leading to faster processing speed, greater information-storage capacity, improved price/performance, better reliability, less required maintenance, and the like: today’s computers are literally millions of times better than the first computers on almost all measures of this kind.

It was typical of Turing to be able to express a complex mathematical argument in terms that a nonmathematician could understand. The computability of mathematical functions would later become a cornerstone of computer science theory. Turing’s growing reputation earned him a research studentship at Princeton University to study under Alonzo Church in 1937. There he encountered John von Neumann, a founding professor of the Institute for Advanced Study at Princeton, who a few years later would play a pivotal role in the invention of the modern computer. Von Neumann was deeply interested in Turing’s work and invited him to stay on at the Institute. Turing, however, decided to return to Britain.


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Fancy Bear Goes Phishing: The Dark History of the Information Age, in Five Extraordinary Hacks by Scott J. Shapiro

3D printing, 4chan, active measures, address space layout randomization, air gap, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, availability heuristic, Bernie Sanders, bitcoin, blockchain, borderless world, Brian Krebs, business logic, call centre, carbon tax, Cass Sunstein, cellular automata, cloud computing, cognitive dissonance, commoditize, Compatible Time-Sharing System, Computing Machinery and Intelligence, coronavirus, COVID-19, CRISPR, cryptocurrency, cyber-physical system, Daniel Kahneman / Amos Tversky, Debian, Dennis Ritchie, disinformation, Donald Trump, double helix, Dr. Strangelove, dumpster diving, Edward Snowden, en.wikipedia.org, Evgeny Morozov, evil maid attack, facts on the ground, false flag, feminist movement, Gabriella Coleman, gig economy, Hacker News, independent contractor, information security, Internet Archive, Internet of things, invisible hand, John Markoff, John von Neumann, Julian Assange, Ken Thompson, Larry Ellison, Laura Poitras, Linda problem, loss aversion, macro virus, Marc Andreessen, Mark Zuckerberg, Menlo Park, meta-analysis, Minecraft, Morris worm, Multics, PalmPilot, Paul Graham, pirate software, pre–internet, QWERTY keyboard, Ralph Nader, RAND corporation, ransomware, Reflections on Trusting Trust, Richard Stallman, Richard Thaler, Ronald Reagan, Satoshi Nakamoto, security theater, Shoshana Zuboff, side hustle, Silicon Valley, Skype, SoftBank, SQL injection, Steve Ballmer, Steve Jobs, Steven Levy, Stuxnet, supply-chain attack, surveillance capitalism, systems thinking, TaskRabbit, tech billionaire, tech worker, technological solutionism, the Cathedral and the Bazaar, the new new thing, the payments system, Turing machine, Turing test, Unsafe at Any Speed, vertical integration, Von Neumann architecture, Wargames Reagan, WarGames: Global Thermonuclear War, Wayback Machine, web application, WikiLeaks, winner-take-all economy, young professional, zero day, éminence grise

Born in Budapest: Stanislaw Ulam, “John von Neumann, 1903–1957,” Bulletin of the American Mathematical Society 64, no. 3, pt. 2 (May 1958): 1; George Dyson, Turing’s Cathedral: The Origins of the Digital Universe (New York: Vintage, 2012), chap. 4; Herman Goldstine, The Computer: From Pascal to von Neumann (Princeton, NJ: Princeton University Press, 1980). In 1913, Emperor Franz Joseph ennobled John’s family for his father’s service to the Hapsburgs, adding the honorific Margittai to the family name. (Jonas Neumann de Margittai later Germanized his name to become John von Neumann.) both degrees simultaneously: Ulam, “John von Neumann,” 2.

(it weighed thirty tons): Steven Levy, “A Brief History of the ENIAC,” Smithsonian Magazine, November 2013, https://www.smithsonianmag.com/history/the-brief-history-of-the-eniac-computer-3889120/. Levy claims that the ENIAC had 18,000 vacuum tubes, the figure used in the text, but other estimates range from 17,468 to 19,000. to study natural systems: John von Neumann, Theory of Self-Reproducing Automata, edited and completed by Arthur W. Burks (Champaign: University of Illinois Press, 1966), 64–73. Von Neumann is also credited: John von Neumann, “A First Draft of a Report on the EDVAC,” IEEE Annals of the History of Computing 15, no. 4 (1993). The credit to von Neumann has been much debated. See Dyson, Turing’s Cathedral, 77–80; B. J. Copeland and Giovanni Sommaruga, “Did Zuse Anticipate Turing and von Neumann?

Descartes was summoned: “Go Forth and Replicate,” Scientific American 285, no. 2 (August 2001): 34–43. In 1949, von Neumann set out: Von Neumann completed two studies on self-replication. See “The General and Logical Theory of Automata,” in John von Neumann Collected Works, 5:288–328, and “Probabilistic Logics and the Synthesis of Reliable Organisms from Unreliable Components,” in John von Neumann Collected Works, 5:329–378. In 1957, von Neumann passed away, leaving two manuscripts on self-replicating automata unpublished: “Theory and Organization of Complicated Automata,” five lectures delivered at the University of Illinois, December 1949, and “The Theory of Automata: Construction, Reproduction, Homogeneity,” started in 1952 and worked on for a year.


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The Information: A History, a Theory, a Flood by James Gleick

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AltaVista, bank run, bioinformatics, Bletchley Park, Brownian motion, butterfly effect, Charles Babbage, citation needed, classic study, Claude Shannon: information theory, clockwork universe, computer age, Computing Machinery and Intelligence, conceptual framework, crowdsourcing, death of newspapers, discovery of DNA, Donald Knuth, double helix, Douglas Hofstadter, en.wikipedia.org, Eratosthenes, Fellow of the Royal Society, Gregor Mendel, Gödel, Escher, Bach, Henri Poincaré, Honoré de Balzac, index card, informal economy, information retrieval, invention of the printing press, invention of writing, Isaac Newton, Jacquard loom, Jaron Lanier, jimmy wales, Johannes Kepler, John von Neumann, Joseph-Marie Jacquard, Lewis Mumford, lifelogging, Louis Daguerre, machine translation, Marshall McLuhan, Menlo Park, microbiome, Milgram experiment, Network effects, New Journalism, Norbert Wiener, Norman Macrae, On the Economy of Machinery and Manufactures, PageRank, pattern recognition, phenotype, Pierre-Simon Laplace, pre–internet, quantum cryptography, Ralph Waldo Emerson, RAND corporation, reversible computing, Richard Feynman, Rubik’s Cube, Simon Singh, Socratic dialogue, Stephen Hawking, Steven Pinker, stochastic process, talking drums, the High Line, The Wisdom of Crowds, transcontinental railway, Turing machine, Turing test, women in the workforce, yottabyte

♦ “CONTRARY TO APPEARANCES, SUCH A PROPOSITION”: Ibid., 151 n15. ♦ “AMAZING FACT”—“THAT OUR LOGICAL INTUITIONS”: Kurt Gödel, “Russell’s Mathematical Logic” (1944), 124. ♦ “A SUDDEN THUNDERBOLT FROM THE BLUEST OF SKIES”: Douglas R. Hofstadter, I Am a Strange Loop, 166. ♦ “THE IMPORTANT POINT”: John von Neumann, “Tribute to Dr. Gödel” (1951), quoted in Steve J. Heims, John von Neumann and Norbert Weiner (Cambridge, Mass.: MIT Press, 1980), 133. ♦ “IT MADE ME GLAD”: Russell to Leon Henkin, 1 April 1963. ♦ “MATHEMATICS CANNOT BE INCOMPLETE”: Ludwig Wittgenstein, Remarks on the Foundations of Mathematics (Cambridge, Mass.: MIT Press, 1967), 158

Gödel’s first public mention of his discovery, on the third and last day of a philosophical conference in Königsberg in 1930, drew no response; only one person seems to have heard him at all, a Hungarian named Neumann János. This young mathematician was in the process of moving to the United States, where he would soon and for the rest of his life be called John von Neumann. He understood Gödel’s import at once; it stunned him, but he studied it and was persuaded. No sooner did Gödel’s paper appear than von Neumann was presenting it to the mathematics colloquium at Princeton. Incompleteness was real. It meant that mathematics could never be proved free of self-contradiction.

.♦ Gödel’s retort took care of them both. “Russell evidently misinterprets my result; however, he does so in a very interesting manner,” he wrote. “In contradistinction Wittgenstein … advances a completely trivial and uninteresting misinterpretation.”♦ In 1933 the newly formed Institute for Advanced Study, with John von Neumann and Albert Einstein among its first faculty members, invited Gödel to Princeton for the year. He crossed the Atlantic several more times that decade, as fascism rose and the brief glory of Vienna began to fade. Gödel, ignorant of politics and naïve about history, suffered depressive breakdowns and bouts of hypochondria that forced him into sanatoria.


Theory of Games and Economic Behavior: 60th Anniversary Commemorative Edition (Princeton Classic Editions) by John von Neumann, Oskar Morgenstern

Abraham Wald, Albert Einstein, business cycle, collective bargaining, full employment, Isaac Newton, John Nash: game theory, John von Neumann, linear programming, Nash equilibrium, Parkinson's law, Paul Samuelson, profit motive, RAND corporation, the market place, zero-sum game

ROSENBLITH Heads I Win, and Tails, You Lose, BY PAUL SAMUELSON Big D, BY PAUL CRUME Mathematics of Games and Economics, BY E. ROWLAND Theory of Games, BY CLAUDE CHEVALLEY Mathematical Theory of Poker Is Applied to Business Problems, BY WILL LISSNER A Theory of Strategy, BY JOHN MCDONALD The Collaboration between Oskar Morgenstern and John von Neumann on the Theory of Games, BY OSKAR MORGENSTERN Index Credits Introduction HAROLD W. KUHN Although John von Neumann was without doubt “the father of game theory,” the birth took place after a number of miscarriages. From an isolated and amazing minimax solution of a zero-sum two-person game in 1713 [1] to sporadic considerations by E. Zermelo [2], E.

It was originated by one of the chief participants in the development of the bomb, the young and already great contemporary mathematician, John von Neumann, whose work in games was given a preliminary exploration in an essay on poker in Fortune (March, 1948). This story began more than a year ago when the author innocently looked into the game of poker with the idea of providing Fortune’s readers with some diverting comments on the national indoor game of strategy. When the first part of the story was published (March, 1948), however, it seemed that we had the bear by the tail. Madiematician John von Neumann, unknown to the poker-playing fraternity, had got there first and really made something out of it.

Theory of Games and Economic Behavior Theory of Games and Economic Behavior John von Neumann and Oskar Morgenstern With an introduction by Harold W. Kuhn and an afterword by Ariel Rubinstein SIXTIETH-ANNIVERSARY EDITION Copyright © 1944 by Princeton University Press Copyright © renewed 1972 Princeton University Press Sixtieth-Anniversary Edition copyright © 2004 Princeton University Press Published by Princeton University Press, 41 William Street, Princeton, New Jersey 08540 In the United Kingdom: Princeton University Press, 3 Market Place, Woodstock, Oxfordshire 0X20 1SY All Rights Reserved Second Edition, 1947 Third Edition, 1953 Fourth printing, and first paperback printing, of Sixtieth Anniversary Edition, 2007 Paperback ISBN-13: 978-0-691-13061-3 Paperback ISBN-10: 0-691-13061-2 Library of Congress Control Number 2004100346 ISBN-13: 978-0-691-11993-9 ISBN-10: 0-691-11993-7 British Library Cataloging-in-Publication Data is available This book has been composed in Baskerville MT, Monotype Century, and Helvetica Condensed Printed on acid-free paper. ∞ press.princeton.edu Primed in the United States of America 9 10 Contents Introduction, BY HAROLD W.


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Rise of the Machines: A Cybernetic History by Thomas Rid

1960s counterculture, A Declaration of the Independence of Cyberspace, agricultural Revolution, Albert Einstein, Alistair Cooke, Alvin Toffler, Apple II, Apple's 1984 Super Bowl advert, back-to-the-land, Berlin Wall, Bletchley Park, British Empire, Brownian motion, Buckminster Fuller, business intelligence, Charles Babbage, Charles Lindbergh, Claude Shannon: information theory, conceptual framework, connected car, domain-specific language, Douglas Engelbart, Douglas Engelbart, Dr. Strangelove, dumpster diving, Extropian, full employment, game design, global village, Hacker News, Haight Ashbury, Herman Kahn, Howard Rheingold, Ivan Sutherland, Jaron Lanier, job automation, John Gilmore, John Markoff, John Perry Barlow, John von Neumann, Kevin Kelly, Kubernetes, Marshall McLuhan, Menlo Park, military-industrial complex, Mitch Kapor, Mondo 2000, Morris worm, Mother of all demos, Neal Stephenson, new economy, New Journalism, Norbert Wiener, offshore financial centre, oil shale / tar sands, Oklahoma City bombing, operational security, pattern recognition, public intellectual, RAND corporation, Silicon Valley, Simon Singh, Snow Crash, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, systems thinking, technoutopianism, Telecommunications Act of 1996, telepresence, The Hackers Conference, Timothy McVeigh, Vernor Vinge, We are as Gods, Whole Earth Catalog, Whole Earth Review, Y2K, Yom Kippur War, Zimmermann PGP

Woirol, The Technological Unemployment and Structural Unemployment Debates (Westport, CT: Greenwood, 1996), 78. 75.David Fouquet, “Automation Held Threat to US Value Code,” Washington Post, May 12, 1964, A24. 76.Diebold, Beyond Automation, 10. 77.Fouquet, “Automation Held Threat.” 78.Diebold, Automation, 170. 79.Diebold, Beyond Automation, 206. 80.Kahn left Rand before publishing The Year 2000. 81.Herman Kahn and Anthony Wiener, The Year 2000: A Framework for Speculation on the Next Thirty-Three Years (London: Macmillan, 1967), 350. 4. ORGANISMS 1.Pesi Masani, Norbert Wiener, 1894–1964 (Basel: Burkhäuser, 1990), 225. 2.Paul E. Ceruzzi, A History of Modern Computing (Cambridge, MA: MIT Press, 2003), 21. 3.Masani, Norbert Wiener, 184. 4.John von Neumann to Norbert Wiener, November 29, 1946, in ibid., 243. 5.John von Neumann, Theory of Self-Reproducing Automata, ed. Arthur W. Burks (Urbana: University of Illinois Press, 1966), fifth lecture, 78. 6.Ibid., 79. 7.Ibid., 86. 8.Ibid., 87. 9.Edward F. Moore, “Artificial Living Plants,” Scientific American, October 1956, 118–26. 10.Ibid., 118. 11.Ibid., 119. 12.Ibid., 121. 13.Ibid., 122. 14.Ibid., 126. 15.David R.

Licklider, “Topics for Discussion at the Forthcoming Meeting,” Memorandum for Affiliates of the Intergalactic Computer Network, Advanced Research Projects Agency, Washington, DC, April 25, 1963. 86.Dan van der Vat, “Jack Good,” Guardian, April 29, 2009. 87.Irving J. Good, “Speculations concerning the First Ultraintelligent Machine,” Advances in Computers 6 (1965): 31–88. 88.John von Neumann discussed the effects of ever-accelerating technological progress with colleagues. In one such discussion, he allegedly said that humankind is approaching an essential “singularity” after which human affairs will be altered forever. See the recollection of Stanislaw Ulam: “Tribute to John von Neumann,” Bulletin of the American Mathematical Society 64, no. 3 (1958): 5. 89.Vernor Vinge, “First Word,” Omni 5, no. 1 (January 1983): 10. For Vinge’s weak scientific output, see his Google Scholar profile, http://bit.ly/vinge-scholar+. 90.Jürgen Kraus, “Selbstreproduktion bei Programmen” (master’s thesis, Universität Dortmund, Abteilung Informatik, 1980). 91.Ibid., 2. 92.Ibid., 154. 93.Ibid., 161. 94.Ibid., 160. 95.Ronald R.

And there was no reason why the theory could not be applied to all complex systems. Many leading minds in engineering, mathematics, biology, and psychology, but also sociology, philosophy, anthropology, and political science, would initially be drawn to the new thinking of adaptive systems. The best-known early cyberneticists were the mathematician John von Neumann, a fellow polyglot, computer pioneer, and prominent professor at the Institute for Advanced Study in Princeton still in his early forties, nine years younger than Wiener; the American neurophysiologist and neural networks pioneer Warren McCulloch; the Austrian American physicist Heinz von Foerster; and the Mexican physician Arturo Rosenblueth, one of Wiener’s closest friends and collaborators.


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Turing's Vision: The Birth of Computer Science by Chris Bernhardt

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Andrew Wiles, Bletchley Park, British Empire, cellular automata, Charles Babbage, Claude Shannon: information theory, complexity theory, Computing Machinery and Intelligence, Conway's Game of Life, discrete time, Douglas Hofstadter, Georg Cantor, Gödel, Escher, Bach, Henri Poincaré, Internet Archive, Jacquard loom, John Conway, John von Neumann, Joseph-Marie Jacquard, Ken Thompson, Norbert Wiener, Paul Erdős, Reflections on Trusting Trust, Turing complete, Turing machine, Turing test, Von Neumann architecture

We conclude by giving Turing’s proof that computable numbers are not effectively enumerable. Chapter 9 The final chapter describes both what happened to Turing and the computer in the years after his paper was published. It begins with Turing going to Princeton to obtain his Ph.D. under Church. This is where he gets to know John von Neumann. It then describes Turing’s move back to England and his work during the Second World War on code breaking. After this, we briefly look at how the modern computer came into existence during the forties. The procession from sophisticated calculator, to universal computer, to stored-program universal computer is outlined.

McCulloch and Pitts realized that this was a simplified model of how brains actually worked, but studied neural nets to see how logic could be handled by them. Since their nets had basic features in common with neurons and the human brain, their work, they hoped, would shed some light on logical reasoning in people. Their paper caught the attention of both John von Neumann and Norbert Wiener. Both were very impressed. Wiener, the famous American mathematician and philosopher, saw the power of feedback loops. He realized that they were widely applicable and used this idea to develop the theory of cybernetics.1 Cybernetics naturally led to the idea of machines that could learn and, in turn, led to the birth of artificial intelligence.

What is surprising is that we can design a Turing machine to simulate a modern computer, showing that Turing machines are equivalent in computing power to modern computers. We will sketch how this is done. The first step is to get a concrete description of the modern computer. Von Neumann Architecture Later we will talk more about John von Neumann, but it is important to know a few facts before we proceed. The First Draft of a Report on the EDVAC is probably the most important paper on the design of modern computers. It was written in 1945, as the first electronic computers were being built. It described the basic outline of how a computer should be designed, incorporating what had been learned from the design of earlier machines.


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In Our Own Image: Savior or Destroyer? The History and Future of Artificial Intelligence by George Zarkadakis

3D printing, Ada Lovelace, agricultural Revolution, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, animal electricity, anthropic principle, Asperger Syndrome, autonomous vehicles, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, Bletchley Park, British Empire, business process, carbon-based life, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, complexity theory, Computing Machinery and Intelligence, continuous integration, Conway's Game of Life, cosmological principle, dark matter, data science, deep learning, DeepMind, dematerialisation, double helix, Douglas Hofstadter, driverless car, Edward Snowden, epigenetics, Flash crash, Google Glasses, Gödel, Escher, Bach, Hans Moravec, income inequality, index card, industrial robot, intentional community, Internet of things, invention of agriculture, invention of the steam engine, invisible hand, Isaac Newton, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, job automation, John von Neumann, Joseph-Marie Jacquard, Kickstarter, liberal capitalism, lifelogging, machine translation, millennium bug, mirror neurons, Moravec's paradox, natural language processing, Nick Bostrom, Norbert Wiener, off grid, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, Paul Erdős, Plato's cave, post-industrial society, power law, precautionary principle, prediction markets, Ray Kurzweil, Recombinant DNA, Rodney Brooks, Second Machine Age, self-driving car, seminal paper, Silicon Valley, social intelligence, speech recognition, stem cell, Stephen Hawking, Steven Pinker, Strategic Defense Initiative, strong AI, Stuart Kauffman, synthetic biology, systems thinking, technological singularity, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K

When Fremont-Smith became the Medical Director of the Macy Foundation, he set up a series of annual conferences that expanded the Man–Machine Project. Hosted by the Macy Foundation, these became known as the ‘Macy Conferences on Cybernetics’. Cybernetics as a field grew out of these interdisciplinary meetings, held from 1946 until 1953, which brought together a number of notable post-war intellectuals, including Norbert Wiener, John von Neumann, Warren McCulloch, Claude Shannon, Heinz von Foerster and W. Ross Ashby. From its original focus on machines and animals, cybernetics quickly broadened in scope to encompass the workings of the mind (e.g. in the work of Bateson and Ashby) as well as social systems (e.g. Stafford Beer’s management cybernetics), thus rediscovering Plato’s original focus on the control relations in society.

I will return to the very interesting connection of cybernetics, Plato and global governance later in the book. For now, I want to focus on four individuals who took part in the Macy Conferences, and whose work laid the foundations for Artificial Intelligence: Norbert Wiener, Claude Shannon, Warren McCulloch and John von Neumann. We have already met the first two. Norbert Wiener was the grand visionary of cybernetics. Inspired by mechanical control systems, such as artillery targeting and servomechanisms, as well as Claude Shannon’s mathematical theory of communication and information, he articulated the theory of cybernetics in his landmark book, Cybernetics, of 1948.4 Godfather number two, Claude Shannon, was the genius who gave us information theory.

Finally, there comes a tipping point, where global change happens and the artificial, agent-based system becomes intelligent, in a similar fashion to the neuron-based human brain.6 The fourth cybernetician godfather of Artificial Intelligence, who also took part in the Macy Conferences, was the legendary Hungarian-American mathematician John von Neumann (1903–1957). He was the modern equivalent of Gottfried Leibniz, a polymath who made fundamental contributions to several sciences including mathematics, computing, cybernetics, logic, economics and quantum physics – to name but a few! His last work, before his untimely death at the age of fifty-three, was an unfinished manuscript entitled ‘The Computer and the Brain’, which shows how deeply interested von Neumann had become in the nascent science of Artificial Intelligence.7 During the time he participated in the Macy Conferences, von Neumann expanded on his theory of self-replicating automata.


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Licence to be Bad by Jonathan Aldred

"Friedman doctrine" OR "shareholder theory", Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, availability heuristic, Ayatollah Khomeini, behavioural economics, Benoit Mandelbrot, Berlin Wall, Black Monday: stock market crash in 1987, Black Swan, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Cass Sunstein, Charles Babbage, clean water, cognitive dissonance, corporate governance, correlation does not imply causation, cuban missile crisis, Daniel Kahneman / Amos Tversky, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dr. Strangelove, Edward Snowden, fake news, Fall of the Berlin Wall, falling living standards, feminist movement, framing effect, Frederick Winslow Taylor, From Mathematics to the Technologies of Life and Death, full employment, Gary Kildall, George Akerlof, glass ceiling, Glass-Steagall Act, Herman Kahn, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Jeff Bezos, John Nash: game theory, John von Neumann, Linda problem, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, meta-analysis, Mont Pelerin Society, mutually assured destruction, Myron Scholes, Nash equilibrium, Norbert Wiener, nudge unit, obamacare, offshore financial centre, Pareto efficiency, Paul Samuelson, plutocrats, positional goods, power law, precautionary principle, profit maximization, profit motive, race to the bottom, RAND corporation, rent-seeking, Richard Thaler, ride hailing / ride sharing, risk tolerance, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, scientific management, Skinner box, Skype, Social Responsibility of Business Is to Increase Its Profits, spectrum auction, The Nature of the Firm, The Wealth of Nations by Adam Smith, Tragedy of the Commons, transaction costs, trickle-down economics, Vilfredo Pareto, wealth creators, zero-sum game

Moggridge (Royal Economic Society), vol. 10, 173–4. 6 Letter to Morgenstern, 8 October 1947, explaining von Neumann’s refusal to review Paul Samuelson’s Foundations of Economic Analysis. Quoted in Morgenstern (1976), ‘The Collaboration between Oskar Morgenstern and John von Neumann on the Theory of Games’, Journal of Economic Literature, 14 (3), 810. 7 Morgenstern’s diary, April–May 1942. Quoted in Leonard, Robert J. (1995), ‘From Parlor Games to Social Science: Von Neumann, Morgenstern, and the Creation of Game Theory 1928–1944’, Journal of Economic Literature, 33 (2), 730. 8 Nasar, 94. 9 Ibid. 10 Quoted in Heims, S. (1980). John Von Neumann and Norbert Wiener: From Mathematics to the Technologies of Life and Death (Cambridge: MIT Press), 327. 11 Quoted in Poundstone, W. (1992), Prisoner’s Dilemma (New York: Anchor Books), 168. 12 Quoted in Ferguson, N. (2017), The Square and the Tower: Networks and Power, from the Freemasons to Facebook (London: Allen Lane), 260. 13 Hertzberg, H. (2001), ‘Comment: Tuesday, and After’, New Yorker, 24 September 2001, 27.

The intellectual framework for all this nuclear strategizing was game theory. It was the perfect tool for the RAND style of military thinking. Game theory assumes that humans are purely selfish and hyper-rational, in possession not only of all the information relevant to making decisions but of perfect and exhaustive powers of computation and logical reasoning. John von Neumann is usually seen as the father of game theory. Nash may have been a genius, but he was almost a mathematical minnow in comparison to von Neumann. DR STRANGELOVE AND THE KAISER’S GRANDSON The 1964 film Dr Strangelove satirized the Cold War with its tale of impending Armageddon triggered by a crazy US air force general launching a nuclear first strike on the USSR.

In 1956 President Eisenhower held regular secret meetings with a Hungarian mathematician confined to a wheelchair who would be taken back and forth by limousine to the White House from his bed at Walter Reed Hospital in Washington. The patient was under armed guard day and night because he would frequently descend into deranged babbling, so it was feared he might spill military secrets if an enemy agent could get to his bedside. The patient, in what was to be the last year of his life, was John von Neumann, undoubtedly one of the inspirations for Dr Strangelove. (At one point in the film, Strangelove refers to research by the ‘Bland Corporation’.) Before his tragic decline ‘Johnny’ von Neumann’s genius was so overwhelming that it is hard to summarize. He was a mathematical prodigy: at the age of eight, when given any two eight-digit numbers, he could divide one by the other in his head.


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How to Create a Mind: The Secret of Human Thought Revealed by Ray Kurzweil

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Albert Michelson, anesthesia awareness, anthropic principle, brain emulation, cellular automata, Charles Babbage, Claude Shannon: information theory, cloud computing, computer age, Computing Machinery and Intelligence, Dean Kamen, discovery of DNA, double helix, driverless car, en.wikipedia.org, epigenetics, George Gilder, Google Earth, Hans Moravec, Isaac Newton, iterative process, Jacquard loom, Jeff Hawkins, John von Neumann, Law of Accelerating Returns, linear programming, Loebner Prize, mandelbrot fractal, Nick Bostrom, Norbert Wiener, optical character recognition, PalmPilot, pattern recognition, Peter Thiel, Ralph Waldo Emerson, random walk, Ray Kurzweil, reversible computing, selective serotonin reuptake inhibitor (SSRI), self-driving car, speech recognition, Steven Pinker, strong AI, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Wall-E, Watson beat the top human players on Jeopardy!, X Prize

Chapter 8: The Mind as Computer 1. Salomon Bochner, A Biographical Memoir of John von Neumann (Washington, DC: National Academy of Sciences, 1958). 2. A. M. Turing, “On Computable Numbers, with an Application to the Entscheidungsproblem,” Proceedings of the London Mathematical Society Series 2, vol. 42 (1936–37): 230–65, http://www.comlab.ox.ac.uk/activities/ieg/e-library/sources/tp2-ie.pdf. A. M. Turing, “On Computable Numbers, with an Application to the Entscheidungsproblem: A Correction,” Proceedings of the London Mathematical Society 43 (1938): 544–46. 3. John von Neumann, “First Draft of a Report on the EDVAC,” Moore School of Electrical Engineering, University of Pennsylvania, June 30, 1945.

—Diane Ackerman Brains exist because the distribution of resources necessary for survival and the hazards that threaten survival vary in space and time. —John M. Allman The modern geography of the brain has a deliciously antiquated feel to it—rather like a medieval map with the known world encircled by terra incognita where monsters roam. —David Bainbridge In mathematics you don’t understand things. You just get used to them. —John von Neumann E ver since the emergence of the computer in the middle of the twentieth century, there has been ongoing debate not only about the ultimate extent of its abilities but about whether the human brain itself could be considered a form of computer. As far as the latter question was concerned, the consensus has veered from viewing these two kinds of information-processing entities as being essentially the same to their being fundamentally different.

The basic idea is that the human brain is likewise subject to natural law, and thus its information-processing ability cannot exceed that of a machine (and therefore of a Turing machine). We can properly credit Turing with establishing the theoretical foundation of computation with his 1936 paper, but it is important to note that he was deeply influenced by a lecture that Hungarian American mathematician John von Neumann (1903–1957) gave in Cambridge in 1935 on his stored program concept, a concept enshrined in the Turing machine.1 In turn, von Neumann was influenced by Turing’s 1936 paper, which elegantly laid out the principles of computation, and made it required reading for his colleagues in the late 1930s and early 1940s.2 In the same paper Turing reports another unexpected discovery: that of unsolvable problems.


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The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street by Justin Fox

"Friedman doctrine" OR "shareholder theory", Abraham Wald, activist fund / activist shareholder / activist investor, Alan Greenspan, Albert Einstein, Andrei Shleifer, AOL-Time Warner, asset allocation, asset-backed security, bank run, beat the dealer, behavioural economics, Benoit Mandelbrot, Big Tech, Black Monday: stock market crash in 1987, Black-Scholes formula, book value, Bretton Woods, Brownian motion, business cycle, buy and hold, capital asset pricing model, card file, Carl Icahn, Cass Sunstein, collateralized debt obligation, compensation consultant, complexity theory, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, democratizing finance, Dennis Tito, discovery of the americas, diversification, diversified portfolio, Dr. Strangelove, Edward Glaeser, Edward Thorp, endowment effect, equity risk premium, Eugene Fama: efficient market hypothesis, experimental economics, financial innovation, Financial Instability Hypothesis, fixed income, floating exchange rates, George Akerlof, Glass-Steagall Act, Henri Poincaré, Hyman Minsky, implied volatility, impulse control, index arbitrage, index card, index fund, information asymmetry, invisible hand, Isaac Newton, John Bogle, John Meriwether, John Nash: game theory, John von Neumann, joint-stock company, Joseph Schumpeter, junk bonds, Kenneth Arrow, libertarian paternalism, linear programming, Long Term Capital Management, Louis Bachelier, low interest rates, mandelbrot fractal, market bubble, market design, Michael Milken, Myron Scholes, New Journalism, Nikolai Kondratiev, Paul Lévy, Paul Samuelson, pension reform, performance metric, Ponzi scheme, power law, prediction markets, proprietary trading, prudent man rule, pushing on a string, quantitative trading / quantitative finance, Ralph Nader, RAND corporation, random walk, Richard Thaler, risk/return, road to serfdom, Robert Bork, Robert Shiller, rolodex, Ronald Reagan, seminal paper, shareholder value, Sharpe ratio, short selling, side project, Silicon Valley, Skinner box, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, statistical model, stocks for the long run, tech worker, The Chicago School, The Myth of the Rational Market, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, Thorstein Veblen, Tobin tax, transaction costs, tulip mania, Two Sigma, Tyler Cowen, value at risk, Vanguard fund, Vilfredo Pareto, volatility smile, Yogi Berra

The developments of the late 1930s, in which young Keynesians grafted a few kludgy imperfect-foresight formulas onto the body of perfect-foresight mathematical economics, aggravated him. He began consorting with the scientists and mathematicians of Vienna, one of whom steered him toward a 1928 paper about poker written by Hungarian mathematician John von Neumann.4 After emigrating to the United States in 1930, von Neumann became the brightest intellectual light at Princeton’s Institute for Advanced Study, a place that also employed Albert Einstein. He helped plan the Battle of the Atlantic, design the atomic bomb, and invent the computer. In the late 1950s, dying of bone cancer likely brought on by witnessing one too many atomic test blasts, he peddled his doctrine of nuclear brinksmanship while rolling his wheelchair down the halls of power in Washington—providing at least part of the inspiration for Stanley Kubrick’s Dr.

At the University of Chicago, he found an enthusiastic follower in Eugene Fama, another student of Harry Roberts studying market movements. Holbrook Working rejoined the fray with a paper showing that Alfred Cowles’s 1937 finding of patterns in stock movements was largely the result of a statistical error.12 Oskar Morgenstern chipped in, too. His friend John von Neumann had suggested before he died in 1957 that Morgenstern use a statistical technique called spectral analysis, helpful in distinguishing between true cycles and randomly generated ones, to examine economic data. Morgenstern wasn’t enough of a mathematician to do this himself, but he hired young British statistician Clive Granger and put him to work examining stock prices.

Even before that happened, scholars on multiple campuses were making it clear that, in theory, it would be awfully convenient if speculative markets functioned perfectly. CHAPTER 5 MODIGLIANI AND MILLER ARRIVE AT A SIMPLIFYING ASSUMPTION Finance, the business school version of economics, is transformed from a field of empirical research and rules of thumb to one ruled by theory. FOUR YEARS AFTER JOHN VON Neumann and Oskar Morgenstern published their equation-filled guide to weighing potential rewards and losses in an uncertain future, economist Milton Friedman and statistician Jimmie Savage made a startling proposal. With just a few tweaks, they wrote, the von Neumann-Morgenstern utility theory could describe the way real people made economic decisions.


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The Computer Boys Take Over: Computers, Programmers, and the Politics of Technical Expertise by Nathan L. Ensmenger

barriers to entry, business process, Charles Babbage, Claude Shannon: information theory, computer age, deskilling, Donald Knuth, Firefox, Frederick Winslow Taylor, functional programming, future of work, Grace Hopper, informal economy, information retrieval, interchangeable parts, Isaac Newton, Jacquard loom, job satisfaction, John von Neumann, knowledge worker, Larry Ellison, loose coupling, machine readable, new economy, no silver bullet, Norbert Wiener, pattern recognition, performance metric, Philip Mirowski, post-industrial society, Productivity paradox, RAND corporation, Robert Gordon, scientific management, Shoshana Zuboff, sorting algorithm, Steve Jobs, Steven Levy, systems thinking, tacit knowledge, technological determinism, the market place, The Theory of the Leisure Class by Thorstein Veblen, Thomas Kuhn: the structure of scientific revolutions, Thorstein Veblen, Turing machine, Von Neumann architecture, world market for maybe five computers, Y2K

The Computer Boys Take Over History of Computing William Aspray, editor The Government Machine: A Revolutionary History of the Computer William Aspray John von Neumann and the Origins of Modern Computing William Aspray and Paul E. Ceruzzi, editors The Internet and American Business Charles J. Bashe, Lyle R. Johnson, John H. Palmer, and Emerson W. Pugh IBM’s Early Computers Martin Campbell-Kelly From Airline Reservations to Sonic the Hedgehog: A History of the Software Industry Paul E. Ceruzzi A History of Modern Computing I. Bernard Cohen Howard Aiken: Portrait of a Computer Pioneer I.

The ENIAC women would simply set up the machine to perform these predetermined plans; that this work would turn out to be difficult and require radically innovative thinking was completely unanticipated.32 The telephone switchboardlike appearance of the ENIAC programming cable-and-plug panels reinforced the notion that programmers were mere machine operators, that programming was more handicraft than science, more feminine than masculine, more mechanical than intellectual. The idea that the development of hardware was the real business of computing, and that software was at best secondary, persisted throughout the 1940s and early 1950s. In the first textbooks on computing published in the United States, for example, John von Neumann and Herman Goldstine outlined a clear division of labor in computing—presumably based on their experience with the ENIAC project—that clearly distinguished between the headwork of the (male) scientist or “planner,” and the handwork of the (largely female) “coder.” In the von Neumann and Goldstine schema, the planner did the intellectual work of analysis and the coder simply translated this work into a form that a computer could understand.

Conventional histories of computer programming tend to conflate programming as a vocational activity with computer science as an academic discipline. In many of these accounts, programming is represented as a subdiscipline of formal logic and mathematics, and its origins are identified in the writings of early computer theorists Alan Turing and John von Neumann. The development of the discipline is evaluated in terms of advances in programming languages, formal methods, and generally applicable theoretical research. This purely intellectual approach to the history of programming, however, conceals the essentially craftlike nature of early programming practice.


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From Counterculture to Cyberculture: Stewart Brand, the Whole Earth Network, and the Rise of Digital Utopianism by Fred Turner

"World Economic Forum" Davos, 1960s counterculture, A Declaration of the Independence of Cyberspace, Alan Greenspan, Alvin Toffler, Apple's 1984 Super Bowl advert, back-to-the-land, Bill Atkinson, bioinformatics, Biosphere 2, book value, Buckminster Fuller, business cycle, Californian Ideology, classic study, Claude Shannon: information theory, complexity theory, computer age, Computer Lib, conceptual framework, Danny Hillis, dematerialisation, distributed generation, Douglas Engelbart, Douglas Engelbart, Dr. Strangelove, Dynabook, Electric Kool-Aid Acid Test, Fairchild Semiconductor, Ford Model T, From Mathematics to the Technologies of Life and Death, future of work, Future Shock, game design, George Gilder, global village, Golden Gate Park, Hacker Conference 1984, Hacker Ethic, Haight Ashbury, Herbert Marcuse, Herman Kahn, hive mind, Howard Rheingold, informal economy, intentional community, invisible hand, Ivan Sutherland, Jaron Lanier, John Gilmore, John Markoff, John Perry Barlow, John von Neumann, Kevin Kelly, knowledge economy, knowledge worker, Lewis Mumford, market bubble, Marshall McLuhan, mass immigration, means of production, Menlo Park, military-industrial complex, Mitch Kapor, Mondo 2000, Mother of all demos, new economy, Norbert Wiener, peer-to-peer, post-industrial society, postindustrial economy, Productivity paradox, QWERTY keyboard, Ralph Waldo Emerson, RAND corporation, reality distortion field, Richard Stallman, Robert Shiller, Ronald Reagan, Shoshana Zuboff, Silicon Valley, Silicon Valley ideology, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, systems thinking, technoutopianism, Ted Nelson, Telecommunications Act of 1996, The Hackers Conference, the strength of weak ties, theory of mind, urban renewal, Vannevar Bush, We are as Gods, Whole Earth Catalog, Whole Earth Review, Yom Kippur War

On the laboratory floor, this led to an egalitarian ethic of collaboration and a “hybrid of practices” in Galison’s terms, known as “Radar Philosophy” (152). 28. As several historians have pointed out, the “systems” approach taken by cybernetics predated the invention of the term itself by a little more than a decade. In 1928, for instance, John Von Neumann published his “Theory of Parlor Games,” thus inventing game theory. Heims, John Von Neumann and Norbert Wiener, 84. In the 1930s in England, Robert Lilienfeld has argued, the invention of radar led to the need for the coordination of machines and thus the invention of the “total point of view” characteristic of systems thinking. Lilienfeld, Rise of Systems Theory, 103.

As in its profile of the Electronic Frontier Foundation, Wired had offered the freelance lifestyle of a high-profile consultant as a model of the independent lifestyle ostensibly becoming available to the digital generation as a whole. A month after Kelly’s first interview with Gilder appeared in Wired, Paulina Borsook published a similar profile of Dyson. The story moved swiftly through Dyson’s biography— child of physicist Freeman Dyson, childhood friend of Alice Bigelow (daughter of Julian Bigelow, John Von Neumann’s engineer), former Forbes reporter and Wall Street stock analyst, later editor of the newsletter Release 1.0 and hostess of the annual PC Forum conference. When it came to Dyson’s present career, however, the story slipped into information-system metaphors like those that appeared in Bronson’s profile of Gilder.

Cybernetics emerged as a self-consciously comprehensive field of thought, however, with the work of Norbert Wiener. For a fuller account of Wiener’s career and the emergence of his cybernetics, see also Galison, “Ontology of the Enemy”; and Hayles, How We Became Posthuman. 29. Wiener, Cybernetics, 8. 30. Ibid., 9. 31. Heims, John Von Neumann and Norbert Wiener, 182 – 88. For a chronicle of Wiener’s shifting relationship to the Rad Lab, see Conway and Siegelman, Dark Hero of the Information Age, 115 –25. 32. Wiener, I Am a Mathematician, 251–52. N o t e s t o Pa g e s 2 1 _ 2 6 [ 265 ] 33. For a critical analysis of this choice, and especially its relationship to conceptions of the Other in contemporary cultural theory, see Galison, “Ontology of the Enemy.” 34.


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New Dark Age: Technology and the End of the Future by James Bridle

AI winter, Airbnb, Alfred Russel Wallace, AlphaGo, Anthropocene, Automated Insights, autonomous vehicles, back-to-the-land, Benoit Mandelbrot, Bernie Sanders, bitcoin, Boeing 747, British Empire, Brownian motion, Buckminster Fuller, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, coastline paradox / Richardson effect, cognitive bias, cognitive dissonance, combinatorial explosion, computer vision, congestion charging, cryptocurrency, data is the new oil, disinformation, Donald Trump, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dr. Strangelove, drone strike, Edward Snowden, Eyjafjallajökull, Fairchild Semiconductor, fake news, fear of failure, Flash crash, fulfillment center, Google Earth, Greyball, Haber-Bosch Process, Higgs boson, hive mind, income inequality, informal economy, Internet of things, Isaac Newton, ITER tokamak, James Bridle, John von Neumann, Julian Assange, Kickstarter, Kim Stanley Robinson, Large Hadron Collider, late capitalism, Laura Poitras, Leo Hollis, lone genius, machine translation, mandelbrot fractal, meta-analysis, Minecraft, mutually assured destruction, natural language processing, Network effects, oil shock, p-value, pattern recognition, peak oil, recommendation engine, road to serfdom, Robert Mercer, Ronald Reagan, security theater, self-driving car, Seymour Hersh, Silicon Valley, Silicon Valley ideology, Skype, social graph, sorting algorithm, South China Sea, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stem cell, Stuxnet, technoutopianism, the built environment, the scientific method, Uber for X, undersea cable, University of East Anglia, uranium enrichment, Vannevar Bush, warehouse robotics, WikiLeaks

He may perish in conflict before he learns to wield that record for his true good. Yet, in the application of science to the needs and desires of man, it would seem to be a singularly unfortunate stage at which to terminate the process, or to lose hope as to the outcome.12 One of Bush’s colleagues at the Manhattan Project was another scientist, John von Neumann, who shared similar concerns about the overwhelming volumes of information being produced – and required – by the scientific endeavours of the day. He was also captivated by the idea of predicting, and even controlling, the weather. In 1945, he came across a mimeograph entitled ‘Outline of Weather Proposal’, written by a researcher at RCA Laboratories named Vladimir Zworykin.

It consumed 140 kilowatts of power, and pumped out so much heat that special ceiling fans had to be installed. To reprogram it, it was necessary to turn hundreds of ten-pole rotary switches by hand, the operators moving between the stacks of equipment, connecting cables and checking hundreds of thousands of hand-soldered joints. Among the operators was Klára Dán von Neumann, John von Neumann’s wife, who wrote most of the meteorological code and checked the work of the others. In 1950, a team of meteorologists assembled at Aberdeen in order to perform the first automated twenty-four-hour weather forecast, along exactly the same lines as Richardson had proposed. For this project, the boundaries of the world were the edges of the continental United States; a grid separated it into fifteen rows and eighteen columns.

The ENIAC was actually one that you kind of lived inside.’18 But in fact, today, we all live inside a version of the ENIAC: a vast machinery of computation that encircles the entirety of the globe and extends into outer space on a network of satellites. It is this machine, imagined by Lewis Fry Richardson and actualised by John von Neumann, that governs in one way or another every aspect of life today. And it is one of the most striking conditions of this computational regime that it has rendered itself almost invisible to us. It is almost possible to pinpoint the exact moment when militarised computation, and the belief in prediction and control that it embodies and produces, slid out of view.


pages: 338 words: 104,815

Nobody's Fool: Why We Get Taken in and What We Can Do About It by Daniel Simons, Christopher Chabris

Abraham Wald, Airbnb, artificial general intelligence, Bernie Madoff, bitcoin, Bitcoin "FTX", blockchain, Boston Dynamics, butterfly effect, call centre, Carmen Reinhart, Cass Sunstein, ChatGPT, Checklist Manifesto, choice architecture, computer vision, contact tracing, coronavirus, COVID-19, cryptocurrency, DALL-E, data science, disinformation, Donald Trump, Elon Musk, en.wikipedia.org, fake news, false flag, financial thriller, forensic accounting, framing effect, George Akerlof, global pandemic, index fund, information asymmetry, information security, Internet Archive, Jeffrey Epstein, Jim Simons, John von Neumann, Keith Raniere, Kenneth Rogoff, London Whale, lone genius, longitudinal study, loss aversion, Mark Zuckerberg, meta-analysis, moral panic, multilevel marketing, Nelson Mandela, pattern recognition, Pershing Square Capital Management, pets.com, placebo effect, Ponzi scheme, power law, publication bias, randomized controlled trial, replication crisis, risk tolerance, Robert Shiller, Ronald Reagan, Rubik’s Cube, Sam Bankman-Fried, Satoshi Nakamoto, Saturday Night Live, Sharpe ratio, short selling, side hustle, Silicon Valley, Silicon Valley startup, Skype, smart transportation, sovereign wealth fund, statistical model, stem cell, Steve Jobs, sunk-cost fallacy, survivorship bias, systematic bias, TED Talk, transcontinental railway, WikiLeaks, Y2K

Goichberg knew that anyone capable of drawing a grandmaster and beating a master could solve the chess problem in one second. But when asked to prove himself, von Neumann refused to even try. He left the playing area in a huff and never received a prize or a refund. Indeed, he never entered another rated chess tournament—at least not under the name of John von Neumann—and neither he nor his accomplice has been seen in the chess world again. The case of John von Neumann remains one of the great unsolved mysteries of chess.4 Since 1993, there have been many similar incidents of computer-assisted cheating, a form of “intellectual doping,” in chess tournaments. Now that the processing power of a smartphone is sufficient to outplay the human world champion, it has become easier than ever to gain an unfair advantage.

But no one was expecting what happened in 1993.1 It began with a minor sensation. In the second round, when the top seeds are normally still mowing down weaker opponents on their way to eventually playing against one another, grandmaster Helgi Ólafsson of Iceland was held to a draw. His opponent, a player from California named John von Neumann, was unrated and playing in his first official tournament—or so he said when he registered for the event and joined the US Chess Federation.2 It wasn’t unheard of for players to make the World Open their first US tournament. The large prize fund attracted many players from the former Soviet Union who had not stood out in their home country, where chess was practically a national sport, but who were good enough to compete for prizes in the United States.

For the entire game, lazzir had never made a move in fewer than five seconds or more than twelve seconds. Chris, on the other hand, made his opening moves in just one or two seconds each but took over thirty seconds on several moves and almost two full minutes on one of them. Recall that odd timing between moves was one of the tells that revealed John von Neumann’s chess cheating. Master-level players often rely on memory for the initial moves in a game, which tend to follow well-established plans. Later parts of the game require more thought and decision-making, and at some point, taking extra time to find the best move—or at least avoid a losing one—can be critical.


pages: 339 words: 92,785

I, Warbot: The Dawn of Artificially Intelligent Conflict by Kenneth Payne

Abraham Maslow, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, AlphaGo, anti-communist, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, Asperger Syndrome, augmented reality, Automated Insights, autonomous vehicles, backpropagation, Black Lives Matter, Bletchley Park, Boston Dynamics, classic study, combinatorial explosion, computer age, computer vision, Computing Machinery and Intelligence, coronavirus, COVID-19, CRISPR, cuban missile crisis, data science, deep learning, deepfake, DeepMind, delayed gratification, Demis Hassabis, disinformation, driverless car, drone strike, dual-use technology, Elon Musk, functional programming, Geoffrey Hinton, Google X / Alphabet X, Internet of things, job automation, John Nash: game theory, John von Neumann, Kickstarter, language acquisition, loss aversion, machine translation, military-industrial complex, move 37, mutually assured destruction, Nash equilibrium, natural language processing, Nick Bostrom, Norbert Wiener, nuclear taboo, nuclear winter, OpenAI, paperclip maximiser, pattern recognition, RAND corporation, ransomware, risk tolerance, Ronald Reagan, self-driving car, semantic web, side project, Silicon Valley, South China Sea, speech recognition, Stanislav Petrov, stem cell, Stephen Hawking, Steve Jobs, strong AI, Stuxnet, technological determinism, TED Talk, theory of mind, TikTok, Turing machine, Turing test, uranium enrichment, urban sprawl, V2 rocket, Von Neumann architecture, Wall-E, zero-sum game

He demonstrated that logical propositions, like AND/OR and IF/THEN, and binary numbers could be implemented by switches in a telephone circuit.13 Switches, binary code and Boolean logic soon became part of the basic architecture of modern digital computing. Another significant figure early in the history of computing was the charismatic American, John von Neumann.14 His contribution is rather less clear-cut; others can also lay claim to what has become known as the von Neumann architecture for modern computers. By this stage, spurred by the war and the problems of fire control, communications and code-breaking, computing was a large and rapidly expanding field.

The long-lived Schelling wrote his classic works on strategy in the 1950s and 60s, an era when nuclear weapons were a new and terrifying weapon.21 And also an era when computers and quantitative thinking seemed to offer a new, more rigorous approach to thinking about all manner of social questions, including nuclear war. One exciting branch of maths was ‘game theory’, which considered the way in which rational agents interacted. Pioneered by the brilliant John von Neumann, co-inventor of the modern computer, game theory looked like a good way of modelling the sorts of adversarial behaviours that took place in international relations. It was enthusiastically embraced by a group of quantitative theorists then growing in prominence, some of whom worked for the US Air Force’s inhouse thinktank, the RAND Corporation.22 Schelling himself was a mathematically trained economist, and so was well placed to take advantage of the new technique.

‘Solving’ real strategy problems will require much more than solving poker. In the real world, decisions are altogether more complex than card games, whatever Clausewitz wrote. Something else is needed—but what? THE ART OF i-WAR Libratus, the poker playing AI, isn’t a genius. The geniuses are the mathematicians who built it—John von Neumann, originator of both the computer and game theory; John Nash, discoverer of the optimum strategy for two-player games; and the Libratus team at Carnegie Mellon University, who harnessed some abstract maths to a powerful deep learning architecture. To see the difference and appreciate why it will be difficult to find a genius warbot general, we need to think about creativity in humans and machines.


pages: 245 words: 12,162

In Pursuit of the Traveling Salesman: Mathematics at the Limits of Computation by William J. Cook

Bletchley Park, complexity theory, computer age, Computer Numeric Control, financial engineering, four colour theorem, index card, John von Neumann, linear programming, NP-complete, P = NP, p-value, RAND corporation, Richard Feynman, traveling salesman, Turing machine

Nonetheless, plots such as the one displayed in figure 2.21 strongly suggest a steady decrease √ in the average tour length divided by n as n increases, pointing toward an ultimate value of approximately 0.712 for b.29 43 3: The Salesman in Action Because my mathematics has its origin in a real problem doesn’t make it less interesting to me—just the other way around. —George Dantzig, 1986.1 he name itself announces the applied nature of the traveling salesman problem. This has surely contributed to a focus on computational issues, keeping the research topic well away from perils famously described in John von Neumann’s essay “The Mathematician”. “In other words, at a great distance from its empirical source, or after much ‘abstract’ inbreeding, a mathematical subject is in danger of degeneration”. Indeed, a strength of TSP research is the steady stream of practical applications that breathe new life into the area.

Naturally I agreed. von Neumann said: “The speaker titled his talk ‘linear programming’ and carefully stated his axioms. If you have an application that satisfies the axioms, well use it. If it does not, then don’t.” Fortunately for the world, many of its complexities can in fact be described in sufficient detail by linear models. The episode with Dantzig, Hotelling, and John von Neumann is summed up nicely by a cartoon Dantzig’s Stanford colleagues reported as hanging outside his office.9 It featured the Peanuts character Linus in his traditional pose, sucking his thumb and Linear Programming holding a blanket. The caption read, “Happiness is assuming the world is linear.”

It is remarkable that there always exists such a simple and elegant proof of optimality: the simplex algorithm constructs multipliers that can be used to combine the primal LP constraints into a convincing statement that no solution gives an objective value greater than that supplied by the final dictionary. Moreover, the multipliers are themselves an optimal solution to the dual LP problem and the optimal primal and dual objective values 107 108 Chapter 5 are equal. This beautiful result is known as the strong duality theorem, first stated and proved by John von Neumann.22 Strong duality gets top billing in LP theory, but in our TSP discussion we really only need the much easier statement that any dual LP solution provides a bound on the primal objective; this is called the weak duality theorem. And don’t worry if you missed a few details in our rush through material in the past few pages: in the special case of the TSP we provide an intuitive explanation of duality, showing how to trap the salesman with linear inequalities.


pages: 229 words: 67,599

The Logician and the Engineer: How George Boole and Claude Shannon Created the Information Age by Paul J. Nahin

air gap, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Charles Babbage, Claude Shannon: information theory, Computing Machinery and Intelligence, conceptual framework, Edward Thorp, Fellow of the Royal Society, finite state, four colour theorem, Georg Cantor, Grace Hopper, Isaac Newton, John von Neumann, knapsack problem, New Journalism, Pierre-Simon Laplace, reversible computing, Richard Feynman, Schrödinger's Cat, Steve Jobs, Steve Wozniak, thinkpad, Thomas Bayes, Turing machine, Turing test, V2 rocket

With his PhD in hand, and after spending the summer of 1940 back at Bell Labs, Shannon used a National Research Council Fellowship for a year’s stay at the Institute for Advanced Study in Princeton, New Jersey, where he worked under the great mathematician Hermann Weyl. Also there were such luminaries as John von Neumann and Albert Einstein. He might even have bumped into Richard Feynman, who was working on his PhD in physics at Princeton. Also there with Shannon was his first wife, Norma Levor (born 1920), whom he had married in 1939. Theirs was an intense, passionate, but ultimately doomed brief marriage, and Norma left him in June 1941.

So, the answer is that the additional relay E does not result in improved reliability.8 6.5 MAJORITY LOGIC In this final section I’ll comment just a bit on what sparked Shannon’s interest in building more reliable circuits out of less reliable components. In 1956 Shannon was coeditor of an anthology of technical papers, one of which was authored by the great Hungarian-born American mathematician John von Neumann (1903–1957). Titled “Probabilistic Logics and the Synthesis of Reliable Organisms from Unreliable Components,” Shannon read that paper as an editor long before the anthology appeared, and in his 1956 “crummy relay” paper specifically cited von Neumann’s earlier work.9 Von Neumann’s paper is heavily oriented toward mimicking the fundamental component of the human brain, the neuron cell that “fires” (that is, produces an output) when its multiple inputs (the outputs of other neurons) satisfy certain requirements.

An implicit recognition of this can be found as long ago as 1929, in an important thermodynamics paper by the Hungarian physicist Leo Szilard (1898–1964).7 The explicit tying together of information, energy, and computation in analysts’ minds is, however, almost certainly due to a remark made by the Institute for Advanced Study mathematician John von Neumann (1903–1957) in a December 1949 lecture at the University of Illinois.8 In that lecture he asserted that the minimum energy Emin associated with manipulating a bit to be kT ln(2) joules (J), where T is the temperature on the Kelvin scale and k is Boltzmann’s constant (k = 1.38. 10−23).9 (Power is energy per unit time and so, just to keep the scale of this in mind, 1 = 1 = 1 watt) At “room temperature,” that is, at T = 300 K, this minimum energy is 2.87 · 10−21 J, a very tiny amount of energy.


pages: 523 words: 143,139

Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian, Tom Griffiths

4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, algorithmic bias, algorithmic trading, anthropic principle, asset allocation, autonomous vehicles, Bayesian statistics, behavioural economics, Berlin Wall, Big Tech, Bill Duvall, bitcoin, Boeing 747, Charles Babbage, cognitive load, Community Supported Agriculture, complexity theory, constrained optimization, cosmological principle, cryptocurrency, Danny Hillis, data science, David Heinemeier Hansson, David Sedaris, delayed gratification, dematerialisation, diversification, Donald Knuth, Donald Shoup, double helix, Dutch auction, Elon Musk, exponential backoff, fault tolerance, Fellow of the Royal Society, Firefox, first-price auction, Flash crash, Frederick Winslow Taylor, fulfillment center, Garrett Hardin, Geoffrey Hinton, George Akerlof, global supply chain, Google Chrome, heat death of the universe, Henri Poincaré, information retrieval, Internet Archive, Jeff Bezos, Johannes Kepler, John Nash: game theory, John von Neumann, Kickstarter, knapsack problem, Lao Tzu, Leonard Kleinrock, level 1 cache, linear programming, martingale, multi-armed bandit, Nash equilibrium, natural language processing, NP-complete, P = NP, packet switching, Pierre-Simon Laplace, power law, prediction markets, race to the bottom, RAND corporation, RFC: Request For Comment, Robert X Cringely, Sam Altman, scientific management, sealed-bid auction, second-price auction, self-driving car, Silicon Valley, Skype, sorting algorithm, spectrum auction, Stanford marshmallow experiment, Steve Jobs, stochastic process, Thomas Bayes, Thomas Malthus, Tragedy of the Commons, traveling salesman, Turing machine, urban planning, Vickrey auction, Vilfredo Pareto, Walter Mischel, Y Combinator, zero-sum game

As long as the two stacks were themselves sorted, the procedure of merging them into a single sorted stack was incredibly straightforward and took linear time: simply compare the two top cards to each other, move the smaller of them to the new stack you’re creating, and repeat until finished. The program that John von Neumann wrote in 1945 to demonstrate the power of the stored-program computer took the idea of collating to its beautiful and ultimate conclusion. Sorting two cards is simple: just put the smaller one on top. And given a pair of two-card stacks, both of them sorted, you can easily collate them into an ordered stack of four.

The computer industry is currently in transition from hard disk drives to solid-state drives; at the same price point, a hard disk will offer dramatically greater capacity, but a solid-state drive will offer dramatically better performance—as most consumers now know, or soon discover when they begin to shop. What casual consumers may not know is that this exact tradeoff is being made within the machine itself at a number of scales—to the point where it’s considered one of the fundamental principles of computing. In 1946, Arthur Burks, Herman Goldstine, and John von Neumann, working at the Institute for Advanced Study in Princeton, laid out a design proposal for what they called an electrical “memory organ.” In an ideal world, they wrote, the machine would of course have limitless quantities of lightning-fast storage, but in practice this wasn’t possible. (It still isn’t.)

Exactly calculating the chances of some particular outcome of that process, with many, many particles interacting, is hard to the point of impossibility. But simulating it, with each interaction being like turning over a new card, provides an alternative. Ulam developed the idea further with John von Neumann, and worked with Nicholas Metropolis, another of the physicists from the Manhattan Project, on implementing the method on the Los Alamos computer. Metropolis named this approach—replacing exhaustive probability calculations with sample simulations—the Monte Carlo Method, after the Monte Carlo casino in Monaco, a place equally dependent on the vagaries of chance.


pages: 436 words: 127,642

When Einstein Walked With Gödel: Excursions to the Edge of Thought by Jim Holt

Ada Lovelace, Albert Einstein, Andrew Wiles, anthropic principle, anti-communist, Arthur Eddington, Benoit Mandelbrot, Bletchley Park, Brownian motion, cellular automata, Charles Babbage, classic study, computer age, CRISPR, dark matter, David Brooks, Donald Trump, Dr. Strangelove, Eddington experiment, Edmond Halley, everywhere but in the productivity statistics, Fellow of the Royal Society, four colour theorem, Georg Cantor, George Santayana, Gregor Mendel, haute couture, heat death of the universe, Henri Poincaré, Higgs boson, inventory management, Isaac Newton, Jacquard loom, Johannes Kepler, John von Neumann, Joseph-Marie Jacquard, Large Hadron Collider, Long Term Capital Management, Louis Bachelier, luminiferous ether, Mahatma Gandhi, mandelbrot fractal, Monty Hall problem, Murray Gell-Mann, new economy, Nicholas Carr, Norbert Wiener, Norman Macrae, Paradox of Choice, Paul Erdős, Peter Singer: altruism, Plato's cave, power law, probability theory / Blaise Pascal / Pierre de Fermat, quantum entanglement, random walk, Richard Feynman, Robert Solow, Schrödinger's Cat, scientific worldview, Search for Extraterrestrial Intelligence, selection bias, Skype, stakhanovite, Stephen Hawking, Steven Pinker, Thorstein Veblen, Turing complete, Turing machine, Turing test, union organizing, Vilfredo Pareto, Von Neumann architecture, wage slave

Having launched himself with his offbeat thesis as a “solo scientist,” Mandelbrot sought out other similarly innovative mathematicians. One such was Norbert Wiener, the founder (and coiner) of “cybernetics,” the science of how systems ranging from telephone switchboards to the human brain are controlled by feedback loops. Another was John von Neumann, the creator of game theory (and much else). To Mandelbrot, these two men were “made of stardust.” He served as postdoc to both: first to Wiener at MIT, and then to von Neumann at the Institute for Advanced Study in Princeton, where he had a nightmarish experience. Delivering a lecture on the deep links between physics and linguistics, he watched as one after another of the famous figures in the audience nodded off and snored.

At Princeton, Turing took the first steps toward building a working model of his imaginary computer, pondering how to realize its logical design in a network of relay-operated switches; he even managed to get into a machine shop in the physics department and construct some of the relays himself. In addition to his studies with Church, he had dealings with the formidable John von Neumann, who would later be credited with innovations in computer architecture that Turing himself had pioneered. On the social side, he found the straightforward manners of Americans congenial, with certain exceptions: “Whenever you thank them for anything, they say ‘You’re welcome.’ I rather liked it at first, thinking I was welcome, but now I find it comes back like a ball thrown against a wall, and become positively apprehensive.

A marine biologist on the scene recalled that a week after the H-bomb test he was still finding terns with their feathers blackened and scorched and fish whose “skin was missing from a side as if they had been dropped in a hot pan.” The computer, one might well conclude, was conceived in sin. Its birth helped ratchet up, by several orders of magnitude, the destructive force available to the superpowers during the cold war. And the man most responsible for the creation of that first computer, John von Neumann, was himself among the most ardent of the cold warriors, an advocate of a preemptive military attack on the Soviet Union, and one of the models for the film character Dr. Strangelove. “The digital universe and the hydrogen bomb were brought into existence at the same time,” the historian of science George Dyson has observed.


Gaming the Vote: Why Elections Aren't Fair (And What We Can Do About It) by William Poundstone

affirmative action, Albert Einstein, book value, business cycle, Debian, democratizing finance, desegregation, Donald Trump, en.wikipedia.org, Everything should be made as simple as possible, global village, guest worker program, guns versus butter model, hiring and firing, illegal immigration, invisible hand, jimmy wales, John Nash: game theory, John von Neumann, Kenneth Arrow, manufacturing employment, Nash equilibrium, Paul Samuelson, Pierre-Simon Laplace, prisoner's dilemma, Ralph Nader, RAND corporation, Ronald Reagan, Silicon Valley, slashdot, the map is not the territory, Thomas Bayes, Tragedy of the Commons, transcontinental railway, Unsafe at Any Speed, Y2K

Despite the smiling faces, presidenti,,1 comenders Teddy Roosevelt, Woodrow lNilson, and William Howard Taft well kne'F that electionl can be lmfair when there are three Or more candidates. (U.S. Senate Collection. Center for Legislative Archives) To Scott Contents Prologue: The Wizard and the Lizard 3 THE PROBLEM 25 I. Game Theory Kurt Code! • Adolf Hitler· Albert Einstein· Oskar Morgenstern· Bambi· the u.s. Constitution· Joseph Goebbels • God· Kaiser Wilhelm II • John von Neumann" Kenneth Arrow" J\'larxism • Alfred Tarski • intransitivity· Harold Hotelling· ice cream· John Hicks· "Scissors, Paper. Stone" • Duncan Black· the "forty-seven-year-old wife of a machinist liVing in Dayton. Ohio" • the RAND Corporation· Condoleezzrl Rice· Olaf Helmer· Harry Truman· Joseph Stalin· Abram Bergson 2.

Had the muse of genius allotted Morgenstern a steadier flow of great ideas, he might have lacked the time to play this role. A man who cared more about being liked could not have deployed sharp elbows as effectively as he did. The most impressive of Morgenstern's projects was game theory, the creation mainly of Hungarian-born mathematician John von Neumann. Despite the name, game theory is not primarily about games such as chess or Monopoly or Halo. It is more an exact science of strategy. It explores how rational adversaries make decisions, knowing that their opponents are trying to second-guess or double-cross them. In 1928 von Neumann published the paper inaugurating this field.

, and Einstein, Morgenstern was emphatically not on their level. 32 Game Theory He would sometimes sit in on mathematical seminars and ask questions that appeared to confirm this assessment. Shubik tells of an excruciating lecture in which Morgenstern spent three hours trying and failing to reproduce a result from "his" game theory book. "We would have all been happier," Shubik said, "if Oskar had not attempted to go through formal proofs." John von Neumann had his talking point down pat. a. Johnny, what did Morgenstern really contribute? Come on. You can tell. A. "Without Oskar, I would have never written the Theory of Games and Economic BehmJior." No politician could have handled the question better. I met Kenneth Arrow on a sunny afternoon at the Stanford Faculty Club.


Blindside: How to Anticipate Forcing Events and Wild Cards in Global Politics by Francis Fukuyama

Asian financial crisis, banking crisis, Berlin Wall, Bletchley Park, Bretton Woods, British Empire, business cycle, capital controls, Carmen Reinhart, cognitive bias, contact tracing, cuban missile crisis, currency risk, energy security, Fairchild Semiconductor, flex fuel, global pandemic, Herman Kahn, income per capita, informal economy, Intergovernmental Panel on Climate Change (IPCC), invisible hand, John von Neumann, low interest rates, mass immigration, Menlo Park, Mikhail Gorbachev, moral hazard, Norbert Wiener, oil rush, oil shale / tar sands, oil shock, packet switching, RAND corporation, Ray Kurzweil, reserve currency, Ronald Reagan, The Wisdom of Crowds, trade route, Vannevar Bush, Vernor Vinge, Yom Kippur War

., “The ENIAC,” A History of Computing in the Twentieth Century, edited by Metropolis, Howlett, and Rota, p. 525; and John W. Mauchly, “The ENIAC,” A History of Computing in the Twentieth Century, edited by Metropolis, Howlett, and Rota, p. 541. 7. William Aspray, John von Neumann and the Origins of Modern Computing (MIT Press, 1990); William Aspray, “John von Neumann’s Contributions to Computing and Computer Science,” Annals of the History of Computing 11, no. 3: 189–95 (1989). 8. Paul E. Ceruzzi, A History of Modern Computing (MIT Press, 1998), chap. 7; Martin Campbell-Kelly and William Aspray, Computer: A History of the Information Machine (New York: Basic Books, 1996), chap. 10. 9.

The war, of course, created any number of desperate demands for computation, which in turn led to two of the most famous of the pioneering computers: the digital, all-electronic Colossus, which was actually a series of machines created at the British code-breaking center, Bletchley Park, as a tool for cracking the most difficult German ciphers;5 and the digital, all-electronic ENIAC, which was constructed by engineers at the University of Pennsylvania to calculate artillery trajectories.6 Starting in mid-1944, moreover, the ENIAC team was joined by the world-renowned, Hungarian-born mathematician John von Neumann, who was also a participant in the super-secret Manhattan Project—and who was looking for computing machines that could help out with the horrendous calculations needed in that effort. Although ENIAC was too late to help in designing the atomic bomb—the machine did not become operational until 1946—von Neumann was inspired nonetheless.

The history of information technology offers many other examples of invention-by-convergence. Among them: —The modern concept of information and information processing was a synthesis of insights developed in the 1930s and 1940s by Alan Turing, Claude Shannon, Norbert Wiener, Warren McCulloch, Walter Pitts, and John von Neumann.12 —The hobbyists who sparked the personal computer revolution in the late 1970s were operating (consciously or not) in the context of ideas that had been around for a decade or more. There was the notion of interactive comput- 2990-7 ch11 waldrop 7/23/07 12:13 PM innovation and adaptation Page 125 125 ing, for example, in which a computer would respond to the user’s input immediately (as opposed to generating a stack of fanfold printout hours later); this idea dated back to the Whirlwind project, an experiment in real-time computing that began at MIT in the 1940s.13 There were the twin notions of individually controlled computing (having a computer apparently under the control of a single user) and home computing (having a computer in your own house); both emerged in the 1960s from MIT’s Project MAC, an early experiment in time-sharing.14 And then there was the notion of a computer as an open system, meaning that a user could modify it, add to it, and upgrade it however he or she wanted; that practice was already standard in the minicomputer market, which was pioneered by the Digital Equipment Corporation in the 1960s.15 —The Internet as we know it today represents the convergence of (among other ideas) the notion of packet-switched networking from the 1960s;16 the notion of internetworking (as embodied in the TCP/IP protocol), which was developed in the 1970s to allow packets to pass between different networks;17 and the notion of hypertext—which, of course, goes back to Vannevar Bush’s article on the memex in 1945. 2990-7 ch11 waldrop 7/23/07 12:13 PM Page 126 2990-7 ch12 kurth 7/23/07 12:14 PM Page 127 Part IV What Could Be 2990-7 ch12 kurth 7/23/07 12:14 PM Page 128 2990-7 ch12 kurth 7/23/07 12:14 PM Page 129 12 Cassandra versus Pollyanna A Debate between James Kurth and Gregg Easterbrook James Kurth: I am an optimist about the current pessimism, but a pessimist overall.


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Thinking Machines: The Inside Story of Artificial Intelligence and Our Race to Build the Future by Luke Dormehl

"World Economic Forum" Davos, Ada Lovelace, agricultural Revolution, AI winter, Albert Einstein, Alexey Pajitnov wrote Tetris, algorithmic management, algorithmic trading, AlphaGo, Amazon Mechanical Turk, Apple II, artificial general intelligence, Automated Insights, autonomous vehicles, backpropagation, Bletchley Park, book scanning, borderless world, call centre, cellular automata, Charles Babbage, Claude Shannon: information theory, cloud computing, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, crowdsourcing, deep learning, DeepMind, driverless car, drone strike, Elon Musk, Flash crash, Ford Model T, friendly AI, game design, Geoffrey Hinton, global village, Google X / Alphabet X, Hans Moravec, hive mind, industrial robot, information retrieval, Internet of things, iterative process, Jaron Lanier, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, life extension, Loebner Prize, machine translation, Marc Andreessen, Mark Zuckerberg, Menlo Park, Mustafa Suleyman, natural language processing, Nick Bostrom, Norbert Wiener, out of africa, PageRank, paperclip maximiser, pattern recognition, radical life extension, Ray Kurzweil, recommendation engine, remote working, RFID, scientific management, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, social intelligence, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, tech billionaire, technological singularity, The Coming Technological Singularity, The Future of Employment, Tim Cook: Apple, Tony Fadell, too big to fail, traumatic brain injury, Turing machine, Turing test, Vernor Vinge, warehouse robotics, Watson beat the top human players on Jeopardy!

Compared with the unreliable memory of humans, a machine capable of accessing thousands of items in the span of microseconds had a clear advantage. There are entire books written about the birth of modern computing, but three men stand out as laying the philosophical and technical groundwork for the field that became known as Artificial Intelligence: John von Neumann, Alan Turing and Claude Shannon. A native of Hungary, von Neumann was born in 1903 into a Jewish banking family in Budapest. In 1930, he arrived at Princeton University as a maths teacher and, by 1933, had established himself as one of six professors in the new Institute for Advanced Study in Princeton: a position he stayed in until the day he died.

By trying to find and isolate malicious behaviour online, usually based on the language involved, he came up with what is possibly the most advanced real-world version of that ambition. Negobot is programmed to operate according to the rules of game theory. Game theory was a concept first suggested by the maths pioneer John von Neumann, whose work I briefly described in chapter one. It is the study of strategic decision-making, in which there are multiple players all with their own motives. The payoff depends on the behaviour of these different players. Not everyone can get what they want – and the aim is to predict how people will act and hopefully to turn this to your advantage.

‘Shortly after, the human era will be ended.’ This term, ‘the Singularity’, referring to the point at which machines overtake humans on the intelligence scale, has become an AI reference as widely cited as the Turing Test. It is often credited to Vinge, although in reality the first computer scientist to use it was John von Neumann. In the last decade of von Neumann’s life, he had a conversation with Stan Ulam, a Polish-American mathematician with whom he had collaborated on the Manhattan Project. Recalling the conversation later, Ulam noted that von Neumann was fascinated – and perhaps alarmed – by ‘the ever-accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue’.


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How Markets Fail: The Logic of Economic Calamities by John Cassidy

Abraham Wald, Alan Greenspan, Albert Einstein, An Inconvenient Truth, Andrei Shleifer, anti-communist, AOL-Time Warner, asset allocation, asset-backed security, availability heuristic, bank run, banking crisis, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Black Monday: stock market crash in 1987, Black-Scholes formula, Blythe Masters, book value, Bretton Woods, British Empire, business cycle, capital asset pricing model, carbon tax, Carl Icahn, centralized clearinghouse, collateralized debt obligation, Columbine, conceptual framework, Corn Laws, corporate raider, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, Daniel Kahneman / Amos Tversky, debt deflation, different worldview, diversification, Elliott wave, Eugene Fama: efficient market hypothesis, financial deregulation, financial engineering, financial innovation, Financial Instability Hypothesis, financial intermediation, full employment, Garrett Hardin, George Akerlof, Glass-Steagall Act, global supply chain, Gunnar Myrdal, Haight Ashbury, hiring and firing, Hyman Minsky, income per capita, incomplete markets, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, junk bonds, Kenneth Arrow, Kickstarter, laissez-faire capitalism, Landlord’s Game, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, low interest rates, mandelbrot fractal, margin call, market bubble, market clearing, mental accounting, Mikhail Gorbachev, military-industrial complex, Minsky moment, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, Myron Scholes, Naomi Klein, negative equity, Network effects, Nick Leeson, Nixon triggered the end of the Bretton Woods system, Northern Rock, paradox of thrift, Pareto efficiency, Paul Samuelson, Phillips curve, Ponzi scheme, precautionary principle, price discrimination, price stability, principal–agent problem, profit maximization, proprietary trading, quantitative trading / quantitative finance, race to the bottom, Ralph Nader, RAND corporation, random walk, Renaissance Technologies, rent control, Richard Thaler, risk tolerance, risk-adjusted returns, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, Savings and loan crisis, shareholder value, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical model, subprime mortgage crisis, tail risk, Tax Reform Act of 1986, technology bubble, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, too big to fail, Tragedy of the Commons, transaction costs, Two Sigma, unorthodox policies, value at risk, Vanguard fund, Vilfredo Pareto, wealth creators, zero-sum game

To do this, though, he was forced to introduce some simplifications, such as assuming that the price of each commodity depended only on the quantities it was produced in, and not on the quantities of competing goods. Since the main point of Walrasian economics was to explore the connections between different markets, this wasn’t entirely satisfactory, but it was the best Wald could do. There things rested until 1937, when John von Neumann, a Princeton mathematician who had taught in Berlin before moving to the United States, visited Vienna and presented a paper to Menger’s Mathematical Colloquium that one leading historian of economic ideas has called “the single most important article in mathematical economics.” That judgment is debatable, but von Neumann, who was born in Budapest in 1903, was undoubtedly some sort of genius.

In many cases, it is the basis of what I call rational irrationality, by which I mean a situation in which the application of rational self-interest in the marketplace leads to an inferior and socially irrational outcome. When the prisoner’s dilemma was first introduced, back in the early 1950s, many people refused to accept that the two firms wouldn’t be able to reach the cooperative solution. Economists and mathematicians were excitedly exploring the new science of game theory that John von Neumann and Oskar Morgenstern had invented in their 1944 treatise Theory of Games and Economic Behavior. Many smart people held out great hope for game theory, imagining it could solve many of the outstanding problems in the social sciences. The key to this process was thought to lie in extending the solution methods that von Neumann and Morgenstern had introduced, most of which applied to zero-sum games, such as coin-tossing and poker.

“They are concerned, not with what an investment is really worth to a man who buys it ‘for keeps,’ but with what the market will value it at, under the influence of mass psychology, three months or a year hence.” (If he had been writing in today’s world of day traders and momentum funds, Keynes might well have written “three hours or a day hence.”) Like John von Neumann, the Hungarian genius who invented game theory, Keynes believed that simple parlor games have much to teach economists: they feature the sort of strategic interactions that are largely absent from orthodox economics, but that play such an important role in reality. On Wall Street, Keynes pointed out, investing is a “battle of wits,” the primary aim being “to outwit the crowd, and to pass the bad, or depreciating, half-crown to the other fellow.”


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AIQ: How People and Machines Are Smarter Together by Nick Polson, James Scott

Abraham Wald, Air France Flight 447, Albert Einstein, algorithmic bias, Amazon Web Services, Atul Gawande, autonomous vehicles, availability heuristic, basic income, Bayesian statistics, Big Tech, Black Lives Matter, Bletchley Park, business cycle, Cepheid variable, Checklist Manifesto, cloud computing, combinatorial explosion, computer age, computer vision, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, Donald Trump, Douglas Hofstadter, Edward Charles Pickering, Elon Musk, epigenetics, fake news, Flash crash, Grace Hopper, Gödel, Escher, Bach, Hans Moravec, Harvard Computers: women astronomers, Higgs boson, index fund, information security, Isaac Newton, John von Neumann, late fees, low earth orbit, Lyft, machine translation, Magellanic Cloud, mass incarceration, Moneyball by Michael Lewis explains big data, Moravec's paradox, more computing power than Apollo, natural language processing, Netflix Prize, North Sea oil, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, p-value, pattern recognition, Pierre-Simon Laplace, ransomware, recommendation engine, Ronald Reagan, Salesforce, self-driving car, sentiment analysis, side project, Silicon Valley, Skype, smart cities, speech recognition, statistical model, survivorship bias, systems thinking, the scientific method, Thomas Bayes, Uber for X, uber lyft, universal basic income, Watson beat the top human players on Jeopardy!, young professional

It took the bombing of Pearl Harbor to rouse the American people from their torpor, but roused they were at last. Young men surged forward to enlist. Women joined factories and nursing units. And scientists rushed to their labs and chalkboards, especially the many émigrés who’d fled the Nazis in terror: Albert Einstein, John von Neumann, Edward Teller, Stanislaw Ulam, and hundreds of other brilliant refugees who gave American science a decisive boost during the war. Abraham Wald, too, was eager to answer the call. He was soon given the chance, when his colleague W. Allen Wallis invited him to join Columbia’s Statistical Research Group.

It’s a good thing that an Nvidia graphics card in 2018 can do 1.5 billion calculations in less than 0.0001 seconds. Factor 2: Massive Data But there’s a caveat: to fit a massive model, you need a massive data set. A model like Google’s Inception, with 388,736 parameters, tends to blow the minds of old-school scientists and engineers, who regard such massive models with contempt. The great mathematician John von Neumann, for example, once famously criticized a complicated model with the following enigmatic quip: “With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.” Von Neumann meant that a model with lots of parameters is in danger of “overfitting,” which happens when a model just memorizes the random noise in the training data rather than learns the underlying pattern.

This solution doesn’t work for presidential elections; there have only been 56 of them, so there is basically no way to tell from the data alone whether a complicated post-hoc explanation of who wins the presidency has any value in predicting the future. But it works brilliantly for models that extract patterns from images, texts, and videos, which we have in abundance. John von Neumann would surely be amazed at the result. He thought that you could “fit an elephant” with only four parameters, but it turns out you need 388,736 of them—or at least you need that many parameters to identify an elephant in the photos from your African safari. There’s no magic here, just massive data sets with millions or billions of data points.


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The Doomsday Calculation: How an Equation That Predicts the Future Is Transforming Everything We Know About Life and the Universe by William Poundstone

Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, Arthur Eddington, Bayesian statistics, behavioural economics, Benoit Mandelbrot, Berlin Wall, bitcoin, Black Swan, conceptual framework, cosmic microwave background, cosmological constant, cosmological principle, CRISPR, cuban missile crisis, dark matter, DeepMind, digital map, discounted cash flows, Donald Trump, Doomsday Clock, double helix, Dr. Strangelove, Eddington experiment, Elon Musk, Geoffrey Hinton, Gerolamo Cardano, Hans Moravec, heat death of the universe, Higgs boson, if you see hoof prints, think horses—not zebras, index fund, Isaac Newton, Jaron Lanier, Jeff Bezos, John Markoff, John von Neumann, Large Hadron Collider, mandelbrot fractal, Mark Zuckerberg, Mars Rover, Neil Armstrong, Nick Bostrom, OpenAI, paperclip maximiser, Peter Thiel, Pierre-Simon Laplace, Plato's cave, probability theory / Blaise Pascal / Pierre de Fermat, RAND corporation, random walk, Richard Feynman, ride hailing / ride sharing, Rodney Brooks, Ronald Reagan, Ronald Reagan: Tear down this wall, Sam Altman, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, Skype, Stanislav Petrov, Stephen Hawking, strong AI, tech billionaire, Thomas Bayes, Thomas Malthus, time value of money, Turing test

As philosopher Daniel Hill said of Bostrom, “His interest in science was a natural outgrowing of his understandable desire to live forever, basically.” Another transhumanist tenet is the singularity. The term was first used by mathematician Stanislaw Ulam in 1958, recalling a conversation with John von Neumann (who died in 1957). In math, dividing by zero creates a singularity—a point where a function is undefined. Ulam and von Neumann used the jargon metaphorically, speaking of “the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.”

They annihilate themselves in global war before they get around to exploring the galaxy. “What we all fervently hope,” Fermi once said, “is that man will soon grow sufficiently adult to make good use of the powers that he acquires over nature.” Privately Fermi believed atomic weapons would lead to war. His Manhattan Project colleague, mathematician John von Neumann, minced no words. He rated it “absolutely certain (1) that there would be a nuclear war; and (2) that everyone would die in it.” Drake Equation The consensus of biologists and screenwriters is that we are not alone in the universe. This is not a new idea. Dominican friar Giordano Bruno, a supporter of Copernicus, asserted that stars are suns, circled by planets harboring intelligent beings.

(We have little interest in communicating with ibexes, much less in establishing diplomatic relations with every ibex herd or zoo specimen.) It could be that contact with a more advanced civilization is known to be devastating to the less advanced civilization. ETs might be avoiding us for our own protection. Even in Fermi’s time, there was a comeback for these ideas: von Neumann probes, described by John von Neumann. The best-known examples, fictional of course, are the black monoliths in Stanley Kubrick’s 2001: A Space Odyssey. An early cut of the film had a segment explaining exactly what the monoliths were. They were identified as self-reproducing machines, designed to explore space. Kubrick decided to cut the exposition, leaving the monoliths enigmatic and symbolic.


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Our Final Invention: Artificial Intelligence and the End of the Human Era by James Barrat

AI winter, air gap, AltaVista, Amazon Web Services, artificial general intelligence, Asilomar, Automated Insights, Bayesian statistics, Bernie Madoff, Bill Joy: nanobots, Bletchley Park, brain emulation, California energy crisis, cellular automata, Chuck Templeton: OpenTable:, cloud computing, cognitive bias, commoditize, computer vision, Computing Machinery and Intelligence, cuban missile crisis, Daniel Kahneman / Amos Tversky, Danny Hillis, data acquisition, don't be evil, drone strike, dual-use technology, Extropian, finite state, Flash crash, friendly AI, friendly fire, Google Glasses, Google X / Alphabet X, Hacker News, Hans Moravec, Isaac Newton, Jaron Lanier, Jeff Hawkins, John Markoff, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, Loebner Prize, lone genius, machine translation, mutually assured destruction, natural language processing, Neil Armstrong, Nicholas Carr, Nick Bostrom, optical character recognition, PageRank, PalmPilot, paperclip maximiser, pattern recognition, Peter Thiel, precautionary principle, prisoner's dilemma, Ray Kurzweil, Recombinant DNA, Rodney Brooks, rolling blackouts, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Silicon Valley, Singularitarianism, Skype, smart grid, speech recognition, statistical model, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steve Wozniak, strong AI, Stuxnet, subprime mortgage crisis, superintelligent machines, technological singularity, The Coming Technological Singularity, Thomas Bayes, traveling salesman, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, zero day

It means that an individual or “agent” will have goals and also preferences (called a utility function in economics). He will have beliefs about the world and the best way to achieve his goals and preferences. As conditions change, he will update his beliefs. He is a rational economic agent when he pursues his goals with actions based on up-to-date beliefs about the world. Mathematician John von Neumann (1903–1957) codeveloped the idea connecting rationality and utility functions. As we’ll see, von Neumann laid the groundwork for many ideas in computer science, AI, and economics. Yet social scientists argue that a “rational economic agent” is a load of hogwash. Humans are not rational—we don’t specify our goals or our beliefs, and we don’t always update our beliefs as conditions change.

Probably only Good, and Leslie Pendleton, knew about it. Vernor Vinge was the first person to formally use the word “singularity” when describing the technological future—he did it in a 1993 address to NASA, entitled “The Coming Technological Singularity.” Mathematician Stanislaw Ulam reported that he and polymath John von Neumann had used “singularity” in a conversation about technological change thirty-five years earlier, in 1958. But Vinge’s coinage was public, deliberate, and set the singularity ball rolling into the hands of Ray Kurzweil and what is today a Singularity movement. With that street cred, why doesn’t Vinge work the lecture and conference circuits as the ultimate Singularity pundit?

So, there’s hundreds of thousands of people in the world, very smart people, who are working on things that lead to superhuman intelligence. And probably most of them don’t even look at it that way. They look at it as faster, cheaper, better, more profitable.” Vinge compares it to the Cold War strategy called MAD—mutually assured destruction. Coined by acronym-loving John von Neumann (also the creator of an early computer with the winning initials, MANIAC), MAD maintained Cold War peace through the promise of mutual obliteration. Like MAD, superintelligence boasts a lot of researchers secretly working to develop technologies with catastrophic potential. But it’s like mutually assured destruction without any commonsense brakes.


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The Quest: Energy, Security, and the Remaking of the Modern World by Daniel Yergin

"Hurricane Katrina" Superdome, "World Economic Forum" Davos, accelerated depreciation, addicted to oil, Alan Greenspan, Albert Einstein, An Inconvenient Truth, Asian financial crisis, Ayatollah Khomeini, banking crisis, Berlin Wall, bioinformatics, book value, borderless world, BRICs, business climate, California energy crisis, carbon credits, carbon footprint, carbon tax, Carl Icahn, Carmen Reinhart, clean tech, Climategate, Climatic Research Unit, colonial rule, Colonization of Mars, corporate governance, cuban missile crisis, data acquisition, decarbonisation, Deng Xiaoping, Dissolution of the Soviet Union, diversification, diversified portfolio, electricity market, Elon Musk, energy security, energy transition, Exxon Valdez, facts on the ground, Fall of the Berlin Wall, fear of failure, financial innovation, flex fuel, Ford Model T, geopolitical risk, global supply chain, global village, Great Leap Forward, Greenspan put, high net worth, high-speed rail, hydraulic fracturing, income inequality, index fund, informal economy, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), It's morning again in America, James Watt: steam engine, John Deuss, John von Neumann, Kenneth Rogoff, life extension, Long Term Capital Management, Malacca Straits, market design, means of production, megacity, megaproject, Menlo Park, Mikhail Gorbachev, military-industrial complex, Mohammed Bouazizi, mutually assured destruction, new economy, no-fly zone, Norman Macrae, North Sea oil, nuclear winter, off grid, oil rush, oil shale / tar sands, oil shock, oil-for-food scandal, Paul Samuelson, peak oil, Piper Alpha, price mechanism, purchasing power parity, rent-seeking, rising living standards, Robert Metcalfe, Robert Shiller, Robert Solow, rolling blackouts, Ronald Coase, Ronald Reagan, Sand Hill Road, Savings and loan crisis, seminal paper, shareholder value, Shenzhen special economic zone , Silicon Valley, Silicon Valley billionaire, Silicon Valley startup, smart grid, smart meter, South China Sea, sovereign wealth fund, special economic zone, Stuxnet, Suez crisis 1956, technology bubble, the built environment, The Nature of the Firm, the new new thing, trade route, transaction costs, unemployed young men, University of East Anglia, uranium enrichment, vertical integration, William Langewiesche, Yom Kippur War

Pollack, and Carl Sagan, “Nuclear Winter: Global Consequences of Multiple Nuclear Explosions,” Science 222, no. 4630 (1983), pp. 1283–92. 25 Hart and Victor, “Scientific Elites,” pp. 657–61 (“advertant”); Weart, The Discovery of Global Warming, p. 5 (Kennedy); Martin Campbell-Kelly and William Aspray, Computer: A History of the Information Machine (Boulder, CO: Westview Press, 2004), p. 79 (“considerable temerity”). 26 Norman Macrae, John von Neumann: The Scientific Genius Who Pioneered the Modern Computer, Game Theory, Nuclear Deterrence, and Much More (American Mathematical Society, 2008), pp. 5, 248 (“last words”). 27 Macrae, John von Neumann, pp. 52, 250, 266, 325, 369; Stanislaw M. Ulam, Adventures of a Mathematician (Berkeley: University of California Press, 1991), pp. 4, 203, 245. 28 Campbell-Kelly and Aspray, Computer, pp. 3–4 (“computers”); Macrae, John von Neumann, p. 234 (“modern mathematical modeling”). 29 Macrae, John von Neumann, pp. 298, 302 (“phenomena”). 30 Spencer Weart, “Government: The View from Washington, DC,” The Discovery of Global Warming, at http://www.aip.org/history/climate/Govt.htm (“warfare”); Macrae, John von Neumann, pp. 298, 316 (“jiggle,” “weather predictions”); New York Times, February 9, 1957 (“electronic brain”). 31 Norman Phillips, “Jule Charney, 1917–1981,” Annals of the History of Computing 3, no. 4 (1981), pp. 318–19; Norman Phillips, “Jule Charney’s Influence on Meteorology,” Bulletin of the American Meteorological Society 63, no. 5 (1982), pp. 492–98; John M.

A young mathematician caught sight of a world-famous figure—at least world famous in the worlds of science and mathematics. His name was John von Neumann. “With considerable temerity” the mathematician, Herman Goldfine, started a conversation. To Goldfine’s surprise, von Neumann, despite his towering reputation, was quite friendly. But when Goldfine told von Neumann that he was helping develop “an electronic computer capable of 333 multiplications per second,” the conversation abruptly changed “from one of relaxed good humor to one more like the oral examination for the doctor’s degree in mathematics.”25 John von Neumann—born János Neumann in Budapest—had emigrated to the United States in 1930 to become, along with Albert Einstein, one of the first faculty members at Princeton’s Institute for Advanced Study.

Ulam, Adventures of a Mathematician (Berkeley: University of California Press, 1991), pp. 4, 203, 245. 28 Campbell-Kelly and Aspray, Computer, pp. 3–4 (“computers”); Macrae, John von Neumann, p. 234 (“modern mathematical modeling”). 29 Macrae, John von Neumann, pp. 298, 302 (“phenomena”). 30 Spencer Weart, “Government: The View from Washington, DC,” The Discovery of Global Warming, at http://www.aip.org/history/climate/Govt.htm (“warfare”); Macrae, John von Neumann, pp. 298, 316 (“jiggle,” “weather predictions”); New York Times, February 9, 1957 (“electronic brain”). 31 Norman Phillips, “Jule Charney, 1917–1981,” Annals of the History of Computing 3, no. 4 (1981), pp. 318–19; Norman Phillips, “Jule Charney’s Influence on Meteorology,” Bulletin of the American Meteorological Society 63, no. 5 (1982), pp. 492–98; John M. Lewis, “Smagorinsky’s GFDL: Building the Team,” Bulletin of the American Meteorological Society 89, no. 9 (2008), pp. 1339–53; Macrae, John von Neumann, pp. 316–20. 32 “ ‘Suki’ Manabe: Pioneer of Climate Modeling,” IPRC Climate 5, no. 2 (2005), pp. 11–15; Syukuro Manabe and Richard Wetherald, “Thermal Equilibrium of the Atmosphere with a Given Distribution of Relative Humidity,” Journal of Atmospheric Sciences 24, no. 3 (1967), pp. 241–59; Spencer Weart, “General Circulation Models of Climate,” The Discovery of Global Warming, at http://www.aip.org/history/climate/GCM.htm. 33 Interview with Fred Krupp. 34 Macrae, John von Neumann, p. 3245–326 (most prominent meteorologist); James G.


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The Making of the Atomic Bomb by Richard Rhodes

Able Archer 83, Albert Einstein, Arthur Eddington, Brownian motion, Charles Lindbergh, cuban missile crisis, death from overwork, Donner party, Eddington experiment, Ernest Rutherford, Etonian, fixed income, full employment, God and Mammon, Isaac Newton, jitney, John von Neumann, Louis Pasteur, nuclear winter, publish or perish, Richard Feynman, Ronald Reagan, seminal paper, the scientific method, Upton Sinclair, uranium enrichment, Works Progress Administration

At the end of March 1933 the most original physicist of the twentieth century once again renounced his German citizenship. Princeton University acquired John von Neumann and Eugene Wigner in 1930, in Wigner’s puckish recollection, as a package deal. The university sought advice on improving its science from Paul Ehrenfest, who “recommended to them not to invite a single person but at least two . . . who already knew each other, who wouldn’t feel suddenly put on an island where they have no intimate contact with anybody. Johnny’s name was of course well known by that time the world over, so they decided to invite Johnny von Neumann. They looked: who wrote articles with John von Neumann? They found: Mr. Wigner. So they sent a telegram to me also.”683 In fact, Wigner had already earned a high reputation in a recondite area of physics known as group theory, about which he published a book in 1931.

Caught between predominantly Jewish socialists and radicals on one side and the entrenched bureaucracy on the other, both sides hostile, the Jewish commercial elite allied itself for survival with the old nobility and the monarchy; one measure of that conservative alliance was the dramatic increase in the early twentieth century of ennobled Jews. George de Hevesy’s prosperous maternal grandfather, S. V. Schossberger, became in 1863 the first unconverted Jew ennobled since the Middle Ages, and in 1895 de Hevesy’s entire family was ennobled.387 Max Neumann, the banker father of the brilliant mathematician John von Neumann, was elevated in 1913. Von Kármán’s father’s case was exceptional. Mór Kármán, the founder of the celebrated Minta school, was an educator rather than a wealthy businessman. In the last decades of the nineteenth century he reorganized the haphazard Hungarian school system along German lines, to its great improvement—and not incidentally wrested control of education from the religious institutions that dominated it and passed that control to the state.

They were thus brought into political connection, their power of independent action siphoned away. Out of the prospering but vulnerable Hungarian Jewish middle class came no fewer than seven of the twentieth century’s most exceptional scientists: in order of birth, Theodor von Kármán, George de Hevesy, Michael Polanyi, Leo Szilard, Eugene Wigner, John von Neumann and Edward Teller. All seven left Hungary as young men; all seven proved unusually versatile as well as talented and made major contributions to science and technology; two among them, de Hevesy and Wigner, eventually won Nobel Prizes. The mystery of such a concentration of ability from so remote and provincial a place has fascinated the community of science.


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The Logic of Life: The Rational Economics of an Irrational World by Tim Harford

activist fund / activist shareholder / activist investor, affirmative action, Albert Einstein, Andrei Shleifer, barriers to entry, behavioural economics, Berlin Wall, business cycle, colonial rule, company town, Daniel Kahneman / Amos Tversky, double entry bookkeeping, Dr. Strangelove, Edward Glaeser, en.wikipedia.org, endowment effect, European colonialism, experimental economics, experimental subject, George Akerlof, income per capita, invention of the telephone, Jane Jacobs, John von Neumann, Larry Ellison, law of one price, Martin Wolf, mutually assured destruction, New Economic Geography, new economy, Patri Friedman, plutocrats, Richard Florida, Richard Thaler, Ronald Reagan, Silicon Valley, spinning jenny, Steve Jobs, The Death and Life of Great American Cities, the market place, the strength of weak ties, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Malthus, Tyler Cowen, women in the workforce, zero-sum game

The Vegas lobby, with poker on one side and slot machines on the other, is a visual metaphor for how game theory has matured—a story that can best be told by contrasting two of the most famous game theorists. Both were cold war intellectuals, advising the U.S. government at the highest levels and using game theory to try to understand the riskiest of all games, nuclear war. Game theory emerged from the sparkling mind of John von Neumann, a celebrated mathematical prodigy, when he decided to create a theory of poker. Von Neumann’s academic brilliance offered penetrating insights but the cold force of his logic could have led us to Armageddon. It was tempered by the earthier wisdom—usually expressed in witty prose rather than equations—of Thomas Schelling.

Tormented by a tobacco addiction he could not kick, Schelling nudged game theory into a direction that now offers us surprising insights into the minds of hapless slot machine addicts. LATE IN THE 1920s, the most ostentatiously brilliant man in the world decided to work out the correct way to play poker. John von Neumann, a mathematician who helped to develop both the computer and the atomic bomb, had been struck by an engaging new conceit. Could his beloved mathematics uncover the secrets of poker, which seemed to be a quintessentially human game of secrets and lies? Von Neumann believed that if you wanted a theory—he called it “game theory”—that could explain life, you should start with a theory that could explain poker.

It was not a high spot for Andy, nor for my project of using economics as a tool for self-improvement. You might think that was the first and last time any economist has dared to show his face at a speed date, but not at all. We can’t get enough of them. Economists at Columbia University even went to the trouble of organizing one. Ever since John von Neumann’s game theory promised to help us understand love and marriage, economists have been interested in how people choose their partners and how relationships work. And if you want to understand the way people choose their partners, a speed date is a great place to start. At a speed date you can get information about how each person responded to dozens of potential partners, something that would be impossible to collect in more traditional dating situations without binoculars, snooping devices, and a good private investigator.


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The Chip: How Two Americans Invented the Microchip and Launched a Revolution by T. R. Reid

Albert Einstein, Bob Noyce, Claude Shannon: information theory, computer age, cotton gin, discovery of penicillin, double helix, Ernest Rutherford, Fairchild Semiconductor, full employment, George Gilder, Guggenheim Bilbao, hiring and firing, industrial robot, Internet Archive, Isaac Newton, John von Neumann, Menlo Park, New Journalism, Norbert Wiener, oil shock, PalmPilot, Parkinson's law, popular electronics, Richard Feynman, Ronald Reagan, seminal paper, Silicon Valley, Turing machine, William Shockley: the traitorous eight

The ingenious, indeed breathtaking, insight that binary mathematics was perfectly suited to electronic computers occurred more or less simultaneously on both sides of the Atlantic to a pair of ingenious, indeed breathtaking, visionaries who had scoped out, by the late 1940s, remarkably accurate forecasts of the development of digital computers over the ensuing half century. These two cybernetic pioneers were John von Neumann and Alan M. Turing. Von Neumann was born in Budapest, the son of a wealthy banker, in 1903. He was recognized almost immediately as a prodigious mathematical talent, and spent his youth shuttling from one great university to another: Berlin, Zurich, Budapest, Göttingen, Hamburg. He published his first scholarly monograph at the age of eighteen and thereafter turned out key papers in a wide variety of fields.

One of the first things Kilby realized was that tearing apart existing adding machines to see how they worked—a process known as reverse engineering—would offer little, if any, help, because the basic architecture of this pocket-size device would have to be completely new. And so the team started at ground zero, setting down the fundamental elements that their calculator would require. In accordance with the architecture worked out by Alan Turing and John von Neumann, all digital devices, from the most powerful mainframe supercomputer to the simplest handheld electronic game, can be divided into four basic parts serving four essential functions: Input: The unit that receives information from a human operator, a sensory device, or another computer and delivers it to the processing unit.

An important contribution to this literature is Herman Goldstine’s The Computer from Pascal to von Neumann (Princeton, N.J.: Princeton University Press, 1972), which is strangely organized but has the immediacy that could be conveyed only by one who was present at the creation of the modem electronic computer. Andrew Hodges, Alan Turing: The Enigma (New York: Simon & Schuster, 1983), and Steve J. Heims, John von Neumann and Norbert Wiener (Cambridge, Mass.: MIT Press, 1980), are the first complete biographies. Von Neumann’s seminal paper “Preliminary Discussion of the Logical Design of an Electronic Computing Instrument” is reprinted in John Diebold, ed., The World of the Computer (New York: Random House, 1973).


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Code: The Hidden Language of Computer Hardware and Software by Charles Petzold

Bill Gates: Altair 8800, Charles Babbage, Claude Shannon: information theory, computer age, Dennis Ritchie, digital divide, Donald Knuth, Douglas Engelbart, Douglas Engelbart, Dynabook, Eratosthenes, Fairchild Semiconductor, Free Software Foundation, Gary Kildall, Grace Hopper, invention of the telegraph, Isaac Newton, Ivan Sutherland, Jacquard loom, James Watt: steam engine, John von Neumann, Joseph-Marie Jacquard, Ken Thompson, Louis Daguerre, millennium bug, Multics, Norbert Wiener, optical character recognition, popular electronics, Richard Feynman, Richard Stallman, Silicon Valley, Steve Jobs, Turing machine, Turing test, Vannevar Bush, Von Neumann architecture

Atanasoff (1903–1995), who earlier designed an electronic computer that never worked quite right. The ENIAC attracted the interest of mathematician John von Neumann (1903–1957). Since 1930, the Hungarian-born von Neumann (whose last name is pronounced noy mahn) had been living in the United States. A flamboyant man who had a reputation for doing complex arithmetic in his head, von Neumann was a mathematics professor at the Princeton Institute for Advanced Study, and he did research in everything from quantum mechanics to the application of game theory to economics. John von Neumann helped design the successor to the ENIAC, the EDVAC (Electronic Discrete Variable Automatic Computer).

Microsoft, MS-DOS, and Windows are either registered trademarks or trademarks of Microsoft Corporation in the United States and/or other countries. Other product and company names mentioned herein may be the trademarks of their respective owners. Images of Charles Babbage, George Boole, Louis Braille, Herman Hollerith, Samuel Morse, and John von Neumann appear courtesy of Corbis Images and were modified for this book by Joel Panchot. The January 1975 cover of Popular Electronics is reprinted by permission of Ziff-Davis and the Ziff family. All other illustrations in the book were produced by Joel Panchot. Unless otherwise noted, the example companies, organizations, products, people, and events depicted herein are fictitious.

Such memory consisted of large arrays of little magnetized metal rings strung with wires. Each little ring could store a bit of information. Long after core memory had been replaced by other technologies, it was common to hear older programmers refer to the memory that the processor accessed as core. John von Neumann wasn't the only person doing some major conceptual thinking about the nature of computers in the 1940s. Claude Shannon (born 1916) was another influential thinker. In Chapter 11, I discussed his 1938 master's thesis, which established the relationship between switches, relays, and Boolean algebra.


pages: 415 words: 125,089

Against the Gods: The Remarkable Story of Risk by Peter L. Bernstein

Alan Greenspan, Albert Einstein, Alvin Roth, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, Bayesian statistics, behavioural economics, Big bang: deregulation of the City of London, Bretton Woods, business cycle, buttonwood tree, buy and hold, capital asset pricing model, cognitive dissonance, computerized trading, Daniel Kahneman / Amos Tversky, diversified portfolio, double entry bookkeeping, Edmond Halley, Edward Lloyd's coffeehouse, endowment effect, experimental economics, fear of failure, Fellow of the Royal Society, Fermat's Last Theorem, financial deregulation, financial engineering, financial innovation, full employment, Great Leap Forward, index fund, invention of movable type, Isaac Newton, John Nash: game theory, John von Neumann, Kenneth Arrow, linear programming, loss aversion, Louis Bachelier, mental accounting, moral hazard, Myron Scholes, Nash equilibrium, Norman Macrae, Paul Samuelson, Philip Mirowski, Post-Keynesian economics, probability theory / Blaise Pascal / Pierre de Fermat, prudent man rule, random walk, Richard Thaler, Robert Shiller, Robert Solow, spectrum auction, statistical model, stocks for the long run, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, Thomas Bayes, trade route, transaction costs, tulip mania, Vanguard fund, zero-sum game

So we usually settle for compromise alternatives, which may require us to make the best of a bad bargain; game theory uses terms like "maximin" and "minimax" to describe such decisions. Think of seller-buyer, landlord-tenant, husband-wife, lender-borrower, GM-Ford, parentchild, President-Congress, driver-pedestrian, boss-employee, pitcherbatter, soloist-accompanist. Game theory was invented by John von Neumann (1903-1957), a physicist of immense intellectual accomplishment.' Von Neumann was instrumental in the discovery of quantum mechanics in Berlin during the 1920s, and he played a major role in the creation of the first American atomic bomb and, later, the hydrogen bomb. He also invented the digital computer, was an accomplished meteorologist and mathematician, could multiply eight digits by eight digits in his head, and loved telling ribald jokes and reciting off-color limericks.

Von Neumann was born in Budapest to a well-to-do, cultured, jolly family. Budapest at the time was the sixth-largest city in Europe, prosperous and growing, with the world's first underground subway. Its literacy rate was over 90%. More than 25% of the population was Jewish, including the von Neumanns, although John von Neumann paid little attention to his Jewishness except as a source of jokes. He was by no means the only famous product of pre-World War I Budapest. Among his contemporaries were famous physicists like himself-Leo Szilard and Edward Teller-as well as celebrities from the world of entertainment-George Solti, Paul Lukas, Leslie Howard (born Lazlo Steiner), Adolph Zukor, Alexander Korda, and, perhaps most famous of all, ZsaZsa Gabor.

Strangely, Markowitz had no interest in equity investment when he first turned his attention to the ideas dealt with in "Portfolio Selection." He knew nothing about the stock market. A self-styled "nerd" as a student, he was working in what was then the relatively young field of linear programming. Linear programming, which happened to be an innovation to which John von Neumann had made significant contributions, is a means of developing mathematical models for minimizing costs while holding outputs constant, or for maximizing outputs while holding costs constant. The technique is essential for dealing with problems like those faced by an airline that aims to keep a limited number of aircraft as busy as possible while flying to as many destinations as possible.


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The Singularity Is Near: When Humans Transcend Biology by Ray Kurzweil

additive manufacturing, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, Benoit Mandelbrot, Bill Joy: nanobots, bioinformatics, brain emulation, Brewster Kahle, Brownian motion, business cycle, business intelligence, c2.com, call centre, carbon-based life, cellular automata, Charles Babbage, Claude Shannon: information theory, complexity theory, conceptual framework, Conway's Game of Life, coronavirus, cosmological constant, cosmological principle, cuban missile crisis, data acquisition, Dava Sobel, David Brooks, Dean Kamen, digital divide, disintermediation, double helix, Douglas Hofstadter, en.wikipedia.org, epigenetics, factory automation, friendly AI, functional programming, George Gilder, Gödel, Escher, Bach, Hans Moravec, hype cycle, informal economy, information retrieval, information security, invention of the telephone, invention of the telescope, invention of writing, iterative process, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, lifelogging, linked data, Loebner Prize, Louis Pasteur, mandelbrot fractal, Marshall McLuhan, Mikhail Gorbachev, Mitch Kapor, mouse model, Murray Gell-Mann, mutually assured destruction, natural language processing, Network effects, new economy, Nick Bostrom, Norbert Wiener, oil shale / tar sands, optical character recognition, PalmPilot, pattern recognition, phenotype, power law, precautionary principle, premature optimization, punch-card reader, quantum cryptography, quantum entanglement, radical life extension, randomized controlled trial, Ray Kurzweil, remote working, reversible computing, Richard Feynman, Robert Metcalfe, Rodney Brooks, scientific worldview, Search for Extraterrestrial Intelligence, selection bias, semantic web, seminal paper, Silicon Valley, Singularitarianism, speech recognition, statistical model, stem cell, Stephen Hawking, Stewart Brand, strong AI, Stuart Kauffman, superintelligent machines, technological singularity, Ted Kaczynski, telepresence, The Coming Technological Singularity, Thomas Bayes, transaction costs, Turing machine, Turing test, two and twenty, Vernor Vinge, Y2K, Yogi Berra

Although the number of transistors per unit cost has doubled every two years, transistors have been getting progressively faster, and there have been many other levels of innovation and improvement. The overall power of computation per unit cost has recently been doubling every year. In particular, the amount of computation (in computations per second) that can be brought to bear to a computer chess machine doubled every year during the 1990s. 3. John von Neumann, paraphrased by Stanislaw Ulam, "Tribute to John von Neumann," Bulletin of the American Mathematical Society 64.3, pt. 2 (May 1958): 1–49. Von Neumann (1903–1957) was born in Budapest into a Jewish banking family and came to Princeton University to teach mathematics in 1930. In 1933 he became one of the six original professors in the new Institute for Advanced Study in Princeton, where he stayed until the end of his life.

The Intuitive Linear View Versus the Historical Exponential View When the first transhuman intelligence is created and launches itself into recursive self-improvement, a fundamental discontinuity is likely to occur, the likes of which I can't even begin to predict. —MICHAEL ANISSIMOV In the 1950s John von Neumann, the legendary information theorist, was quoted as saying that "the ever-accelerating progress of technology ... gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue."3 Von Neumann makes two important observations here: acceleration and singularity.

One theory speculates that the universe itself began with such a Singularity.18 Interestingly, however, the event horizon (surface) of a black hole is of J finite size, and gravitational force is only theoretically infinite at the zero-size center of the black hole. At any location that could actually be measured, the forces are finite, although extremely large. The first reference to the Singularity as an event capable of rupturing the fabric of human history is John von Neumann's statement quoted above. In the 1960s, I. J. Good wrote of an "intelligence explosion" resulting from intelligent machines' designing their next generation without human intervention. Vernor Vinge, a mathematician and computer scientist at San Diego State University, wrote about a rapidly approaching "technological singularity" in an article for Omni magazine in 1983 and in a science-fiction novel, Marooned in Realtime, in 1986.19 My 1989 book, The Age of Intelligent Machines, presented a future headed inevitably toward machines greatly exceeding human intelligence in the first half of the twenty-first century.20 Hans Moravec's 1988 book Mind Children came to a similar conclusion by analyzing the progression of robotics.21 In 1993 Vinge presented a paper to a NASA-organized symposium that described the Singularity as an impending event resulting primarily from the advent of "entities with greater than human intelligence," which Vinge saw as the harbinger of a runaway phenomenon.22 My 1999 book, The Age of Spiritual Machines: When Computers Exceed Human Intelligence, described the increasingly intimate connection between our biological intelligence and the artificial intelligence we are creating.23 Hans Moravec's book Robot: Mere Machine to Transcendent Mind, also published in 1999, described the robots of the 2040s as our "evolutionary heirs," machines that will "grow from us, learn our skills, and share our goals and values, ... children of our minds."24 Australian scholar Damien Broderick's 1997 and 2001 books, both titled The Spike, analyzed the pervasive impact of the extreme phase of technology acceleration anticipated within several decades.25 In an extensive series of writings, John Smart has described the Singularity as the inevitable result of what he calls "MEST" (matter, energy, space, and time) compression.26 From my perspective, the Singularity has many faces.


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Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

agricultural Revolution, AI winter, Albert Einstein, algorithmic trading, anthropic principle, Anthropocene, anti-communist, artificial general intelligence, autism spectrum disorder, autonomous vehicles, backpropagation, barriers to entry, Bayesian statistics, bioinformatics, brain emulation, cloud computing, combinatorial explosion, computer vision, Computing Machinery and Intelligence, cosmological constant, dark matter, DARPA: Urban Challenge, data acquisition, delayed gratification, Demis Hassabis, demographic transition, different worldview, Donald Knuth, Douglas Hofstadter, driverless car, Drosophila, Elon Musk, en.wikipedia.org, endogenous growth, epigenetics, fear of failure, Flash crash, Flynn Effect, friendly AI, general purpose technology, Geoffrey Hinton, Gödel, Escher, Bach, hallucination problem, Hans Moravec, income inequality, industrial robot, informal economy, information retrieval, interchangeable parts, iterative process, job automation, John Markoff, John von Neumann, knowledge worker, Large Hadron Collider, longitudinal study, machine translation, megaproject, Menlo Park, meta-analysis, mutually assured destruction, Nash equilibrium, Netflix Prize, new economy, Nick Bostrom, Norbert Wiener, NP-complete, nuclear winter, operational security, optical character recognition, paperclip maximiser, pattern recognition, performance metric, phenotype, prediction markets, price stability, principal–agent problem, race to the bottom, random walk, Ray Kurzweil, recommendation engine, reversible computing, search costs, social graph, speech recognition, Stanislav Petrov, statistical model, stem cell, Stephen Hawking, Strategic Defense Initiative, strong AI, superintelligent machines, supervolcano, synthetic biology, technological singularity, technoutopianism, The Coming Technological Singularity, The Nature of the Firm, Thomas Kuhn: the structure of scientific revolutions, time dilation, Tragedy of the Commons, transaction costs, trolley problem, Turing machine, Vernor Vinge, WarGames: Global Thermonuclear War, Watson beat the top human players on Jeopardy!, World Values Survey, zero-sum game

In particular, cognitive enhancement could accelerate science and technology, including progress toward more potent forms of biological intelligence amplification and machine intelligence. Consider how the rate of progress in the field of artificial intelligence would change in a world where Average Joe is an intellectual peer of Alan Turing or John von Neumann, and where millions of people tower far above any intellectual giant of the past.63 A discussion of the strategic implications of cognitive enhancement will have to await a later chapter. But we can summarize this section by noting three conclusions: (1) at least weak forms of superintelligence are achievable by means of biotechnological enhancements; (2) the feasibility of cognitively enhanced humans adds to the plausibility that advanced forms of machine intelligence are feasible—because even if we were fundamentally unable to create machine intelligence (which there is no reason to suppose), machine intelligence might still be within reach of cognitively enhanced humans; and (3) when we consider scenarios stretching significantly into the second half of this century and beyond, we must take into account the probable emergence of a generation of genetically enhanced populations—voters, inventors, scientists—with the magnitude of enhancement escalating rapidly over subsequent decades.

Both of these approaches were proposed at the time. The hardline approach of launching or threatening a first strike was advocated by some prominent intellectuals such as Bertrand Russell (who had long been active in anti-war movements and who would later spend decades campaigning against nuclear weapons) and John von Neumann (co-creator of game theory and one of the architects of US nuclear strategy).34 Perhaps it is a sign of civilizational progress that the very idea of threatening a nuclear first strike today seems borderline silly or morally obscene. A version of the benign approach was tried in 1946 by the United States in the form of the Baruch plan.

Still, it is impressive that an amount of economic growth that took 200 years seven thousand years ago takes just ninety minutes now, and that the world population growth that took two centuries then takes one and a half weeks now. See also Maddison (2005). 2. Such dramatic growth and acceleration might suggest one notion of a possible coming “singularity,” as adumbrated by John von Neumann in a conversation with the mathematician Stanislaw Ulam: Our conversation centred on the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.


The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do by Erik J. Larson

AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Alignment Problem, AlphaGo, Amazon Mechanical Turk, artificial general intelligence, autonomous vehicles, Big Tech, Black Swan, Bletchley Park, Boeing 737 MAX, business intelligence, Charles Babbage, Claude Shannon: information theory, Computing Machinery and Intelligence, conceptual framework, correlation does not imply causation, data science, deep learning, DeepMind, driverless car, Elon Musk, Ernest Rutherford, Filter Bubble, Geoffrey Hinton, Georg Cantor, Higgs boson, hive mind, ImageNet competition, information retrieval, invention of the printing press, invention of the wheel, Isaac Newton, Jaron Lanier, Jeff Hawkins, John von Neumann, Kevin Kelly, Large Hadron Collider, Law of Accelerating Returns, Lewis Mumford, Loebner Prize, machine readable, machine translation, Nate Silver, natural language processing, Nick Bostrom, Norbert Wiener, PageRank, PalmPilot, paperclip maximiser, pattern recognition, Peter Thiel, public intellectual, Ray Kurzweil, retrograde motion, self-driving car, semantic web, Silicon Valley, social intelligence, speech recognition, statistical model, Stephen Hawking, superintelligent machines, tacit knowledge, technological singularity, TED Talk, The Coming Technological Singularity, the long tail, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, theory of mind, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, Yochai Benkler

Turing, for instance, disliked viewing thinking or intelligence as something social or situational.8 Yet the Bletchley success was in fact part of a vast system that extended far outside its cloistered walls. A massive effort was underway. It would soon pull in the United States and the work of scientists like Shannon at Bell Labs, as well as scientists at Prince­ton’s celebrated Institute for Advanced Studies—­where Einstein, Gödel, and John Von Neumann all had appointments. The expanded, human-­machine T uring at B letchley 27 system is actually much more realistic as a model of how a­ ctual real-­ world prob­lems get solved—of which, world war must certainly count among the most complex and impor­tant. AI’s tone-­deafness on social or situational intelligence has been noted before, more recently by machine learning scientist François Chollet, who summarizes his critique of Turing’s (and, more broadly, the AI field's) view of intelligence nicely.

One major prob­lem with assumptions about increases in intelligence in AI circles is the prob­lem of circularity: it takes (seemingly general) intelligence to increase general intelligence. A closer look reveals no linear progression, but only mystery. VON N EU M A N N A N D S E L F -­R E P R O D U C I N G M A C H I N E S Good introduced the idea of self-­improving AIs leading to ultraintelligence in the mid-1960s, but nearly two de­cades ­earlier John Von Neumann had considered the idea and rejected it. In a 1948 talk at the Institute for Advanced Studies at Prince­ton, Von Neumann explained that, while ­human reproduction often improves on prior “designs,” it’s clear that machines tasked with designing new and better machines face a fundamental stumbling block, since any design for a new machine must be specified in the parent machine.

The idea of superintelligence is in real­ity a multiplication of errors, and it represents in barest form the extension of the fantasy about the rise of AI. To dig deeper into all of this, we should push further into this fantasy. It’s called the Singularity, and we turn to it next. Chapter 4 • • • T H E S I N G U L A R I T Y, T H EN A N D NOW In the 1950s, the mathematician Stanislaw Ulam recalled an old conversation with John Von Neumann, in which Von Neumann discussed the possibility of a technological turning point for humanity: “the ever accelerating pro­g ress of technology . . . ​g ives the appearance of approaching some essential singularity in the history of the race beyond which h­ uman affairs, as we know them, could not continue.”1 Von Neumann likely made this comment as digital computers ­were arriving on the technological scene.


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How We Got Here: A Slightly Irreverent History of Technology and Markets by Andy Kessler

Albert Einstein, Andy Kessler, animal electricity, automated trading system, bank run, Big bang: deregulation of the City of London, Black Monday: stock market crash in 1987, Bletchley Park, Bob Noyce, Bretton Woods, British Empire, buttonwood tree, Charles Babbage, Claude Shannon: information theory, Corn Laws, cotton gin, Dennis Ritchie, Douglas Engelbart, Edward Lloyd's coffeehouse, Fairchild Semiconductor, fiat currency, fixed income, floating exchange rates, flying shuttle, Fractional reserve banking, full employment, GPS: selective availability, Grace Hopper, invention of the steam engine, invention of the telephone, invisible hand, Isaac Newton, Jacquard loom, James Hargreaves, James Watt: steam engine, John von Neumann, joint-stock company, joint-stock limited liability company, Joseph-Marie Jacquard, Ken Thompson, Kickstarter, Leonard Kleinrock, Marc Andreessen, Mary Meeker, Maui Hawaii, Menlo Park, Metcalfe's law, Metcalfe’s law, military-industrial complex, Mitch Kapor, Multics, packet switching, pneumatic tube, price mechanism, probability theory / Blaise Pascal / Pierre de Fermat, profit motive, proprietary trading, railway mania, RAND corporation, Robert Metcalfe, Silicon Valley, Small Order Execution System, South Sea Bubble, spice trade, spinning jenny, Steve Jobs, Suez canal 1869, supply-chain management, supply-chain management software, systems thinking, three-martini lunch, trade route, transatlantic slave trade, tulip mania, Turing machine, Turing test, undersea cable, UUNET, Wayback Machine, William Shockley: the traitorous eight

The need for precision weapons would both directly and indirectly launch the digital revolution: Transistors in 1948, lasers and integrated circuits in 1958, packet switching in 1964 and microprocessors in 1970, and that was just the easy stuff. Using Edison effect tubes and relays and other forms of logic and memory, scientists and engineers invented electronic computers to help win World War II. John von Neumann at the Moore School at the University of Pennsylvania designed the ENIAC digital computer, the birth mother of the U.S. computer industry, to speed up calculations for artillery firing tables for Navy guns. At the same time, Alan Turing and the British at Bletchley Park designed the Colossus computer to decipher Enigma codes.

It also might take hours or even several days to change the algorithm or program that the ENIAC 116 HOW WE GOT HERE worked on. It had very little internal memory. Of course, the biggest problem with the ENIAC was that it was still a decimal machine working with 10 digits instead of the two of Boolean binary math. That increased its complexity, probably 100-fold. One of the folks working on ENIAC was John von Neumann, who had come over in June 1944 from Princeton’s Institute of Advanced Study, where Turing had studied. Von Neumann reengineered the ENIAC to store the algorithm/program inside it along with the data to be processed, and also added a “conditional control transfer.” For memory, von Neumann noticed that mercury delay lines, used in radar systems to store aircraft location information, stored a pulse or wave in a vial of slow moving mercury.

. *** The need for precision weapons would both directly and indirectly launch the digital revolution: transistors in 1948, lasers and integrated circuits in 1958, packet switching in 1964 and microprocessors in 1970, and that was just the easy stuff. Computers were invented to help win World War II. John von Neumann and the Moore School at the University of Pennsylvania designed the ENIAC digital computer, the birth mother of the U.S. computer industry, to speed up calculations for artillery firing tables for Navy guns. At the same time, Alan Turing and the British at Bletchley Park designed the Colossus computer to decipher Enigma codes.


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The Scientist as Rebel by Freeman Dyson

"World Economic Forum" Davos, Albert Einstein, Asilomar, Boeing 747, British Empire, Claude Shannon: information theory, dark matter, double helix, Edmond Halley, Ernest Rutherford, experimental subject, Fellow of the Royal Society, From Mathematics to the Technologies of Life and Death, Gregor Mendel, Henri Poincaré, Isaac Newton, Johannes Kepler, John von Neumann, kremlinology, Mikhail Gorbachev, military-industrial complex, Norbert Wiener, Paul Erdős, Plato's cave, precautionary principle, quantum entanglement, Recombinant DNA, Richard Feynman, Ronald Reagan, seminal paper, Silicon Valley, Stephen Hawking, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, undersea cable

The day after his arrival, he died suddenly of a pulmonary embolism on the steps of the Royal Institute of Technology in Stockholm. Dark Hero of the Information Age5 is the third biography of Norbert Wiener, unless there are others of which I am ignorant. First came a joint biography of Wiener and the mathematician John von Neumann, John von Neumann and Norbert Wiener: From Mathematics to the Technologies of Life and Death, by Steve Heims in 1980.6 Then came Norbert Wiener, 1894–1964, by Pesi Masani in 1990.7 The main justification for a new biography is that the three biographies emphasize different aspects of Wiener’s life and character.

But here too, even when Teller is most heavily engaged in political battles, he portrays his opponents as human beings and describes their concerns fairly. There is sadness in his account but no bitterness. The greatest sadness is the personal sadness, when three of his close friends and allies, Enrico Fermi, John von Neumann, and Ernest Lawrence, die untimely deaths before their work is done. Throughout his struggles he maintains his talent for friendship. Szilard, who disagreed violently with Teller about almost everything, remained one of his closest friends. The worst period of Teller’s life began in 1954 when he testified against J.

In parallel with our exploitation of biological engineering, we may achieve an equally profound industrial revolution by following the alternative route of self-reproducing machinery. Self-reproducing machines are devices which have the multiplying and self-organizing capabilities of living organisms but are built of metal and computers instead of protoplasm and brains. It was the mathematician John von Neumann who first demonstrated that self-reproducing machines are theoretically possible and sketched the logical principles underlying their construction. The basic components of a self-reproducing machine are precisely analogous to those of a living cell. The separation of function between genetic material (DNA) and enzymatic machinery (protein) in a cell corresponds exactly to the separation between software (computer programs) and hardware (machine tools) in a self-reproducing machine.


The Deep Learning Revolution (The MIT Press) by Terrence J. Sejnowski

AI winter, Albert Einstein, algorithmic bias, algorithmic trading, AlphaGo, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, autonomous vehicles, backpropagation, Baxter: Rethink Robotics, behavioural economics, bioinformatics, cellular automata, Claude Shannon: information theory, cloud computing, complexity theory, computer vision, conceptual framework, constrained optimization, Conway's Game of Life, correlation does not imply causation, crowdsourcing, Danny Hillis, data science, deep learning, DeepMind, delayed gratification, Demis Hassabis, Dennis Ritchie, discovery of DNA, Donald Trump, Douglas Engelbart, driverless car, Drosophila, Elon Musk, en.wikipedia.org, epigenetics, Flynn Effect, Frank Gehry, future of work, Geoffrey Hinton, Google Glasses, Google X / Alphabet X, Guggenheim Bilbao, Gödel, Escher, Bach, haute couture, Henri Poincaré, I think there is a world market for maybe five computers, industrial robot, informal economy, Internet of things, Isaac Newton, Jim Simons, John Conway, John Markoff, John von Neumann, language acquisition, Large Hadron Collider, machine readable, Mark Zuckerberg, Minecraft, natural language processing, Neil Armstrong, Netflix Prize, Norbert Wiener, OpenAI, orbital mechanics / astrodynamics, PageRank, pattern recognition, pneumatic tube, prediction markets, randomized controlled trial, Recombinant DNA, recommendation engine, Renaissance Technologies, Rodney Brooks, self-driving car, Silicon Valley, Silicon Valley startup, Socratic dialogue, speech recognition, statistical model, Stephen Hawking, Stuart Kauffman, theory of mind, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, Turing machine, Von Neumann architecture, Watson beat the top human players on Jeopardy!, world market for maybe five computers, X Prize, Yogi Berra

The world of law is well on its way to becoming “Legally Deep.”25 Learning How to Play Poker Heads-up no-limit Texas hold ’em is one of the most popular versions of poker, commonly played in casinos, and the no-limit betting form is played at the main event of the World Series of Poker (figure 1.7). Poker is challenging because, unlike chess, where both players have access to the same information, poker players have imperfect information, and, at the highest levels of play, skills in bluffing and deception are as important as the cards that are dealt. The mathematician John von Neumann, who founded mathematical game theory and pioneered digital computers, was particularly fascinated with poker. As he put it: “Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do. And that is what games are about in my theory.”26 Poker is a game that reflects parts of human intelligence that were refined by evolution.

Cellular automata typically have only a few discrete values that evolve in time, depending on the states of the other cells. One of the simplest cellular automata is a one-dimensional array of cells, each with value of 0 or 1 (box 13.1). Perhaps the most famous cellular automaton is called the “Game of Life,” which was invented by John Conway, the John von Neumann professor of mathematics at Princeton, in 1968, popularized by Martin Gardner in his “Mathematical Games” column in Scientific American, and is illustrated in figure 13.2. The board is a two-dimensional array of cells that can only be “on” or “off” and the update rule only depends on the four nearest neighbors.

In 1943, Warren McCulloch and Walter Pitts showed that it was possible to build a digital computer out of simple binary threshold units like the perceptron, which could be wired up to make the elementary logical gates in a computer.11 We now know that brains have mixed analog and digital properties and that their neural circuits generally do not compute logical functions. But McCulloch and Pitts’s 1943 paper received a lot of attention at the time and, in particular, inspired John von Neumann to think about computers. He built one of the first digital computers that had stored programs, an unusual project for a mathematician at that time, although when von Neumann died in 1957, the Institute for Advanced Study did not continue his line of research and scrapped his computer.12 Von Neumann also was interested in the brain.


Smart Mobs: The Next Social Revolution by Howard Rheingold

"hyperreality Baudrillard"~20 OR "Baudrillard hyperreality", A Pattern Language, Alvin Toffler, AOL-Time Warner, augmented reality, barriers to entry, battle of ideas, Brewster Kahle, Burning Man, business climate, citizen journalism, computer vision, conceptual framework, creative destruction, Dennis Ritchie, digital divide, disinformation, Douglas Engelbart, Douglas Engelbart, experimental economics, experimental subject, Extropian, Free Software Foundation, Garrett Hardin, Hacker Ethic, Hedy Lamarr / George Antheil, Herman Kahn, history of Unix, hockey-stick growth, Howard Rheingold, invention of the telephone, inventory management, Ivan Sutherland, John Markoff, John von Neumann, Joi Ito, Joseph Schumpeter, Ken Thompson, Kevin Kelly, Lewis Mumford, Metcalfe's law, Metcalfe’s law, more computing power than Apollo, move 37, Multics, New Urbanism, Norbert Wiener, packet switching, PalmPilot, Panopticon Jeremy Bentham, pattern recognition, peer-to-peer, peer-to-peer model, pez dispenser, planetary scale, pre–internet, prisoner's dilemma, radical decentralization, RAND corporation, recommendation engine, Renaissance Technologies, RFID, Richard Stallman, Robert Metcalfe, Robert X Cringely, Ronald Coase, Search for Extraterrestrial Intelligence, seminal paper, SETI@home, sharing economy, Silicon Valley, skunkworks, slashdot, social intelligence, spectrum auction, Steven Levy, Stewart Brand, the Cathedral and the Bazaar, the scientific method, Tragedy of the Commons, transaction costs, ultimatum game, urban planning, web of trust, Whole Earth Review, Yochai Benkler, zero-sum game

Those “covenants” mentioned by Hobbes turn out to be tricky because humans play elaborate games of trust and deception. Economists have long sought the mathematical grail that could predict the behavior of markets. In 1944, John von Neumann and Oskar Morgenstern’s Theory of Games and Economic Behavior provided, if not a grail, a means of looking at the way people compete and collude, cooperate and defect, in competitive situations.28 John von Neumann was arguably the most influential but least-famous scientist in history, considering his fundamental contributions to mathematics, quantum physics, game theory, and the development of the atomic bomb, digital computer, and intercontinental ballistic missile.29 Von Neumann was a prodigy who joked with his father in classical Latin and Greek at the age of six, was a colleague of Einstein at Princeton’s Institute for Advanced Study, and was perhaps the most brilliant of the stellar collection of scientists gathered at Los Alamos to undertake the Manhattan Project.

Hamilton, “The Genetical Evolution of Social Behavior,” Journal of Theoretical Biology 7 (1964): 152. 26. Richard Dawkins, The Selfish Gene (Oxford: Oxford University Press, 1976). 27. Hobbes, Leviathan, 95. 28. John von Neumann and Oskar Morgenstern, Theory of Games and Economic Behavior (Princeton: Princeton University Press, 1944). 29. William Poundstone, Prisoner’s Dilemma: John von Neumann, Game Theory, and the Puzzle of the Bomb (New York: Doubleday, 1992). 30. J. Bronowski, The Ascent of Man (Toronto: Little, Brown, 1973). 31. Herman Kahn, On Thermonuclear War (Princeton: Princeton University Press, 1960). 32.


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Life's Greatest Secret: The Race to Crack the Genetic Code by Matthew Cobb

a long time ago in a galaxy far, far away, Anthropocene, anti-communist, Asilomar, Asilomar Conference on Recombinant DNA, Benoit Mandelbrot, Berlin Wall, bioinformatics, Claude Shannon: information theory, conceptual framework, Copley Medal, CRISPR, dark matter, discovery of DNA, double helix, Drosophila, epigenetics, factory automation, From Mathematics to the Technologies of Life and Death, Gregor Mendel, heat death of the universe, James Watt: steam engine, John von Neumann, Kickstarter, Large Hadron Collider, military-industrial complex, New Journalism, Norbert Wiener, phenotype, post-materialism, Recombinant DNA, Stephen Hawking, synthetic biology

If the demon and the chamber were taken as a whole, the entropy of the system would not decline, and the second law remained intact. Although Szilárd did not use the term information, his theoretical discussion linked entropy and measures of knowledge in a way that proved significant. * At the beginning of 1945, Wiener and fellow mathematician John von Neumann organised a meeting of the newly formed Teleological Society. The aim of the society was to study ‘how purpose is realised in human and animal conduct and on the other hand how purpose can be imitated by mechanical and electrical means.’21 Von Neumann was a mathematician and a pioneer of game theory – mathematical models that describe and predict simple behaviours.

The backdrop to the developments in cybernetics, and indeed the source of much of its funding, was the Cold War. In February 1949, the US lost its monopoly on nuclear weapons when the USSR exploded its first atom bomb. In 1950, the Cold War began to heat up as the Korean War broke out and the US fought a proxy war against the Russians and the Chinese. Shocked by these developments, the anti-communist John von Neumann pressed the US government to focus all its research effort on building a hydrogen bomb. Thanks in part to his lobbying, a major development programme began in which he was heavily involved, leaving little time for his other interests. The project culminated in the explosion of the first H-bomb in November 1952, with a yield that was nearly 1,000 times more destructive than that of Hiroshima.

., ‘Alphonse Raymond Dochez, 1882–1964’, Biographical Memoir, Washington DC, National Academy of Sciences, 1971. Heijmans, B. T., Tobi, E. W., Stein, A. D. et al., ‘Persistent epigenetic differences associated with prenatal exposure to famine in humans’, Proceedings of the National Academy of Sciences USA, vol. 105, 2008, pp. 17046–9. Heims, S. J., John von Neumann & Norbert Weiner: From Mathematics to the Technologies of Life and Death, London, MIT Press, 1980. Heims, S. J., The Cybernetics Group, London, MIT Press, 1991. Henikoff, S., Keene, M. A., Fechtel, K. and Fristrom, J. W., ‘Gene within a gene: nested Drosophila genes encode unrelated proteins on opposite DNA strands’, Cell, vol. 44, 1986, pp. 33–42.


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The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory by Kariappa Bheemaiah

"World Economic Forum" Davos, accounting loophole / creative accounting, Ada Lovelace, Adam Curtis, Airbnb, Alan Greenspan, algorithmic trading, asset allocation, autonomous vehicles, balance sheet recession, bank run, banks create money, Basel III, basic income, behavioural economics, Ben Bernanke: helicopter money, bitcoin, Bletchley Park, blockchain, Bretton Woods, Brexit referendum, business cycle, business process, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, cashless society, cellular automata, central bank independence, Charles Babbage, Claude Shannon: information theory, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, complexity theory, constrained optimization, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cross-border payments, crowdsourcing, cryptocurrency, data science, David Graeber, deep learning, deskilling, Diane Coyle, discrete time, disruptive innovation, distributed ledger, diversification, double entry bookkeeping, Ethereum, ethereum blockchain, fiat currency, financial engineering, financial innovation, financial intermediation, Flash crash, floating exchange rates, Fractional reserve banking, full employment, George Akerlof, Glass-Steagall Act, Higgs boson, illegal immigration, income inequality, income per capita, inflation targeting, information asymmetry, interest rate derivative, inventory management, invisible hand, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Joseph Schumpeter, junk bonds, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, knowledge economy, large denomination, Large Hadron Collider, Lewis Mumford, liquidity trap, London Whale, low interest rates, low skilled workers, M-Pesa, machine readable, Marc Andreessen, market bubble, market fundamentalism, Mexican peso crisis / tequila crisis, Michael Milken, MITM: man-in-the-middle, Money creation, money market fund, money: store of value / unit of account / medium of exchange, mortgage debt, natural language processing, Network effects, new economy, Nikolai Kondratiev, offshore financial centre, packet switching, Pareto efficiency, pattern recognition, peer-to-peer lending, Ponzi scheme, power law, precariat, pre–internet, price mechanism, price stability, private sector deleveraging, profit maximization, QR code, quantitative easing, quantitative trading / quantitative finance, Ray Kurzweil, Real Time Gross Settlement, rent control, rent-seeking, robo advisor, Satoshi Nakamoto, Satyajit Das, Savings and loan crisis, savings glut, seigniorage, seminal paper, Silicon Valley, Skype, smart contracts, software as a service, software is eating the world, speech recognition, statistical model, Stephen Hawking, Stuart Kauffman, supply-chain management, technology bubble, The Chicago School, The Future of Employment, The Great Moderation, the market place, The Nature of the Firm, the payments system, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, too big to fail, trade liberalization, transaction costs, Turing machine, Turing test, universal basic income, Vitalik Buterin, Von Neumann architecture, Washington Consensus

To combat this, pioneers such as Alan Turing and his mentor Max Newman, set about designing and building automated machines (Turing Machines) that could decrypt these camouflaged communiqués. This effectively changed the use of the computer and increased the diversity of the kinds of computers. After the war, advances by notable inventors such as John Mauchly, Presper Eckert and John von Neumann (a veritable polymath) led to the creation of the EDVAC (Electronic Discrete Variable Automatic Computer) , the first binary computer. With binary computers coming of age, there was an increasing need to develop software to give instructions to computers. Punch cards were soon replaced by logic gates (from Boolean algebra) and languages such as COBOL and FORTRAN (FORmula TRANslation), helped in the creation of early operating systems.

The mapping of macroeconoic movements to the flow of fluids was representative that these thinkers looked at the economy as a subject of physical inquiry. Figure 4-5.Professor A.W.H (Bill) Phillips with the Phillips Machine (MONIAC) Source: The Phillips Machine Project’ by Nicholas Bar, LSE Magazine, June 1988, No 75. However, the introduction of mathematical game theory in the 1950s by John von Neumann, threw a monkey wrench into this link between economic and physics. When game theory was introduced (See ‘Theory of Games and Economic Behaviour’, von Neumann and Morgenstern), economics immediately realised that the maths of this field could be used to study the behaviour of selfish agents to get the better of other agents in an economy.

Mauchly, a physicist, who was interested in meteorology tried to develop a weather prediction model. But he soon realized that this would not be possible without some kind of automatic calculating machine. As a result, he developed the concept of an electronic computer using vacuum tubes. It was during the time of developing ENIAC that he met the renowned polymath, John von Neumann, and with his help went on to design a stored-program computer, the EDVAC (Electronic Discrete Variable Automatic Computer), the first binary computer (ENIAC was decimal). See Figure 4-11. Figure 4-11.General design of the Electronic Discrete Variable Automatic Computer. Reference Source: ‘The von Neumann Architecture’, The Computing Universe, 2014 From an abstract architecture perspective, von Neumann’s design is logically equivalent to Turing’s Universal Turing Machine.


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Chaos: Making a New Science by James Gleick

Benoit Mandelbrot, business cycle, butterfly effect, cellular automata, Claude Shannon: information theory, discrete time, Edward Lorenz: Chaos theory, experimental subject, Georg Cantor, Henri Poincaré, Herbert Marcuse, Isaac Newton, iterative process, John von Neumann, Louis Pasteur, mandelbrot fractal, military-industrial complex, Murray Gell-Mann, Norbert Wiener, pattern recognition, power law, Richard Feynman, scientific management, Stephen Hawking, stochastic process, trade route

Implicitly, the mission of many twentieth-century scientists—biologists, neurologists, economists—has been to break their universes down into the simplest atoms that will obey scientific rules. In all these sciences, a kind of Newtonian determinism has been brought to bear. The fathers of modern computing always had Laplace in mind, and the history of computing and the history of forecasting were intermingled ever since John von Neumann designed his first machines at the Institute for Advanced Study in Princeton, New Jersey, in the 1950s. Von Neumann recognized that weather modeling could be an ideal task for a computer. There was always one small compromise, so small that working scientists usually forgot it was there, lurking in a corner of their philosophies like an unpaid bill.

Inner Rhythms The sciences do not try to explain, they hardly even try to interpret, they mainly make models. By a model is meant a mathematical construct which, with the addition of certain verbal interpretations, describes observed phenomena. The justification of such a mathematical construct is solely and precisely that it is expected to work. —JOHN VON NEUMANN BERNARDO HUBERMAN LOOKED OUT over his audience of assorted theoretical and experimental biologists, pure mathematicians and physicians and psychiatrists, and he realized that he had a communication problem. He had just finished an unusual talk at an unusual gathering in 1986, the first major conference on chaos in biology and medicine, under the various auspices of the New York Academy of Sciences, the National Institute of Mental Health, and the Office of Naval Research.

Press, 1981), 3:371. Wiener anticipated Lorenz in seeing at least the possibility of “self-amplitude of small details of the weather map.” He noted, “A tornado is a highly local phenomenon, and apparent trifles of no great extent may determine its exact track.” “THE CHARACTER OF THE EQUATION” John von Neumann, “Recent Theories of Turbulence” (1949), in Collected Works, ed. A. H. Taub (Oxford: Pergamon Press, 1963), 6:437. CUP OF HOT COFFEE “The predictability of hydrodynamic flow,” in Transactions of the New York Academy of Sciences II:25:4 (1963), pp. 409–32. “WE MIGHT HAVE TROUBLE” Ibid., p. 410.


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Beyond Weird by Philip Ball

Albert Einstein, Bayesian statistics, cosmic microwave background, dark matter, dark pattern, dematerialisation, Ernest Rutherford, experimental subject, Higgs boson, Isaac Newton, John von Neumann, Kickstarter, Large Hadron Collider, Murray Gell-Mann, quantum cryptography, quantum entanglement, Richard Feynman, Schrödinger's Cat, Stephen Hawking, theory of mind, Thomas Bayes

How the founders puzzled, argued, improvised, guessed, in their efforts to come up with a theory to explain it all. How knowledge once deemed precise and objective now seemed uncertain, contingent and observer-dependent. And the cast! Albert Einstein, Niels Bohr, Werner Heisenberg, Erwin Schrödinger, and other colourful intellectual giants like John von Neumann, Richard Feynman and John Wheeler. Best of all for its narrative value is the largely good-natured but trenchant dispute that rumbled on for decades between Einstein and Bohr about what it all meant – about the nature of reality. This is indeed a superb story, and if you haven’t heard it before then you should.fn1 Yet most popular descriptions of quantum theory have been too wedded to its historical evolution.

We don’t ban some questions simply because we don’t know what to say about them, but instead recognize that quantum mechanics has no maths that can provide an answer: it’s rather like expecting simple arithmetic to tell us what an apple tastes like. In that much, Consistent Histories offers a valuable tool. But it stops short of supplying a physical picture that improves on other interpretations – which is why it is not exactly inconsistent with some of them. The Hungarian mathematical physicist John von Neumann was one of the first to make wavefunction collapse an ‘official’ component of quantum mechanics, incorporating it into his 1932 textbook on the subject. He pointed out that the collapse happens through the intervention of an observer, and so figured that it must have something to do with the act of observation itself.

Many of the pioneers of quantum computing are the same folk who think most profoundly about what quantum mechanics means. Had these machines and related quantum information technologies been invented sooner – and really there is no clear reason why they should not have been – we can be sure that the likes of Bohr, Einstein, John von Neumann and John Wheeler would have had plenty to say about them. After all, one of those quantum pioneers is credited with the initial concept. In 1982 Richard Feynman wondered about the best way of ‘simulating physics with computers’. Computer simulation is now a mature discipline: a way of predicting how things behave by representing them as a kind of computer model governed by physical laws, and letting the laws unfold to see what emerges.


pages: 561 words: 120,899

The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant From Two Centuries of Controversy by Sharon Bertsch McGrayne

Abraham Wald, Alan Greenspan, Bayesian statistics, bioinformatics, Bletchley Park, British Empire, classic study, Claude Shannon: information theory, Daniel Kahneman / Amos Tversky, data science, double helix, Dr. Strangelove, driverless car, Edmond Halley, Fellow of the Royal Society, full text search, government statistician, Henri Poincaré, Higgs boson, industrial research laboratory, Isaac Newton, Johannes Kepler, John Markoff, John Nash: game theory, John von Neumann, linear programming, longitudinal study, machine readable, machine translation, meta-analysis, Nate Silver, p-value, Pierre-Simon Laplace, placebo effect, prediction markets, RAND corporation, recommendation engine, Renaissance Technologies, Richard Feynman, Richard Feynman: Challenger O-ring, Robert Mercer, Ronald Reagan, seminal paper, speech recognition, statistical model, stochastic process, Suez canal 1869, Teledyne, the long tail, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, Turing machine, Turing test, uranium enrichment, We are all Keynesians now, Yom Kippur War

Turing was given an Order of the British Empire (OBE), a routine award given to high civil servants. Newman was so angry at the government’s “derisory” lack of gratitude to Turing that he refused his own OBE. Britain’s science, technology, and economy were losers, too. The Colossi were built and operational years before the ENIAC in Pennsylvania and before John von Neumann’s computer at the Institute for Advance Study in Princeton, but for the next half century the world assumed that U.S. computers had come first. Obliterating all information about the decryption campaign distorted Cold War attitudes about the value of cryptanalysis and about antisubmarine warfare.

In that 80% of aircraft crashes occurred within 3 miles of an air force base, the likelihood of public exposure was growing. And so it went. None of these studies involved a nuclear explosion, but to a Bayesian they suggested ominous possibilities. Computationally, Madansky was confident that RAND’s two powerful computers, a 700 series IBM and the Johnniac, designed by and named for John von Neumann, could handle the job. But he hoped to avoid using them by solving the problem with pencil and paper. Given the power and availability of computers in the 1950s, many Bayesians were searching for ways to make calculations manageable. Madansky latched onto the fact that many types of priors and posteriors share the same probability curves.

“In the year I studied statistics, I don’t think I heard the word ‘Bayes.’ As a way of inference, it was nonexistent. It was all strictly Neyman-Pearson, classical, objectivistic (frequency-based) statistics.”10 Although Schlaifer had embraced Bayes in one fell swoop, Raiffa inched grudgingly toward its subjectivity. But reading John von Neumann and Oskar Morgenstern’s book Game Theory (1944), he instinctively assessed how others would play in order to determine how he himself should compete: “In my naiveté, without any theory or anything like that. . . . [I began] assessing judgmental probability distributions. I slipped into being a subjectivist without realizing how radically I was behaving.


pages: 795 words: 215,529

Genius: The Life and Science of Richard Feynman by James Gleick

Albert Einstein, American ideology, Arthur Eddington, Brownian motion, Charles Babbage, disinformation, double helix, Douglas Hofstadter, Dr. Strangelove, Eddington experiment, Ernest Rutherford, gravity well, Gödel, Escher, Bach, Higgs boson, Isaac Newton, John von Neumann, Menlo Park, military-industrial complex, Murray Gell-Mann, mutually assured destruction, Neil Armstrong, Norbert Wiener, Norman Mailer, pattern recognition, Pepto Bismol, Richard Feynman, Richard Feynman: Challenger O-ring, Ronald Reagan, Rubik’s Cube, Sand Hill Road, Schrödinger's Cat, sexual politics, sparse data, Stephen Hawking, Steven Levy, the scientific method, Thomas Kuhn: the structure of scientific revolutions, uranium enrichment

He was nervous about it. As the day approached, Wigner, who ran the colloquiums, stopped Feynman in the hall. Wigner said he had heard enough from Wheeler about the absorber theory to think it was important. Because of its implications for cosmology he had invited the great astrophysicist Henry Norris Russell. John von Neumann, the mathematician, was also going to come. The formidable Wolfgang Pauli happened to be visiting from Zurich; he would be there. And though Albert Einstein rarely bestirred himself to the colloquiums, he had expressed interest in attending this one. Wheeler tried to calm Feynman by promising to field questions from the audience.

Computing by Brain Walking around the hastily built wooden barracks that housed the soul of the atomic bomb project in 1943 and 1944, a scientist would see dozens of men laboring over computation. Everyone calculated. The theoretical department was home to some of the world’s masters of mental arithmetic, a martial art shortly to go the way of jiujitsu. Any morning might find men such as Bethe, Fermi, and John von Neumann together in a single small room where they would spit out numbers in a rapid-fire calculation of pressure waves. Bethe’s deputy, Weisskopf, specialized in a particularly oracular sort of guesswork; his office became known as the Cave of the Hot Winds, producing, on demand, unjustifiably accurate cross sections (shorthand for the characteristic probabilities of particle collisions in various substances and circumstances).

Such questions required a workable formula for the propagation of a spherical detonation wave in a compressible fluid, the “compressible fluid” in this case being the shotput-size piece of plutonium liquefied in the microseconds before it became a nuclear blast. The pressure would be more intense than at the earth’s center. The temperature would reach 50 million degrees Centigrade. The theorists were on their own here; experimentalists could offer little more than good wishes. All during 1944 the computation effort grew. John von Neumann served as a traveling consultant with an eye on the postwar future. Von Neumann—mathematician, logician, game theorist (he was more and more a fixture in the extraordinary Los Alamos poker game), and one of the fathers of modern computing—talked with Feynman while they worked on the IBM machines or walked though the canyons.


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The Simulation Hypothesis by Rizwan Virk

3D printing, Albert Einstein, AlphaGo, Apple II, artificial general intelligence, augmented reality, Benoit Mandelbrot, bioinformatics, butterfly effect, Colossal Cave Adventure, Computing Machinery and Intelligence, DeepMind, discovery of DNA, Dmitri Mendeleev, Elon Musk, en.wikipedia.org, Ernest Rutherford, game design, Google Glasses, Isaac Newton, John von Neumann, Kickstarter, mandelbrot fractal, Marc Andreessen, Minecraft, natural language processing, Nick Bostrom, OpenAI, Pierre-Simon Laplace, Plato's cave, quantum cryptography, quantum entanglement, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Schrödinger's Cat, Search for Extraterrestrial Intelligence, Silicon Valley, Stephen Hawking, Steve Jobs, Steve Wozniak, technological singularity, TED Talk, time dilation, Turing test, Vernor Vinge, Zeno's paradox

It was then adopted by physicists as a more technical term for black holes—again using the idea of approaching infinity, in this case infinite gravity. More recently, the term has entered popular usage around the idea of artificial intelligence reaching, or even exceeding, human intelligence, resulting in an “intelligence explosion.” The origins of this use of the term singularity date back to the 1950s, at which time mathematician John von Neumann supposedly coined the term when he said, “The ever-accelerating progress of technology ... gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.”17 Irving John Good, another mathematician, was one of the first to call super-intelligent AI the “last invention that man need make.”

This means that the observer, who is a conscious entity, is participating in the outcome of the results of physical phenomena, at least at the subatomic level. This led to an uncomfortable idea for many scientists that consciousness was somehow involved in the physical universe, an idea first proposed by famous mathematician John von Neumann in the 1930s and has been a source of debate ever since. There are other interpretations of the basic findings of quantum physics (we’ll look at one alternative interpretation, the many-worlds interpretation, in the next chapter), but the most prominent, called the Copenhagen interpretation, put forth by Max Born, Heisenberg, and Bohr, is consistent with this worldview: that probabilities are collapsed by observation.

Knowing that several particles (or qubits) are entangled, it’s possible to come up with error-correction code such that if one qubit flips unexpectedly, this can be found out and reversed. Without going too far into the computer science or the physics, if evidence for error-correcting codes is found in models of the universe, it becomes ever more likely that the universe is some kind of simulation running on a computer. Researchers from Einstein and John von Neumann’s research center, the Institute for Advanced Study in Princeton, New Jersey, Ahmed Almheiri, Xi Dong, and Daniel Harlow, have discovered that these quantum error-correction codes not only exist but, at least in their simulated worlds, the error codes may define the fabric of space-time itself.


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The End of Theory: Financial Crises, the Failure of Economics, and the Sweep of Human Interaction by Richard Bookstaber

asset allocation, bank run, Bear Stearns, behavioural economics, bitcoin, business cycle, butterfly effect, buy and hold, capital asset pricing model, cellular automata, collateralized debt obligation, conceptual framework, constrained optimization, Craig Reynolds: boids flock, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, dark matter, data science, disintermediation, Edward Lorenz: Chaos theory, epigenetics, feminist movement, financial engineering, financial innovation, fixed income, Flash crash, geopolitical risk, Henri Poincaré, impact investing, information asymmetry, invisible hand, Isaac Newton, John Conway, John Meriwether, John von Neumann, Joseph Schumpeter, Long Term Capital Management, margin call, market clearing, market microstructure, money market fund, Paul Samuelson, Pierre-Simon Laplace, Piper Alpha, Ponzi scheme, quantitative trading / quantitative finance, railway mania, Ralph Waldo Emerson, Richard Feynman, risk/return, Robert Solow, Saturday Night Live, self-driving car, seminal paper, sovereign wealth fund, the map is not the territory, The Predators' Ball, the scientific method, Thomas Kuhn: the structure of scientific revolutions, too big to fail, transaction costs, tulip mania, Turing machine, Turing test, yield curve

As the mathematician and economist Donald Saari puts it, “Economics so effortlessly offers the needed ingredients for chaos that, rather than being surprised about exotic dynamics, we should be suspicious about models which always are stable.”7 And just as it is for the three-body problem of astronomy, Saari notes that there are examples of three-person, three-commodity economies with permanently unstable price dynamics, showing that we cannot hope to prove the stability of general equilibrium in all cases.8 CALL ME IRREDUCIBLE: THE ROCKET MAN AND CONWAY’S GAME OF LIFE In the 1940s, the famed Princeton polymath John von Neumann developed an abstract template for self-replicating machines, which he called a universal constructor. He simulated it, not on a computer, but using the cells on a sheet of graph paper, where each cell could take on any of twenty-nine states. His universal constructor gave rise to the concept of a von Neumann probe, a spacecraft capable of replicating itself, which could land on one galactic outpost, build a hundred copies of itself, each traveling off in one of a hundred different directions, discover other worlds, and replicate again, thereby exploring the universe—and, depending on the design of the machines, conquering the universe—with exponential efficiency.

His universal constructor gave rise to the concept of a von Neumann probe, a spacecraft capable of replicating itself, which could land on one galactic outpost, build a hundred copies of itself, each traveling off in one of a hundred different directions, discover other worlds, and replicate again, thereby exploring the universe—and, depending on the design of the machines, conquering the universe—with exponential efficiency. The universal constructor caught the interest of John Conway, a British mathematician who would later hold the John von Neumann Chair of Mathematics at Princeton, and over “eighteen months of coffee times,” as he describes it, he began tinkering to simplify its set of rules. The result was what became known as Conway’s Game of Life.9 The “game” really isn’t one—it is a zero-player game, because once the initial conditions of the cells are set, there is no further interaction or input as the process evolves.

Others have called them explanatory inductions, theoretical inductions, or theoretical inferences. More recently, many philosophers have used the term inference to the best explanation (Harman 1965; Lipton 2004). Chapter 15: Conclusion 1. Lynch (2008) provides a history of the development of modern weather forecasting. John von Neumann, in addition to the roles I have already mentioned in developing game theory and conceptualizing replicating machines, and in addition to his foundational work in mathematics, physics, computer science, and economics, also was central in this effort. 2. This fits within an emerging interest among the socially minded in the financial community called impact investing, in which investments are made with an eye toward profits but also with an objective of social returns.


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The Golden Ticket: P, NP, and the Search for the Impossible by Lance Fortnow

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Andrew Wiles, Claude Shannon: information theory, cloud computing, complexity theory, Donald Knuth, Erdős number, four colour theorem, Gerolamo Cardano, Isaac Newton, James Webb Space Telescope, Johannes Kepler, John von Neumann, Large Hadron Collider, linear programming, new economy, NP-complete, Occam's razor, P = NP, Paul Erdős, quantum cryptography, quantum entanglement, Richard Feynman, Rubik’s Cube, seminal paper, smart grid, Stephen Hawking, traveling salesman, Turing machine, Turing test, Watson beat the top human players on Jeopardy!, William of Occam

P versus NP P versus NP is about all the problems described above and thousands more of a similar flavor: How fast can we search through a huge number of possibilities? How easily can we find that “golden ticket,” that one best answer? The P versus NP problem was first mentioned in a 1956 letter from Kurt Gödel to John von Neumann, two of the greatest mathematical minds of the twentieth century. That letter was unfortunately lost until the 1980s. The P versus NP problem was first publicly announced in the early 1970s by Steve Cook and Leonid Levin, working separately in countries on opposite sides of the Cold War. Richard Karp followed up with a list of twenty-one important problems that capture P versus NP, including the traveling salesman problem and the partition puzzle mentioned earlier.

Alexander Razborov, a Russian student, played a major role in the development of circuit complexity as an approach to proving P ≠ NP, a story we tell in chapter 7. After the collapse of the Soviet Union and the rise of the Internet, Russian mathematical researchers no longer worked in isolation. The world is now a truly global research environment. The Gödel Letter In 1956 Kurt Gödel wrote a letter to John von Neumann, one of the pioneers of computer science and many other fields. In this letter (written in German), Gödel talks about the satisfiability problem and formulates the P versus NP question in different terminology. He suggests that if we lived in a world where P = NP, “the mental work of a mathematician concerning Yes-or-No questions could be completely replaced by a machine. … Now it seems to me, however, to be completely within the realm of possibility.”


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Darwin's Dangerous Idea: Evolution and the Meanings of Life by Daniel C. Dennett

Albert Einstein, Alfred Russel Wallace, anthropic principle, assortative mating, buy low sell high, cellular automata, Charles Babbage, classic study, combinatorial explosion, complexity theory, computer age, Computing Machinery and Intelligence, conceptual framework, Conway's Game of Life, Danny Hillis, double helix, Douglas Hofstadter, Drosophila, finite state, Garrett Hardin, Gregor Mendel, Gödel, Escher, Bach, heat death of the universe, In Cold Blood by Truman Capote, invention of writing, Isaac Newton, Johann Wolfgang von Goethe, John von Neumann, junk bonds, language acquisition, Murray Gell-Mann, New Journalism, non-fiction novel, Peter Singer: altruism, phenotype, price mechanism, prisoner's dilemma, QWERTY keyboard, random walk, Recombinant DNA, Richard Feynman, Rodney Brooks, Schrödinger's Cat, selection bias, Stephen Hawking, Steven Pinker, strong AI, Stuart Kauffman, the scientific method, theory of mind, Thomas Malthus, Tragedy of the Commons, Turing machine, Turing test

If it exhibits peculiarities that could only have arisen in the course of solving the subproblems in some apparently remote branch of the Tree that grows in Design Space, then barring a miracle or a coincidence too Cosmic to credit, there must be a copying event of some kind that moved that completed design work to its new location. {134} There is no single summit in Design Space, nor a single staircase or ladder with calibrated steps, so we cannot expect to find a scale for comparing amounts of design work across distant developing branches. Thanks to the vagaries and digressions of different "methods adopted," something that is in some sense just one problem can have both hard and easy solutions, requiring more or less work. There is a famous story about the mathematician and physicist (and coinventor of the computer) John von Neumann, who was legendary for his lightning capacity to do prodigious calculations in his head. (Like most famous stories, this one has many versions, of which I choose the one that best makes the point I am pursuing.) One day a colleague approached him with a puzzle that had two paths to solution, a laborious, complicated calculation and an elegant, Aha!

What on Earth inspired Conway and his students to create first this world and then this amazing denizen of that world? They were trying to answer at a very abstract level one of the central questions we have been considering in this chapter: what is the minimal complexity required for a self-reproducing thing? They were following up the brilliant early speculations of John von Neumann, who had been working on the question at the time of his death {172} in 1957. Francis Crick and James Watson had discovered DNA in 1953, but how it worked was a mystery for many years. Von Neumann had imagined in some detail a sort of floating robot that picked up pieces of flotsam and jetsam that could be used to build a duplicate of itself that would then be able to repeat the process.

(See Mazlish 1993) It is a long and winding road from molecules to minds, with many diverting spectacles along the way — and we will tarry over the most interesting of these in subsequent chapters — but now is the time to look more closely than usual at the Darwinian beginnings of Artificial Intelligence. 5. THE COMPUTER THAT LEARNED TO PLAY CHECKERS Alan Turing and John von Neumann were two of the greatest scientists of the century. If anybody could be said to have invented the computer, they did, and their brainchild has come to be recognized as both a triumph of engineering and an intellectual vehicle for exploring the most abstract realms of pure science. Both thinkers were at one and the same time awesome theorists and deeply practical, epitomizing an intellectual style that has been playing a growing role in science since the Second World War.


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The Transhumanist Reader by Max More, Natasha Vita-More

"World Economic Forum" Davos, 23andMe, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, augmented reality, Bill Joy: nanobots, bioinformatics, brain emulation, Buckminster Fuller, cellular automata, clean water, cloud computing, cognitive bias, cognitive dissonance, combinatorial explosion, Computing Machinery and Intelligence, conceptual framework, Conway's Game of Life, cosmological principle, data acquisition, discovery of DNA, Douglas Engelbart, Drosophila, en.wikipedia.org, endogenous growth, experimental subject, Extropian, fault tolerance, Flynn Effect, Francis Fukuyama: the end of history, Frank Gehry, friendly AI, Future Shock, game design, germ theory of disease, Hans Moravec, hypertext link, impulse control, index fund, John von Neumann, joint-stock company, Kevin Kelly, Law of Accelerating Returns, life extension, lifelogging, Louis Pasteur, Menlo Park, meta-analysis, moral hazard, Network effects, Nick Bostrom, Norbert Wiener, pattern recognition, Pepto Bismol, phenotype, positional goods, power law, precautionary principle, prediction markets, presumed consent, Project Xanadu, public intellectual, radical life extension, Ray Kurzweil, reversible computing, RFID, Ronald Reagan, scientific worldview, silicon-based life, Singularitarianism, social intelligence, stem cell, stochastic process, superintelligent machines, supply-chain management, supply-chain management software, synthetic biology, systems thinking, technological determinism, technological singularity, Ted Nelson, telepresence, telepresence robot, telerobotics, the built environment, The Coming Technological Singularity, the scientific method, The Wisdom of Crowds, transaction costs, Turing machine, Turing test, Upton Sinclair, Vernor Vinge, Von Neumann architecture, VTOL, Whole Earth Review, women in the workforce, zero-sum game

In 1970, Marvin Minsky made what turned out to be highly optimistic forecasts of the advent of super-intelligent artificial intelligence (AI), then in a 1994 Scientific American article explained why vastly extended lives will require replacing our biological brains with superior computational devices. The idea of accelerating technological progress driven by machine super-intelligence dates back several decades. This idea, now frequently referred to as “the singularity,” was explicitly pondered in a 1958 conversation between Stanislaw Ulam and John von Neumann during which they discussed “the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue” (Ulam 1958). In 1965, I.J.

Sandberg, Anders (2001) “Morphological Freedom – Why We Not Just Want It, but Need It.” http://www.nada.kth.se/~asa/Texts/MorphologicalFreedom.htm. Retrieved November 21, 2011. Stambler, Ilia (2010) “Life Extension: A Conservative Enterprise? Some Fin-de-Siècle and Early Twentieth-Century Precursors of Transhumanism.” Journal of Evolution and Technology 21/1 (March), pp. 13–26. Ulam, Stanislaw (1958) “John von Neumann 1903–1957.” Bulletin of the American Mathematical Society (May), part 2, pp. 1–49. Various (2002) “The Transhumanist Declaration.” http://humanityplus.org/philosophy/transhumanist-declaration/. Various (2003) “The Transhumanist FAQ: v 2.1.” World Transhumanist Association. http://humanityplus.org/philosophy/transhumanist-faq/.

The problem is that while we can imagine, for example, a robot arm that can screw, bolt, solder, and weld enough to assemble a robot arm from parts, it needs a sequence of instructions to obey in this process. And there is more than one instruction per part. But the instructions must be embodied in some physical form, so to finish the process we need instructions to build the instructions, and so on, in an infinite regress. The answer to this seeming conundrum was given mathematically by John von Neumann, and at roughly the same time (the 1950s) was teased out of the naturally occurring self-reproducing machines we find all around us, living cells. It turns out to be the same answer in both cases. First, design a machine that can build machines, like the robot arm above. (In a cell, there is such a thing, called a ribosome.)


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The Undercover Economist: Exposing Why the Rich Are Rich, the Poor Are Poor, and Why You Can Never Buy a Decent Used Car by Tim Harford

Alan Greenspan, Albert Einstein, barriers to entry, Berlin Wall, business cycle, collective bargaining, congestion charging, Corn Laws, David Ricardo: comparative advantage, decarbonisation, Deng Xiaoping, Fall of the Berlin Wall, George Akerlof, Great Leap Forward, household responsibility system, information asymmetry, invention of movable type, John Nash: game theory, John von Neumann, Kenneth Arrow, Kickstarter, market design, Martin Wolf, moral hazard, new economy, Pearl River Delta, price discrimination, Productivity paradox, race to the bottom, random walk, rent-seeking, Robert Gordon, Robert Shiller, Ronald Reagan, sealed-bid auction, second-price auction, second-price sealed-bid, Shenzhen special economic zone , Shenzhen was a fishing village, special economic zone, spectrum auction, The Market for Lemons, Thomas Malthus, trade liberalization, Vickrey auction

One auction really did raise less than 1 percent of what was hoped for, while another raised ten times as much as expected. This wasn’t down to luck but to cleverness in some cases and blundering in others. Auctioning air, like playing poker, is a game of great skill—and one that was played for very high stakes indeed. Love, war, and poker Many of those who knew the mathematician John von Neumann regarded him as the “best brain in the world,” and they had a chance to compare him with some stiff competition, given that one of von Neumann’s colleagues at Princeton was Albert Einstein. Von Neumann was a genius around whom grew a my-thology of almost superhuman intelligence. According to one story, Von Neumann was asked to assist with the design of a new supercomputer, required to solve a new and important mathematical problem, which was beyond the capacities of existing supercomputers.

But poker with your buddies in the garage is not the World Series; what can game theory say about players who get drunk and bluff badly? This is not a knockdown objection to game theory. It is possible to model mistakes, forgetfulness, misinformation, and any other kind of failure on the part of the players to live up to the impossibly high standards of John Von Neumann. The trouble is that the more mistakes that need to be taken into account, the more complicated and the less useful game theory becomes. It is always useful for the game theorist to draw on experience as well as pure theory, because if the game becomes too complex for the players to understand, then the theory becomes nearly useless for practical purposes since it tells us nothing about what they will actually do.

Telecom executives may curse the British auctions since 3G remains commercially unproven and threatened by competitors like Wi-Fi, but the public should celebrate them. All the compa- • 174 • T H E M E N W H O K N E W T H E V A L U E O F N O T H I N G nies involved were convinced that the 3G licenses offered tremendous scarcity value, and these auctions successfully secured a fair price for that apparent value. John von Neumann’s successors used game theory to achieve one of the most spectacular, if controversial, policy triumphs that economics had ever seen. The men who knew the “value of nothing” had shown that economists, like dentists, could finally earn their keep. • 175 • This page intentionally left blank W H Y P O O R C O U N T R I E S A R E P O O R E I G H T Why Poor Countries Are Poor They call Douala “the Armpit of Africa.”


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Beyond: Our Future in Space by Chris Impey

3D printing, Admiral Zheng, Albert Einstein, Alfred Russel Wallace, AltaVista, Apollo 11, Apollo 13, Berlin Wall, Biosphere 2, Buckminster Fuller, built by the lowest bidder, butterfly effect, California gold rush, carbon-based life, Charles Lindbergh, Colonization of Mars, cosmic abundance, crowdsourcing, cuban missile crisis, dark matter, Dennis Tito, discovery of DNA, Doomsday Clock, Edward Snowden, Elon Musk, Eratosthenes, Great Leap Forward, Haight Ashbury, Hans Moravec, Hyperloop, I think there is a world market for maybe five computers, Isaac Newton, Jeff Bezos, Johannes Kepler, John von Neumann, Kickstarter, Kim Stanley Robinson, Late Heavy Bombardment, life extension, low earth orbit, Mahatma Gandhi, Marc Andreessen, Mars Rover, Mars Society, military-industrial complex, mutually assured destruction, Neal Stephenson, Neil Armstrong, Nick Bostrom, ocean acidification, Oculus Rift, operation paperclip, out of africa, Peter H. Diamandis: Planetary Resources, phenotype, private spaceflight, purchasing power parity, quantum entanglement, radical life extension, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Rubik’s Cube, Scaled Composites, Search for Extraterrestrial Intelligence, Searching for Interstellar Communications, seminal paper, Silicon Valley, skunkworks, Skype, Snow Crash, space junk, SpaceShipOne, Stephen Hawking, Steven Pinker, supervolcano, technological singularity, telepresence, telerobotics, the medium is the message, the scientific method, theory of mind, There's no reason for any individual to have a computer in his home - Ken Olsen, Virgin Galactic, VTOL, wikimedia commons, world market for maybe five computers, X Prize, Yogi Berra

Using fairly conventional forms of propulsion, these probes could spread through a galaxy the size of the Milky Way in less than a few million years. The probes could investigate planetary systems and send information back to us on the home planet.23 The concept is named after the Hungarian mathematician and physicist John von Neumann. He was one of the major intellectual figures of the twentieth century, making important contributions to mathematics, physics, computer science, and economics. Noted physicist Eugene Wigner recalled that von Neumann’s unusual mind was like a “. . . perfect instrument whose gears were machined to mesh accurately within a thousandth of an inch.”

This is the time, projected to be in the middle of the twenty-first century, when civilization and human nature itself are fundamentally transformed. One variant of the singularity is when artificial intelligence surpasses human intelligence. Software-based synthetic minds begin to program themselves and a runaway reaction of self-improvement occurs. This event was foreshadowed by John von Neumann and Alan Turing in the 1950s. Turing wrote that “. . . at some stage therefore we should have to expect the machines to take control . . . ,” and von Neumann described “. . . an ever-accelerating progress and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.”17 A dystopian version of this event permeates the popular culture, from science fiction novels to movies such as Blade Runner and The Terminator.

“X-Tech and the Search for Infra Particle Intelligence” by H. de Garis 2014, from Best of H+, online at http://hplusmagazine.com/2014/02/20/x-tech-and-the-search-for-infra-particle-intelligence/. 17. Intelligent Machinery, A Heretical Theory by A. Turing 1951, reprinted in Philosophia Mathematica 1996, vol. 4, no. 3, pp. 256–60. The von Neumann quote comes from Stanislaw Ulam’s “Tribute to John von Neumann” in the May 1958 Bulletin of the American Mathematical Society, p. 5. 18. “Are You Living in a Computer Simulation?” by N. Bostrom 2003. Philosophical Quarterly, vol. 53, no. 211, pp. 243–55. The views of Kurzweil and Moravec are represented in their popular books, in particular The Singularity Is Near: When Humans Transcend Biology by R.


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The Road to Conscious Machines by Michael Wooldridge

Ada Lovelace, AI winter, algorithmic bias, AlphaGo, Andrew Wiles, Anthropocene, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, basic income, Bletchley Park, Boeing 747, British Empire, call centre, Charles Babbage, combinatorial explosion, computer vision, Computing Machinery and Intelligence, DARPA: Urban Challenge, deep learning, deepfake, DeepMind, Demis Hassabis, don't be evil, Donald Trump, driverless car, Elaine Herzberg, Elon Musk, Eratosthenes, factory automation, fake news, future of work, gamification, general purpose technology, Geoffrey Hinton, gig economy, Google Glasses, intangible asset, James Watt: steam engine, job automation, John von Neumann, Loebner Prize, Minecraft, Mustafa Suleyman, Nash equilibrium, Nick Bostrom, Norbert Wiener, NP-complete, P = NP, P vs NP, paperclip maximiser, pattern recognition, Philippa Foot, RAND corporation, Ray Kurzweil, Rodney Brooks, self-driving car, Silicon Valley, Stephen Hawking, Steven Pinker, strong AI, technological singularity, telemarketer, Tesla Model S, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, trolley problem, Turing machine, Turing test, universal basic income, Von Neumann architecture, warehouse robotics

Surely what we really want is for them to make good choices – the best choices possible. The goal of AI thus began to shift from building agents that make human choices to agents that make optimal choices. The theory of optimal decision-making that underpins most work in AI goes back to the 1940s, and the work of John von Neumann – the same John von Neumann whom we met in Chapter 1, who did seminal work on the design of the earliest computers. Along with his colleague Oskar Morgenstern, he developed a mathematical theory of rational decision-making. This theory showed how the problem of making a rational choice could be reduced to a mathematical calculation.12 In agent-based AI, the idea was that the agent would use their theory to make optimal decisions on your behalf.

In wartime Munich, Konrad Zuse designed a computer called the Z3 for the German Air Ministry – although it was not quite a modern computer, it introduced many of the key ingredients of one. Across the Atlantic in Pennsylvania, a team led by John Mauchly and J. Presper Eckert developed a machine called ENIAC to compute artillery tables. With some tweaks by the brilliant Hungarian mathematician John von Neumann, ENIAC established the fundamental architecture of the modern computer (the architecture of conventional computers is called the Von Neumann architecture, in his honour). Over in post-war England, Fred Williams and Tom Kilburn built the Manchester Baby, which led directly to the world’s first commercial computer, the Ferranti Mark 1 – Turing himself joined the staff of Manchester University in 1948, and wrote some of the first programs to run on it.


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The Scandal of Money by George Gilder

Affordable Care Act / Obamacare, Alan Greenspan, bank run, behavioural economics, Bernie Sanders, bitcoin, blockchain, borderless world, Bretton Woods, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, Claude Shannon: information theory, Clayton Christensen, cloud computing, corporate governance, cryptocurrency, currency manipulation / currency intervention, currency risk, Daniel Kahneman / Amos Tversky, decentralized internet, Deng Xiaoping, disintermediation, Donald Trump, fiat currency, financial innovation, Fractional reserve banking, full employment, George Gilder, glass ceiling, guns versus butter model, Home mortgage interest deduction, impact investing, index fund, indoor plumbing, industrial robot, inflation targeting, informal economy, Innovator's Dilemma, Internet of things, invisible hand, Isaac Newton, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", Jeff Bezos, John Bogle, John von Neumann, Joseph Schumpeter, Kenneth Rogoff, knowledge economy, Law of Accelerating Returns, low interest rates, Marc Andreessen, Mark Spitznagel, Mark Zuckerberg, Menlo Park, Metcalfe’s law, Money creation, money: store of value / unit of account / medium of exchange, mortgage tax deduction, Nixon triggered the end of the Bretton Woods system, obamacare, OSI model, Paul Samuelson, Peter Thiel, Ponzi scheme, price stability, Productivity paradox, proprietary trading, purchasing power parity, quantitative easing, quantitative trading / quantitative finance, Ray Kurzweil, reality distortion field, reserve currency, road to serfdom, Robert Gordon, Robert Metcalfe, Ronald Reagan, Sand Hill Road, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, secular stagnation, seigniorage, Silicon Valley, Skinner box, smart grid, Solyndra, South China Sea, special drawing rights, The Great Moderation, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Tim Cook: Apple, time value of money, too big to fail, transaction costs, trickle-down economics, Turing machine, winner-take-all economy, yield curve, zero-sum game

Like the electromagnetic spectrum, which bears all the messages of the Internet to and from your smartphone or computer, it must be rooted in the absolute speed of light, the ultimate guarantor of the integrity of time. Dominating our own era and revealing in fundamental ways the nature of money is the information theory of Kurt Gödel, John von Neumann, Alan Turing, and Claude Shannon. Information theory tells us that information is not order but disorder, not the predictable regularity that contains no news, but the unexpected modulation, the surprising bits. But human creativity and surprise depend upon a matrix of regularities, from the laws of physics to the stability of money.4 Information theory has impelled the global ascendancy of information technology.

Gödel’s incompleteness theorem: Every logical system depends on propositions outside the system that are unprovable within the system. The first person to appreciate and publicize the importance of Kurt Gödel’s demonstration in 1931 that mathematical statements can be true but unprovable was John von Neumann. As von Neumann saw, Gödel’s proof depended on his invention of a mathematical “machine” that used numbers to encode and prove algorithms also expressed in numbers. This invention, absorbed by von Neumann and Alan Turing, launched computer science and INFORMATION THEORY and enabled the development of the Internet and the BLOCKCHAIN.


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In Pursuit of the Perfect Portfolio: The Stories, Voices, and Key Insights of the Pioneers Who Shaped the Way We Invest by Andrew W. Lo, Stephen R. Foerster

Alan Greenspan, Albert Einstein, AOL-Time Warner, asset allocation, backtesting, behavioural economics, Benoit Mandelbrot, Black Monday: stock market crash in 1987, Black-Scholes formula, Bretton Woods, Brownian motion, business cycle, buy and hold, capital asset pricing model, Charles Babbage, Charles Lindbergh, compound rate of return, corporate governance, COVID-19, credit crunch, currency risk, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, Donald Trump, Edward Glaeser, equity premium, equity risk premium, estate planning, Eugene Fama: efficient market hypothesis, fake news, family office, fear index, fiat currency, financial engineering, financial innovation, financial intermediation, fixed income, hiring and firing, Hyman Minsky, implied volatility, index fund, interest rate swap, Internet Archive, invention of the wheel, Isaac Newton, Jim Simons, John Bogle, John Meriwether, John von Neumann, joint-stock company, junk bonds, Kenneth Arrow, linear programming, Long Term Capital Management, loss aversion, Louis Bachelier, low interest rates, managed futures, mandelbrot fractal, margin call, market bubble, market clearing, mental accounting, money market fund, money: store of value / unit of account / medium of exchange, Myron Scholes, new economy, New Journalism, Own Your Own Home, passive investing, Paul Samuelson, Performance of Mutual Funds in the Period, prediction markets, price stability, profit maximization, quantitative trading / quantitative finance, RAND corporation, random walk, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Solow, Ronald Reagan, Savings and loan crisis, selection bias, seminal paper, shareholder value, Sharpe ratio, short selling, South Sea Bubble, stochastic process, stocks for the long run, survivorship bias, tail risk, Thales and the olive presses, Thales of Miletus, The Myth of the Rational Market, The Wisdom of Crowds, Thomas Bayes, time value of money, transaction costs, transfer pricing, tulip mania, Vanguard fund, yield curve, zero-coupon bond, zero-sum game

His reading of Hume had piqued his interest in philosophical questions such as “What do we know?” and “How do we know it?” and the uncertainty surrounding those questions. Consequently, Markowitz was drawn to the economics of uncertainty, particularly the theory of games and utility theory developed by John von Neumann and Oskar Morgenstern, and soon to the work on subjective probability by the University of Chicago’s own Leonard Jimmie Savage. Expected utility theory is the framework in economics for understanding how people make decisions over their lifetimes based on their preferences in consumption and savings—how much and when they want to consume or save.

For background related to Markowitz’s early years and for events surrounding the serendipitous moment described in this chapter, see Markowitz (1991), Bernstein (1992), Markowitz (1993), Yost (2002), Buser (2004a), Fox (2009), and Markowitz (2010). 3. Interview with authors. 4. Interview with authors. 5. Interview with authors. 6. Interview with authors. Markowitz was particularly proud to be a recipient of the John von Neumann Theory Prize, awarded to an individual or group that has made fundamental and sustained contributions to theory in operations research and the management sciences. “I have von Neumann’s picture with the first computer posted on the cork board in one of my rooms.” 7. See Friedman (1976). First awarded in 1969 and commonly known as the Nobel Prize in Economics (as we will typically refer to it), but not one of the original categories, the formal name of the prize is the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel. 8.

Vertin Award, received by Leibowitz, 200 Janus Henderson Investors, 169, 352–53n79 Jarrow, Robert, 180, 190–91 Jefferson, Thomas, 333 Jenrette, Richard, 260 Jensen, Michael, 90, 96, 109, 146, 218, 347n46; agency problem and, 108–9; collaboration with Scholes and Black, 146, 148; education of, 143; on efficient market hypothesis, 81; publications of, 148 Johnson, Craig, 75 John von Neumann Theory Prize, Markowitz as winner of, 336n6 joint-stock companies, modern, first, 8–9 Journal of Finance, 27 JP Morgan, Merton Model and, 185 Kahneman, Daniel, 42, 83–84 Kamstra, Mark, 253, 254 Kaplan, Paul, on Markowitz’s contribution to portfolio construction, 44 Katona, George, 228 Ketchum, Marshall, 23, 338n40 Keynes, John Maynard, 283, 320; Cambridge University endowment managed by, 16–17; lack of impact on investing, 17; publications of, 15, 16, 17, 132; on sources of return, 132 Kindleberger, Charles, 240–41 Klein, Lawrence, as Nobel Prize winner, 22 Klingenstein, J.


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American Prometheus: The Triumph and Tragedy of J. Robert Oppenheimer by Kai Bird, Martin J. Sherwin

Albert Einstein, anti-communist, Anton Chekhov, British Empire, centre right, cuban missile crisis, David Brooks, desegregation, disinformation, Eddington experiment, Ernest Rutherford, fear of failure, housing crisis, index card, industrial research laboratory, John von Neumann, Lewis Mumford, Mahatma Gandhi, military-industrial complex, Murray Gell-Mann, post-industrial society, public intellectual, Richard Feynman, Robert Gordon, seminal paper, strikebreaker, traveling salesman, union organizing, Upton Sinclair, uranium enrichment

Another German physicist, Ernst Pascual Jordan, was collaborating with Born and Heisenberg to formulate the matrix mechanics version of quantum theory. The young English physicist Paul Dirac, whom Oppenheimer had met at Cambridge, was then working on early quantum field theory, and in 1933 he would share a Nobel Prize with Erwin Schrödinger. The Hungarian-born mathematician John Von Neumann would later work for Oppenheimer on the Manhattan Project. George Eugene Uhlenbeck was an Indonesian-born Dutchman who, together with Samuel Abraham Goudsmit, discovered the concept of electron spin in late 1925. Robert quickly drew the attention of these men. He had met Uhlenbeck the previous spring during his weeklong visit to the University of Leiden.

Despite having been skeptical about the implosion idea when it was first broached by Serber, Oppenheimer now marshaled all his persuasive powers to argue that they gamble everything on an implosion-design plutonium bomb. It was an audacious and brilliant gamble. Since the spring of 1943, when Seth Neddermeyer had volunteered to experiment with the concept, little progress had been made. But in the autumn of 1943, Oppenheimer brought the Princeton mathematician John von Neumann to Los Alamos, and von Neumann calculated that implosion was possible, at least theoretically. Oppenheimer was willing to bet on it. The next day, July 18, Oppenheimer summarized his conclusions for Groves: “We have investigated briefly the possibility of an electromagnetic separation. . . .

Flexner wanted the very best people, and he wanted to ensure that none of his scholars would ever feel compelled to supplement their income by “writing unnecessary textbooks or engaging in other forms of hack work.” There would be “no duties, only opportunities.” Throughout the 1930s, Flexner recruited brilliant minds, mostly mathematicians like John von Neumann, Kurt Gödel, Hermann Weyl, Deane Montgomery, Boris Podolsky, Oswald Veblen, James Alexander and Nathan Rosen. Flexner hailed the “usefulness of useless knowledge.” But by the 1940s, the Institute was in danger of acquiring a reputation for coddling brilliant minds with forever unfulfilled potential.


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Priceless: The Myth of Fair Value (And How to Take Advantage of It) by William Poundstone

availability heuristic, behavioural economics, book value, Cass Sunstein, collective bargaining, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, Dr. Strangelove, East Village, en.wikipedia.org, endowment effect, equal pay for equal work, experimental economics, experimental subject, feminist movement, game design, German hyperinflation, Henri Poincaré, high net worth, index card, invisible hand, John von Neumann, Kenneth Arrow, laissez-faire capitalism, Landlord’s Game, Linda problem, loss aversion, market bubble, McDonald's hot coffee lawsuit, mental accounting, meta-analysis, Nash equilibrium, new economy, no-fly zone, Paul Samuelson, payday loans, Philip Mirowski, Potemkin village, power law, price anchoring, price discrimination, psychological pricing, Ralph Waldo Emerson, RAND corporation, random walk, RFID, Richard Thaler, risk tolerance, Robert Shiller, rolodex, social intelligence, starchitect, Steve Jobs, The Chicago School, The Wealth of Nations by Adam Smith, three-martini lunch, ultimatum game, working poor

Born in Morristown, New Jersey, he was the son of an economist and grew up hearing the table talk of his father’s colleagues. This instilled in him a rebellious skepticism toward economics. Ward decided on psychology as a career, studying at Swarthmore and Harvard. It was at Harvard that he read the work of John von Neumann and Oskar Morgenstern, and he wasn’t crazy about all he read. Hungarian-born John von Neumann was one of the great mathematicians of the twentieth century. At the urging of Princeton economist Oskar Morgenstern, von Neumann turned his brilliant mind to the problems of economics. The result was a 1944 book, Theory of Games and Economic Behavior.

Between the trick haircut and the tight smile that might be a frown, Allais’ face evoked one of those odd pictures that becomes a different face when turned upside down. Allais had told Savage he had something to show him. It was a little test he wanted him to take. The important thing is that Savage failed the test. Savage was a brash statistician, then at the University of Chicago. He had gone into statistics on the advice of John von Neumann himself. Visually, the most remarkable thing about him was his eyeglasses. Their lenses packed enough diopters to reveal the space behind his head. At Chicago, Savage had acquired a second mentor, Milton Friedman—founding father of the Chicago school of economics, future Nobel laureate, and veritable saint to Reagan-era capitalists.


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Einstein's Fridge: How the Difference Between Hot and Cold Explains the Universe by Paul Sen

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anthropic principle, anti-communist, Bletchley Park, British Empire, Brownian motion, Claude Shannon: information theory, Computing Machinery and Intelligence, cosmic microwave background, cosmological constant, Ernest Rutherford, heat death of the universe, invention of radio, Isaac Newton, James Watt: steam engine, John von Neumann, Khan Academy, Kickstarter, Richard Feynman, seminal paper, Stephen Hawking, traveling salesman, Turing complete, Turing test

A few months later, in January of 1940, the couple married and honeymooned in New Hampshire, an event spoiled by an anti-Semitic hotelier who wouldn’t let them have a room because Levor was Jewish. Later that year, the couple moved to Princeton, where Shannon had been granted a fellowship at the Institute for Advanced Study. Here the pair rubbed shoulders with some of the world’s greatest mathematicians and physicists, Hermann Weyl, John von Neumann, and Einstein, who had made Princeton his home after having been driven out of Germany in 1933. For the Shannons, however, life took an unhappy turn. Their affair, which had blossomed so quickly, self-destructed just as fast. To Levor, Shannon changed. He found the atmosphere at Princeton alienating and stifling and his natural joie de vivre evaporated.

Here’s Shannon’s equation for calculating the size of any given piece of information: H = –Σi pi logb pi And here’s one way of stating Boltzmann’s equation for calculating the entropy of any given system: S = –kB Σi pi ln pi These two equations don’t just look similar; they’re effectively the same. Shortly after deriving his equation, Shannon pointed the similarity out to John von Neumann, then widely considered the world’s best mathematician. Von Neumann shrugged, suggesting that Shannon call his measure of the number of bits needed to carry a piece of information information entropy on the grounds that no one really understood thermodynamic entropy either. The similarity occurs because Shannon considered a system of communication like written English in much the same way that Boltzmann had thought about a gas.

“I had talked to him several times”: From “Shannon: An Interview by Price.” “They never told me”: As quoted in Mind at Play by Soni and Goodman. “A Mathematical Theory of Communication”: From Bell System Technical Journal 27 (1948). “reproducing at one point”: From the above paper. Shannon pointed the similarity out to John von Neumann: This anecdote originates in a 1971 article, “Energy and Information,” Scientific American, by Myron Tribus and Edward C. McIrvine. But in 1982, in a taped interview Shannon is rather hazy about why he chose the term entropy. MST PPL HV: From “Information Theory” by Claude E. Shannon, Encyclopaedia Britannica, 14th ed.


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The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma by Mustafa Suleyman

"World Economic Forum" Davos, 23andMe, 3D printing, active measures, Ada Lovelace, additive manufacturing, agricultural Revolution, AI winter, air gap, Airbnb, Alan Greenspan, algorithmic bias, Alignment Problem, AlphaGo, Alvin Toffler, Amazon Web Services, Anthropocene, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, ASML, autonomous vehicles, backpropagation, barriers to entry, basic income, benefit corporation, Big Tech, biodiversity loss, bioinformatics, Bletchley Park, Blitzscaling, Boston Dynamics, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, ChatGPT, choice architecture, circular economy, classic study, clean tech, cloud computing, commoditize, computer vision, coronavirus, corporate governance, correlation does not imply causation, COVID-19, creative destruction, CRISPR, critical race theory, crowdsourcing, cryptocurrency, cuban missile crisis, data science, decarbonisation, deep learning, deepfake, DeepMind, deindustrialization, dematerialisation, Demis Hassabis, disinformation, drone strike, drop ship, dual-use technology, Easter island, Edward Snowden, effective altruism, energy transition, epigenetics, Erik Brynjolfsson, Ernest Rutherford, Extinction Rebellion, facts on the ground, failed state, Fairchild Semiconductor, fear of failure, flying shuttle, Ford Model T, future of work, general purpose technology, Geoffrey Hinton, global pandemic, GPT-3, GPT-4, hallucination problem, hive mind, hype cycle, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, Internet of things, invention of the wheel, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kickstarter, lab leak, large language model, Law of Accelerating Returns, Lewis Mumford, license plate recognition, lockdown, machine readable, Marc Andreessen, meta-analysis, microcredit, move 37, Mustafa Suleyman, mutually assured destruction, new economy, Nick Bostrom, Nikolai Kondratiev, off grid, OpenAI, paperclip maximiser, personalized medicine, Peter Thiel, planetary scale, plutocrats, precautionary principle, profit motive, prompt engineering, QAnon, quantum entanglement, ransomware, Ray Kurzweil, Recombinant DNA, Richard Feynman, Robert Gordon, Ronald Reagan, Sam Altman, Sand Hill Road, satellite internet, Silicon Valley, smart cities, South China Sea, space junk, SpaceX Starlink, stealth mode startup, stem cell, Stephen Fry, Steven Levy, strong AI, synthetic biology, tacit knowledge, tail risk, techlash, techno-determinism, technoutopianism, Ted Kaczynski, the long tail, The Rise and Fall of American Growth, Thomas Malthus, TikTok, TSMC, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, uranium enrichment, warehouse robotics, William MacAskill, working-age population, world market for maybe five computers, zero day

Consider these words, in their own way as chilling as his famous Bhagavad Gita quotation (on seeing the first nuclear test, he recalled some lines from Hindu scripture: “Now I am become Death, the destroyer of worlds”): “When you see something that is technically sweet, you go ahead and do it, and you argue about what to do about it only after you have had your technical success.” It was an attitude shared by his colleague on the Manhattan Project, the brilliant, polymathic Hungarian American John von Neumann. “What we are creating now,” he said, “is a monster whose influence is going to change history, provided there is any history left, yet it would be impossible not to see it through, not only for military reasons, but it would also be unethical from the point of view of the scientists not to do what they know is feasible, no matter what terrible consequences it may have.”

The costs of saying no are existential. And yet every path from here brings grave risks and downsides. This is the great dilemma. WHERE NEXT? From the start of the nuclear and digital age, this dilemma has been growing clearer. In 1955, toward the end of his life, the mathematician John von Neumann wrote an essay called “Can We Survive Technology?” Foreshadowing the argument here, he believed that global society was “in a rapidly maturing crisis—a crisis attributable to the fact that the environment in which technological progress must occur has become both undersized and underorganized.”

GO TO NOTE REFERENCE IN TEXT Demand for lithium, cobalt “Climate-Smart Mining: Minerals for Climate Action,” World Bank, www.worldbank.org/​en/​topic/​extractiveindustries/​brief/​climate-smart-mining-minerals-for-climate-action. GO TO NOTE REFERENCE IN TEXT Given the population and resource constraints Galor, The Journey of Humanity, 130. GO TO NOTE REFERENCE IN TEXT In 1955, toward the end of his life John von Neumann, “Can We Survive Technology?,” in The Neumann Compendium (River Edge, N.J.: World Scientific, 1995), geosci.uchicago.edu/​~kite/​doc/​von_Neumann_1955.pdf. GO TO NOTE REFERENCE IN TEXT Chapter 13: Containment Must Be Possible How do they account for an age David Cahn et al., “AI 2022: The Explosion,” Coatue Venture, coatue-external.notion.site/​AI-2022-The-Explosion-e76afd140f824f2eb6b049c5b85a7877.


pages: 242 words: 68,019

Why Information Grows: The Evolution of Order, From Atoms to Economies by Cesar Hidalgo

Ada Lovelace, Albert Einstein, Arthur Eddington, assortative mating, business cycle, Claude Shannon: information theory, David Ricardo: comparative advantage, Douglas Hofstadter, Everything should be made as simple as possible, Ford Model T, frictionless, frictionless market, George Akerlof, Gödel, Escher, Bach, income inequality, income per capita, industrial cluster, information asymmetry, invention of the telegraph, invisible hand, Isaac Newton, James Watt: steam engine, Jane Jacobs, job satisfaction, John von Neumann, Joi Ito, New Economic Geography, Norbert Wiener, p-value, Paul Samuelson, phenotype, price mechanism, Richard Florida, Robert Solow, Ronald Coase, Rubik’s Cube, seminal paper, Silicon Valley, Simon Kuznets, Skype, statistical model, Steve Jobs, Steve Wozniak, Steven Pinker, Stuart Kauffman, tacit knowledge, The Market for Lemons, The Nature of the Firm, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, working-age population

By quantifying the number of bits we need to encode messages, he helped develop digital communication technologies. Yet what Shannon did not know when he developed his formula was that it was identical to the formula discovered by Boltzmann nearly half a century earlier. At the suggestion of John von Neumann, the famous Hungarian mathematician, Shannon decided to call his measure “entropy,” since Shannon’s formula was equivalent to the formula for entropy used by statistical physicists. (Also—as the legend goes—von Neumann told Shannon that calling his measure entropy would guarantee Shannon’s victory in every argument, since nobody really knew what entropy was.)

The fact that the genetic variation between individuals is much larger than the genetic variation between groups is a key argument to fend off racist and eugenic arguments. This explanation is key to the line of argumentation advanced in Pinker, The Blank Slate. 14. Speculating about the knowledge- and information-carrying capacity of the human brain is an interesting exercise. Among the first ones to perform this exercise was John von Neumann, the Hungarian polymath who became interested in computers while working on the Manhattan Project. Some of his speculations on the topic are presented in his The Computer and the Brain (New Haven, CT: Yale University Press, 1958). There, Neumann notes that the architecture of the brain is fundamentally different from that of computers.


pages: 238 words: 46

When Things Start to Think by Neil A. Gershenfeld

3D printing, Ada Lovelace, Bretton Woods, cellular automata, Charles Babbage, Claude Shannon: information theory, Computing Machinery and Intelligence, disinformation, Dynabook, Hedy Lamarr / George Antheil, I think there is a world market for maybe five computers, information security, invention of movable type, Iridium satellite, Isaac Newton, Jacquard loom, Johannes Kepler, John von Neumann, low earth orbit, means of production, new economy, Nick Leeson, packet switching, RFID, speech recognition, Stephen Hawking, Steve Jobs, telemarketer, the medium is the message, Turing machine, Turing test, Vannevar Bush, world market for maybe five computers

There is a disconnect between the breathless pronouncements of cyber gurus and the experience of ordinary people left perpetually upgrading hardware to meet the demands of new software, or wondering where their files have gone, or trying to understand why they can't connect to the network. The revolution so far has been for the computers, not the people. Digital data of all kinds, whether an e-mail message or a movie, is encoded as a string of O's and 1's because of a remarkable discovery by Claude Shannon and John von Neumann in the 1940s. Prior to their work, it was obvious that engineered systems degraded with time and use. A tape recording sounds worse after it is duplicated, a photocopy is less satisfactory than an original, a telephone call becomes more garbled the farther it has to travel. They showed that this is not so for a digital representation.

When Babbage started building machines to evaluate not just arithmetic but more complex functions he likewise used discrete values. This required approximating the continuous changes by small differences, hence the name of the Difference Engine. These approximations have been used ever since in electronic digital computers to allow them to manipulate models of the continuous world. Starting in the 1940s with John von Neumann, people realized that this practice was needlessly circular. Most physical phenomena start out discrete at some level. A fluid is not actually continuous; it is just made up of so many molecules that it appears to be continuous. The equations of calculus for a fluid are themselves an approximation of the rules for how the molecules behave.


pages: 413 words: 119,587

Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots by John Markoff

A Declaration of the Independence of Cyberspace, AI winter, airport security, Andy Rubin, Apollo 11, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, basic income, Baxter: Rethink Robotics, Bill Atkinson, Bill Duvall, bioinformatics, Boston Dynamics, Brewster Kahle, Burning Man, call centre, cellular automata, Charles Babbage, Chris Urmson, Claude Shannon: information theory, Clayton Christensen, clean water, cloud computing, cognitive load, collective bargaining, computer age, Computer Lib, computer vision, crowdsourcing, Danny Hillis, DARPA: Urban Challenge, data acquisition, Dean Kamen, deep learning, DeepMind, deskilling, Do you want to sell sugared water for the rest of your life?, don't be evil, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dr. Strangelove, driverless car, dual-use technology, Dynabook, Edward Snowden, Elon Musk, Erik Brynjolfsson, Evgeny Morozov, factory automation, Fairchild Semiconductor, Fillmore Auditorium, San Francisco, From Mathematics to the Technologies of Life and Death, future of work, Galaxy Zoo, General Magic , Geoffrey Hinton, Google Glasses, Google X / Alphabet X, Grace Hopper, Gunnar Myrdal, Gödel, Escher, Bach, Hacker Ethic, Hans Moravec, haute couture, Herbert Marcuse, hive mind, hype cycle, hypertext link, indoor plumbing, industrial robot, information retrieval, Internet Archive, Internet of things, invention of the wheel, Ivan Sutherland, Jacques de Vaucanson, Jaron Lanier, Jeff Bezos, Jeff Hawkins, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Perry Barlow, John von Neumann, Kaizen: continuous improvement, Kevin Kelly, Kiva Systems, knowledge worker, Kodak vs Instagram, labor-force participation, loose coupling, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, medical residency, Menlo Park, military-industrial complex, Mitch Kapor, Mother of all demos, natural language processing, Neil Armstrong, new economy, Norbert Wiener, PageRank, PalmPilot, pattern recognition, Philippa Foot, pre–internet, RAND corporation, Ray Kurzweil, reality distortion field, Recombinant DNA, Richard Stallman, Robert Gordon, Robert Solow, Rodney Brooks, Sand Hill Road, Second Machine Age, self-driving car, semantic web, Seymour Hersh, shareholder value, side project, Silicon Valley, Silicon Valley startup, Singularitarianism, skunkworks, Skype, social software, speech recognition, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Strategic Defense Initiative, strong AI, superintelligent machines, tech worker, technological singularity, Ted Nelson, TED Talk, telemarketer, telepresence, telepresence robot, Tenerife airport disaster, The Coming Technological Singularity, the medium is the message, Thorstein Veblen, Tony Fadell, trolley problem, Turing test, Vannevar Bush, Vernor Vinge, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We are as Gods, Whole Earth Catalog, William Shockley: the traitorous eight, zero-sum game

In his final book, God & Golem, Inc., he explored the future human relationship with machines through the prism of religion. Invoking the parable of the golem, he pointed out that despite best intentions, humans are incapable of understanding the ultimate consequences of their inventions.16 In his 1980 dual biography of John von Neumann and Wiener, Steven Heims notes that in the late 1960s he had asked a range of mathematicians and scientists about Wiener’s philosophy of technology. The general reaction of the scientists was as follows: “Wiener was a great mathematician, but he was also eccentric. When he began talking about society and the responsibility of scientists, a topic outside of his area of expertise, well, I just couldn’t take him seriously.”17 Heims concludes that Wiener’s social philosophy hit a nerve with the scientific community.

He was drafted relatively late in the war, so his army career was more about serving as a cog in the bureaucracy than combat. Stationed close to home at Fort MacArthur in the port city of San Pedro, California, he began as a clerk, preparing discharges, then promotions for soldiers leaving the military. He made his way to Princeton for graduate school and promptly paid a visit to John von Neumann, the applied mathematician and physicist who would become instrumental in defining the basic design of the modern computer. At this point the notion of “artificial intelligence” was fermenting in McCarthy’s mind, but the coinage had not yet come to him. That wouldn’t happen for another half decade in conjunction with the summer 1956 Dartmouth conference.

pagewanted=all. 12.Ibid. 13.Ibid. 14.Carew, Walter Reuther, 144. 15.The Ad Hoc Committee on the Triple Revolution, “The Triple Revolution,” Liberation, April 1964, http://www.educationanddemocracy.org/FSCfiles/C_CC2a_TripleRevolution.htm. 16.Mark D. Stahlman, “Wiener’s Genius Project” (invited paper, IEEE 2014 Conference on Norbert Wiener in the 21st Century, 2014). 17.Steve J. Heims, John von Neumann and Norbert Wiener: From Mathematics to the Technologies of Life and Death (Cambridge, MA: MIT Press, 1980), 343. 18.Norbert Wiener, God and Golem, Inc.: A Comment on Certain Points where Cybernetics Impinges on Religion (Cambridge, MA: MIT Press, 1964), 29. 19.“Machines Smarter Than Men? Interview with Dr.


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Rationality: What It Is, Why It Seems Scarce, Why It Matters by Steven Pinker

affirmative action, Albert Einstein, autonomous vehicles, availability heuristic, Ayatollah Khomeini, backpropagation, basic income, behavioural economics, belling the cat, Black Lives Matter, butterfly effect, carbon tax, Cass Sunstein, choice architecture, classic study, clean water, Comet Ping Pong, coronavirus, correlation coefficient, correlation does not imply causation, COVID-19, critical race theory, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, David Attenborough, deep learning, defund the police, delayed gratification, disinformation, Donald Trump, Dr. Strangelove, Easter island, effective altruism, en.wikipedia.org, Erdős number, Estimating the Reproducibility of Psychological Science, fake news, feminist movement, framing effect, George Akerlof, George Floyd, germ theory of disease, high batting average, if you see hoof prints, think horses—not zebras, index card, Jeff Bezos, job automation, John Nash: game theory, John von Neumann, libertarian paternalism, Linda problem, longitudinal study, loss aversion, Mahatma Gandhi, meta-analysis, microaggression, Monty Hall problem, Nash equilibrium, New Journalism, Paul Erdős, Paul Samuelson, Peter Singer: altruism, Pierre-Simon Laplace, placebo effect, post-truth, power law, QAnon, QWERTY keyboard, Ralph Waldo Emerson, randomized controlled trial, replication crisis, Richard Thaler, scientific worldview, selection bias, social discount rate, social distancing, Social Justice Warrior, Stanford marshmallow experiment, Steve Bannon, Steven Pinker, sunk-cost fallacy, TED Talk, the scientific method, Thomas Bayes, Tragedy of the Commons, trolley problem, twin studies, universal basic income, Upton Sinclair, urban planning, Walter Mischel, yellow journalism, zero-sum game

Three quarters of Americans believe in at least one phenomenon that defies the laws of science, including psychic healing (55 percent), extrasensory perception (41 percent), haunted houses (37 percent), and ghosts (32 percent)—which also means that some people believe in houses haunted by ghosts without believing in ghosts.12 In social media, fake news (such as Joe Biden Calls Trump Supporters “Dregs of Society” and Florida Man Arrested for Tranquilizing and Raping Alligators in the Everglades) is diffused farther and faster than the truth, and humans are more likely to spread it than bots.13 It has become commonplace to conclude that humans are simply irrational—more Homer Simpson than Mr. Spock, more Alfred E. Neuman than John von Neumann. And, the cynics continue, what else would you expect from descendants of hunter-gatherers whose minds were selected to avoid becoming lunch for leopards? But evolutionary psychologists, mindful of the ingenuity of foraging peoples, insist that humans evolved to occupy the “cognitive niche”: the ability to outsmart nature with language, sociality, and know-how.14 If contemporary humans seem irrational, don’t blame the hunter-gatherers.

Either way, the theory shines a light on perplexing conundrums of rationality, and despite its provenance in pure math, it can be a source of profound life lessons.4 The theory of rational choice goes back to the dawn of probability theory and the famous argument by Blaise Pascal (1623–1662) on why you should believe in God: if you did and he doesn’t exist, you would just have wasted some prayers, whereas if you didn’t and he does exist, you would incur his eternal wrath. It was formalized in 1944 by the mathematician John von Neumann and the economist Oskar Morgenstern. Unlike the pope, von Neumann really might have been a space alien—his colleagues wondered about it because of his otherworldly intelligence. He also invented game theory (chapter 8), the digital computer, self-replicating machines, quantum logic, and key components of nuclear weapons, while making dozens of other breakthroughs in math, physics, and computer science.

., van Bochoven, A., et al. 2015. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nature Genetics, 47, 702–9. https://doi.org/10.1038/ng.3285. Popper, K. R. 1983. Realism and the aim of science. London: Routledge. Poundstone, W. 1992. Prisoner’s dilemma: John von Neumann, game theory, and the puzzle of the bomb. New York: Anchor. President’s Council of Advisors on Science and Technology. 2016. Report to the President: Forensic science in criminal courts: ensuring scientific validity of feature-comparison methods. https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/PCAST/pcast_forensic_science_report_final.pdf.


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The Age of Radiance: The Epic Rise and Dramatic Fall of the Atomic Era by Craig Nelson

Albert Einstein, Brownian motion, Charles Lindbergh, clean tech, cognitive dissonance, Columbine, continuation of politics by other means, corporate governance, cuban missile crisis, dark matter, Doomsday Clock, Dr. Strangelove, El Camino Real, Ernest Rutherford, failed state, Great Leap Forward, Henri Poincaré, Herman Kahn, hive mind, Isaac Newton, it's over 9,000, John von Neumann, Louis Pasteur, low earth orbit, Menlo Park, Mikhail Gorbachev, military-industrial complex, music of the spheres, mutually assured destruction, nuclear taboo, nuclear winter, oil shale / tar sands, Project Plowshare, Ralph Nader, Richard Feynman, Ronald Reagan, Skype, Strategic Defense Initiative, Stuxnet, technoutopianism, Ted Sorensen, TED Talk, too big to fail, uranium enrichment, William Langewiesche, éminence grise

To keep Fermi from talking about his work to others, Baudino got him to talk about it to him. So Fermi started saying that, “Soon Johnny will know so much about the project he will need a bodyguard, too.” When agent Charles Campbell, who hated physics but pretended to like it as part of his job, mentioned to John von Neumann that he was too busy to study, von Neumann got upset: “It is my fault! You will come with me and together we will study theoretical physics in New Mexico!” FBI surveillance teams used walkie-talkies disguised as hearing aids, and any assembled together looked conspicuously like an outing of deaf people.

By the summer of 1948, Edward Teller’s Chicago idyll was upended by news of the Soviet invasions of Hungary, his birthplace, and Czechoslovakia, with its uranium mother lode at St. Joachimsthal. Communists were victorious in China, and soon enough, they would successfully blockade Berlin. It appeared to many that America’s foes were taking over the world, that the United States was in real danger. “Russia was traditionally the enemy,” John von Neumann said of his countrymen. “I think you will find, generally speaking, among Hungarians an emotional fear and dislike of Russia.” Had Edward Teller been certain that a hydrogen bomb was impossible, that nobody could make it, he would have set his sights elsewhere. But like Leo Szilard’s thinking of Hitler, Ed was tormented by what might happen if the Americans failed to create such a mighty weapon, and the totalitarians succeeded.

The very least we can conclude is that our twenty-thousandth bomb, useful as it may be in filling the vast munitions pipelines of a great war, will not in any deep strategic sense offset their two-thousandth.” Hearing this, physicist John Wheeler complained to a congressman, “Anybody who says twenty thousand weapons are no better than two thousand ought to read the history of wars.” Sharing Wheeler’s perspective was Hungarian mathematician John von Neumann, who announced in 1950, “If you say why not bomb them tomorrow, I say why not today? If you say today at five o’clock, I say why not one o’clock?” Von Neumann’s promotion of a preemptory nuclear strike was one of the many oddities that inspired Einstein to nickname his Princeton colleague Denktier, “think animal.”


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I Am a Strange Loop by Douglas R. Hofstadter

Albert Einstein, Andrew Wiles, Benoit Mandelbrot, Brownian motion, Charles Babbage, double helix, Douglas Hofstadter, Georg Cantor, Gödel, Escher, Bach, Hans Moravec, Isaac Newton, James Watt: steam engine, John Conway, John von Neumann, language acquisition, mandelbrot fractal, pattern recognition, Paul Erdős, place-making, probability theory / Blaise Pascal / Pierre de Fermat, publish or perish, random walk, Ronald Reagan, self-driving car, Silicon Valley, telepresence, Turing machine

They envisioned their computers as being specialized, single-purpose machines — a little like wind-up music boxes that could play just one tune each. But at some point, when Alan Turing’s abstract theory of computation, based in large part on Gödel’s 1931 paper, collided with the concrete engineering realities, some of the more perceptive people (Turing himself and John von Neumann especially) put two and two together and realized that their machines, incorporating the richness of integer arithmetic that Gödel had shown was so potent, were thereby universal. All at once, these machines were like music boxes that could read arbitrary paper scrolls with holes in them, and thus could play any tune.

SL #641: When we do look down at our fine-grained substrates through scientific experiments, we find small miracles just as Gödelian as is “I”. SL #642: Ah, yes, to be sure — little microgödelinos! But… such as? SL #641: I mean the self-reproduction of the double helix of DNA. The mechanism behind it all involves just the same abstract ideas as are implicated in Gödel’s type of self-reference. This is what John von Neumann unwittingly revealed when he designed a self-reproducing machine in the early 1950’s, and it had exactly the same abstract structure as Gödel’s self-referential trick did. SL #642: Are you saying microgödelinos are self-replicating machines? SL #641: Yes! It’s a subtle but beautiful analogy.

Page 139 an elegant linguistic analogy… See [Quine] for the original idea (which is actually a variation of Gödel’s idea (which is itself a variation of an idea of Jules Richard (which is a variation of an idea of Georg Cantor (which is a variation of an idea of Euclid (with help from Epimenides))))), and [Hofstadter 1979] for a variation on Quine’s theme. Page 147 “…and Related Systems (I)”… Gödel put a roman numeral at the end of the title of his article because he feared he had not spelled out sufficiently clearly some of his ideas, and expected he would have to produce a sequel. However, his paper quickly received high praise from John von Neumann and other respected figures, catapulting the unknown Gödel to a position of great fame in a short time, even though it took most of the mathematical community decades to absorb the meaning of his results. Page 150 respect for …the most mundane of analogies… See [Hofstadter 2001] and [Sander], as well as Chapter 24 in [Hofstadter 1985] and [Hofstadter and FARG].


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To Be a Machine: Adventures Among Cyborgs, Utopians, Hackers, and the Futurists Solving the Modest Problem of Death by Mark O'Connell

"World Economic Forum" Davos, 3D printing, Ada Lovelace, AI winter, Airbnb, Albert Einstein, AlphaGo, Amazon Picking Challenge, artificial general intelligence, Bletchley Park, Boston Dynamics, brain emulation, Charles Babbage, clean water, cognitive dissonance, computer age, cosmological principle, dark matter, DeepMind, disruptive innovation, double helix, Edward Snowden, effective altruism, Elon Musk, Extropian, friendly AI, global pandemic, Great Leap Forward, Hans Moravec, impulse control, income inequality, invention of the wheel, Jacques de Vaucanson, John von Neumann, knowledge economy, Law of Accelerating Returns, Lewis Mumford, life extension, lifelogging, Lyft, Mars Rover, means of production, military-industrial complex, Nick Bostrom, Norbert Wiener, paperclip maximiser, Peter Thiel, profit motive, radical life extension, Ray Kurzweil, RFID, San Francisco homelessness, self-driving car, sharing economy, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Singularitarianism, Skype, SoftBank, Stephen Hawking, Steve Wozniak, superintelligent machines, tech billionaire, technological singularity, technoutopianism, TED Talk, The Coming Technological Singularity, Travis Kalanick, trickle-down economics, Turing machine, uber lyft, Vernor Vinge

With these invocations, he moves his arms downward, then outward to either side, before clasping his hands to his chest. He turns about the room, bestowing a gesture of esoteric benediction on the four points of the compass, speaking in each of these positions the hallowed name of a prophet of the computer age: Alan Turing, John von Neumann, Charles Babbage, Ada Lovelace. Then he stands perfectly still, this priestly young man, arms outspread in a cruciform posture. “Around me shines the bits,” he says, “and in me is the bytes. The data, the code, the communications. Forever, amen.” This young man, I learned, was a Swedish academic named Anders Sandberg.

In the broadest sense, the term refers to a time to come in which machine intelligence greatly surpasses that of its human originators, and biological life is subsumed by technology. It is, in its way, an extreme expression of techno-progressivism, the belief that the universal application of technology will solve the world’s most intractable problems. The idea has been around in some form for at least half a century. In his 1958 obituary for the physicist John von Neumann, with whom he had worked on the Manhattan Project, Stanislaw Ulam wrote about a conversation they once had about “the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.”


Bootstrapping: Douglas Engelbart, Coevolution, and the Origins of Personal Computing (Writing Science) by Thierry Bardini

Apple II, augmented reality, Bill Duvall, Charles Babbage, classic study, Compatible Time-Sharing System, Computing Machinery and Intelligence, conceptual framework, Donald Davies, Douglas Engelbart, Douglas Engelbart, Dynabook, experimental subject, Grace Hopper, hiring and firing, hypertext link, index card, information retrieval, invention of hypertext, Ivan Sutherland, Jaron Lanier, Jeff Rulifson, John von Neumann, knowledge worker, Leonard Kleinrock, Menlo Park, military-industrial complex, Mother of all demos, Multics, new economy, Norbert Wiener, Norman Mailer, packet switching, Project Xanadu, QWERTY keyboard, Ralph Waldo Emerson, RAND corporation, RFC: Request For Comment, Sapir-Whorf hypothesis, Silicon Valley, Steve Crocker, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, stochastic process, Ted Nelson, the medium is the message, theory of mind, Turing test, unbiased observer, Vannevar Bush, Whole Earth Catalog, work culture

(Licklider I9 6 5, 94 -9 5) Efforts to develop "equipment in which the user and the computer make their marks on different screens," that is, equipment in which, as on a type- writer keyboard, what the hand does and what the eye sees were again un- linked, in fact had started in the mid-1950'S, with the design and operation of JOHNNIAC, a Princeton-class computer built at RAND between 1950 and 1953 and named after John von Neumann, and the work of Allen Newell, Herbert Simon, and Cliff Shaw at RAND on JOSS, the JOHNNIAC Open Shop System, between 1960 and 1964. JOSS's main application was a "help- ful assistant" in the Artificial Intelligence tradition designed for mathemati- cians, an "open-shop" experiment in on-line communication. 8 "Open shop" in this context meant that JOSS was directly available to its users, who for the first time in computing history were not programmers or computer scientists: they were mathematicians at RAND.

The excerpt of Engelbart's 1962 report surely conveys the impression that Engelbart directly quotes Whorf. It IS obvious that It IS not the case, but that Engel- bart IS gIving here hIs own translation of the hypothesis. 13. During their training years as young mathematicians, from 1924 to 1926, both Norbert Wiener and John von Neumann spent some time in Gottingen, Ger- many, where their paths first crossed when they attended lectures by Heisenberg (Heims 19 8o , 5 1 - 52). 14. Korzybski summarized these three Aristotelian laws of thought as follows: "( I) The law of identity (Whatever is, is. (A thing is what it is}); (2) The law of con- tradiction.

AvaIl- able on-line at http://picasso.dei.isep.ipp.pt/docs/arpa.html. Hayles, N. K. 1999. How We Became Post-Human: VIrtual Bod,es In CybernetIcs, LIterature, and Informatics. Chicago: UniversIty of ChIcago Press. Helm, M. 1993. MetaphysIcs of Virtual Reality. Oxford: Oxford University Press. Heims, S. J. 1980. John von Neumann and Norbert WIener: From Mathematics to TechnologIes of Life and Death. Cambridge, Mass.: MIT Press. . 1991. The CybernetIcs Group. Cambridge, Mass.: MIT Press. HerkImer County HIstorical Society. 1923. The Story of the TypewrIter, 1873- 1923. HerkImer, N.Y. Hodges, A. 1992 [1983]. Alan TurIng: The EnIgma.


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Fire in the Valley: The Birth and Death of the Personal Computer by Michael Swaine, Paul Freiberger

1960s counterculture, Amazon Web Services, Andy Rubin, Apple II, barriers to entry, Bill Atkinson, Bill Gates: Altair 8800, Byte Shop, Charles Babbage, cloud computing, commoditize, Computer Lib, computer vision, Dennis Ritchie, Do you want to sell sugared water for the rest of your life?, Douglas Engelbart, Douglas Engelbart, Dynabook, Fairchild Semiconductor, Gary Kildall, gentleman farmer, Google Chrome, I think there is a world market for maybe five computers, Internet of things, Isaac Newton, Jaron Lanier, Jeff Hawkins, job automation, John Gilmore, John Markoff, John Perry Barlow, John von Neumann, Jony Ive, Ken Thompson, Larry Ellison, Loma Prieta earthquake, Marc Andreessen, Menlo Park, Mitch Kapor, Mother of all demos, Paul Terrell, popular electronics, Richard Stallman, Robert Metcalfe, Silicon Valley, Silicon Valley billionaire, Silicon Valley startup, stealth mode startup, Steve Ballmer, Steve Jobs, Steve Wozniak, Stewart Brand, Ted Nelson, Tim Cook: Apple, urban sprawl, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, world market for maybe five computers

Because it could perform any task described in the instructions, such a machine would be a true general-purpose device. Perhaps no one before Turing had ever entertained an idea this large. But within a decade, Turing’s visionary idea became reality. The instructions became programs, and his concept, in the hands of another mathematician, John von Neumann, became the general-purpose computer. Most of the work that brought the computer into existence happened in secret laboratories during World War II. That’s where Turing was working. In the US in 1943, at the Moore School of Electrical Engineering in Philadelphia, John Mauchly and J. Presper Eckert proposed the idea for a computer.

(Courtesy of IBM Archives) Credit for inventing the electronic digital computer is disputed, and perhaps ENIAC was based in part on ideas Mauchly hatched during a visit to John Atanasoff. But ENIAC was real. Mauchly and Eckert attracted a number of bright mathematicians to the ENIAC project, including the brilliant John von Neumann. Von Neumann became involved with the project and made various–and variously reported–contributions to building ENIAC, and in addition offered an outline for a more sophisticated machine called EDVAC (Electronic Discrete Variable Automatic Computer). Because of von Neumann, the emphasis at the Moore School swung from technology to logic.

Despite all that electrical power, at any given time ENIAC could handle only 20 numbers of 10 decimal digits each. But even before construction was completed on ENIAC, it was put to significant use. In 1945, it performed calculations used in the atomic-bomb testing at Los Alamos, New Mexico. * * * Figure 9. John von Neumann Von Neumann was a brilliant polymath who made foundational contributions to programming and the ENIAC and EDVAC computers. (Courtesy of The Computer Museum History Center, San Jose) A new industry emerged after World War II when the secret labs began to disclose their discoveries and creations.


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The Marginal Revolutionaries: How Austrian Economists Fought the War of Ideas by Janek Wasserman

"World Economic Forum" Davos, Abraham Wald, Albert Einstein, American Legislative Exchange Council, anti-communist, battle of ideas, Berlin Wall, Bretton Woods, business cycle, collective bargaining, Corn Laws, correlation does not imply causation, creative destruction, David Ricardo: comparative advantage, different worldview, Donald Trump, experimental economics, Fall of the Berlin Wall, floating exchange rates, Fractional reserve banking, Francis Fukuyama: the end of history, full employment, Gunnar Myrdal, housing crisis, Internet Archive, invisible hand, John von Neumann, Joseph Schumpeter, laissez-faire capitalism, liberal capitalism, low interest rates, market fundamentalism, mass immigration, means of production, Menlo Park, military-industrial complex, Mont Pelerin Society, New Journalism, New Urbanism, old-boy network, Paul Samuelson, Philip Mirowski, price mechanism, price stability, public intellectual, RAND corporation, random walk, rent control, road to serfdom, Robert Bork, rolodex, Ronald Coase, Ronald Reagan, Silicon Valley, Simon Kuznets, The Chicago School, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, trade liberalization, union organizing, urban planning, Vilfredo Pareto, Washington Consensus, zero-sum game, éminence grise

The Austrians embarked on a second act in the Anglophone world, reinventing themselves as intellectual entrepreneurs who transplanted their ideas into related disciplines while simultaneously drawing inspiration from novel sources.25 Schumpeter’s “Literary” Turn If the early 1940s represented a low point for the popularity of the Austrian economists, then the mid- and late-1940s resurgence was a vindication of Austrian and central European thought styles. The list of impactful titles produced by the Austrians between 1942 and 1945 is staggering: Schumpeter, Capitalism, Socialism, and Democracy (1942); Hayek, Road to Serfdom (1944); Mises, Bureaucracy (1944); John von Neumann and Morgenstern, The Theory of Games and Economic Behavior (1944). If you include the works of Karl Polanyi and Karl Popper—The Great Transformation (1944) and The Open Society and Its Enemies (1945)—the Austrians may have produced more important texts in social and political theory than any other midcentury group.

Morgenstern pivoted away from his earliest work on time and economic methodology under the influence of Karl Menger and through collaboration with Abraham Wald. He became convinced that advanced mathematics provided the way forward for economics. Upon arrival at Princeton, he struck up a fast friendship with the Hungarian émigré mathematician John von Neumann, who had been at the Institute for Advanced Studies since fleeing Germany in 1932. This friendship became the most meaningful of Morgenstern’s life. Its culmination was the 1944 book The Theory of Games and Economic Behavior, the foundational work of game theory. Morgenstern believed that the work continued the revolution that the marginalists had initiated.

Morgenstern got on famously with the erstwhile heir to the Habsburg crown, Otto Habsburg; he enjoyed hobnobbing with the Rockefellers, David and Nelson. Morgenstern also had an uncanny eye for talent, hitching his star to brilliant thinkers. Theory of Games represented a successful accommodation by Morgenstern to the US academy, and it was a harbinger of the collaborations that sustained his intellectual path going forward. After John von Neumann’s tragic death in 1957, Morgenstern grew close with another Viennese, the mathematician Kurt Gödel. He mentored the Nobel laureate Martin Shubik and produced late-career work on the unpredictability of the stock market with Clive Granger, another Nobelist. The latter work, developed with Burton Malkiel, inspired Malkiel’s well-known random walk theory concerning the stock market.


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Between Human and Machine: Feedback, Control, and Computing Before Cybernetics by David A. Mindell

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Charles Babbage, Charles Lindbergh, Claude Shannon: information theory, Computer Numeric Control, discrete time, Dr. Strangelove, Frederick Winslow Taylor, From Mathematics to the Technologies of Life and Death, James Watt: steam engine, John von Neumann, Lewis Mumford, Menlo Park, military-industrial complex, Neil Armstrong, Norbert Wiener, Paul Samuelson, public intellectual, Ronald Reagan, scientific management, Silicon Valley, Spread Networks laid a new fibre optics cable between New York and Chicago, tacit knowledge, telerobotics, Turing machine

Presper Eckert, John Mauchly, Claude Shannon, and Jay Forrester, among others, participated in the NDRC’s research program on control systems. This is more than coincidence, for these men did not build electronic digital computers simply as calculators. Nor were they generally concerned with the questions of computability and logic that occupied mathematicians like Alan Turing and John von Neumann. Rather, they drew on longstanding traditions of control engineering, especially the technologies of fire control. My point is not to rewrite the history of computing—mathematicians of course played critical roles, as did the business machine industry—but rather to establish how the era of cyberspace and the Internet, with its emphasis on the computer as a communications device and as a vehicle for human interaction, connects to a longer history of control systems that generated computers as networked communications devices.

The Penn group’s ENIAC sought to innovate simultaneously in components and architecture, but this meant that they had difficulty selling the project and that their architecture was not as innovative as it might have been. After all, the ENIAC project’s major contribution to computing theory, John von Neumann’s landmark treatise on the stored program architecture, described not the Penn machine but its proposed successor, the EDVAC, which was never built. 94 George Stibitz succeeded in building wartime computers because he was able to base his architectural innovations on material practice, relying on an established and stable set of components, workers, and procedures to build the machines.

Journal of the AIEE 44 (1925). Hecht, Gabrielle. The Radiance of France: Nuclear Power and National Identity after World War II . Cambridge: MIT Press, 1998. Heims, Steve J. Constructing a Social Science for Postwar America: The Cybernetics Group, 1946–1953 . Cambridge: MIT Press, 1993. ———. John von Neumann and Norbert Wiener: From Mathematics to the Technologies of Life and Death . Cambridge: MIT Press, 1980 . Hewlett, E. M. “The Selsyn System of Position Indication.” General Electric Review 24 (March 1921): 210–18. Hochheiser, Sheldon. “What Makes the Picture Talk: AT&T and the Development of Sound Motion Picture Technology.”


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Ways of Being: Beyond Human Intelligence by James Bridle

Ada Lovelace, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Anthropocene, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, behavioural economics, Benoit Mandelbrot, Berlin Wall, Big Tech, Black Lives Matter, blockchain, Californian Ideology, Cambridge Analytica, carbon tax, Charles Babbage, cloud computing, coastline paradox / Richardson effect, Computing Machinery and Intelligence, corporate personhood, COVID-19, cryptocurrency, DeepMind, Donald Trump, Douglas Hofstadter, Elon Musk, experimental subject, factory automation, fake news, friendly AI, gig economy, global pandemic, Gödel, Escher, Bach, impulse control, James Bridle, James Webb Space Telescope, John von Neumann, Kickstarter, Kim Stanley Robinson, language acquisition, life extension, mandelbrot fractal, Marshall McLuhan, microbiome, music of the spheres, negative emissions, Nick Bostrom, Norbert Wiener, paperclip maximiser, pattern recognition, peer-to-peer, planetary scale, RAND corporation, random walk, recommendation engine, self-driving car, SETI@home, shareholder value, Silicon Valley, Silicon Valley ideology, speech recognition, statistical model, surveillance capitalism, techno-determinism, technological determinism, technoutopianism, the long tail, the scientific method, The Soul of a New Machine, theory of mind, traveling salesman, trolley problem, Turing complete, Turing machine, Turing test, UNCLOS, undersea cable, urban planning, Von Neumann architecture, wikimedia commons, zero-sum game

Once again, we come to the only conclusion available: the oracle is the world. It’s another quirk of computational history that one of the people in part responsible for the fixed and inflexible nature of most modern computers is also partly responsible for one of the most powerful applications of randomness. John von Neumann, a Hungarian-American physicist best known for his role in the development of the atomic bomb, was closely involved in the development of the first computers, which were based on Turing’s designs. These machines were initially developed to assist in the design of the bomb, which required complex calculations beyond the reach of existing calculating machines.

And it was a direct result of trying to get machines to implement a randomized approach to complex problem-solving. In order to fully implement the Monte Carlo method, there was one further, crucial requirement: a source of random numbers, which could not be generated by the computer itself. John von Neumann was all too aware of the failure of machines in this regard. In a paper written on the subject in 1949, he warned that ‘anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin’.8 In response to this need, the RAND Corporation – an offshoot of the US armed forces, which employed von Neumann as a consultant – built an ‘electronic roulette wheel’, which consisted of a pulse generator and a noise source, most likely a small gas-filled transistor valve similar to the kind used in ERNIE.

He too had a ‘system’ which he employed at the casino, which involved throwing dice to decide where to bet at roulette. He claimed it was successful – although excruciatingly slow – and in 1924 produced a series of prints, called the Monte Carlo Bonds, which were simultaneously conceptual artworks and legal documents, bearing the value of his winnings. 8. John von Neumann, ‘Various Techniques Used in Connection with Random Digits’ in Proceedings of a Symposium held 29, 30 June and 1 July 1949, in Los Angeles, California, under the sponsorship of the RAND Corporation and the National Bureau of Standards, with the cooperation of the Oak Ridge National Laboratory; also published in A.


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Fermat’s Last Theorem by Simon Singh

Albert Einstein, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, Augustin-Louis Cauchy, Bletchley Park, Fellow of the Royal Society, Georg Cantor, Henri Poincaré, Isaac Newton, John Conway, John von Neumann, kremlinology, probability theory / Blaise Pascal / Pierre de Fermat, RAND corporation, Rubik’s Cube, Simon Singh, Wolfskehl Prize

In 1931 Gödel published his book Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme (On Formally Undecidable Propositions in Principia Mathematica and Related Systems), which contained his so-called theorems of undecidability. When news of the theorems reached America the great mathematician John von Neumann immediately cancelled a lecture series he was giving on Hilbert’s programme and replaced the remainder of the course with a discussion of Gödel’s revolutionary work. Gödel had proved that trying to create a complete and consistent mathematical system was an impossible task. His ideas could be encapsulated in two statements.

Hardy declared that the best mathematics is largely useless, he was quick to add that this was not necessarily a bad thing: ‘Real mathematics has no effects on war. No one has yet discovered any warlike purpose to be served by the theory of numbers.’ Hardy was soon to be proved wrong. In 1944 John von Neumann co-wrote the book The Theory of Games and Economic Behavior, in which he coined the term game theory. Game theory was von Neumann’s attempt to use mathematics to describe the structure of games and how humans play them. He began by studying chess and poker, and then went on to try and model more sophisticated games such as economics.


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Massive: The Missing Particle That Sparked the Greatest Hunt in Science by Ian Sample

Albert Einstein, Arthur Eddington, cuban missile crisis, dark matter, Donald Trump, double helix, Eddington experiment, Ernest Rutherford, Gary Taubes, Higgs boson, Isaac Newton, Johannes Kepler, John Conway, John von Neumann, Kickstarter, Large Hadron Collider, Menlo Park, Murray Gell-Mann, Richard Feynman, Ronald Reagan, Stephen Hawking, Strategic Defense Initiative, synthetic biology, uranium enrichment, Yogi Berra

Its most famous resident, Albert Einstein, who had died in 1955, had spent the last twenty-five years of his life there, trying to explain how the forces of nature were born. The Austrian-American logician Kurt Gödel was still there, redefining the limits of human knowledge. He and Einstein had been friends, though he had vexed Einstein by pointing out that his famous theories allowed time travel to be possible.21 The father of modern computing, John von Neumann, was also at the institute, turning the mathematics of poker into a political strategy to win the Cold War.22 Robert Oppenheimer, the towering figure who had led the Manhattan Project to build the atomic bomb, had become head of the institute in 1946, only adding to the intimidating aura of the place.

The Higgs boson is the quantum of the remaining neutral component field. 21 For more on Gödel’s work, see Thinking about Gödel and Turing: Essays on Complexity, 1970-2007, by Gregory J. Chaitin, World Scientific, 2007. 22 For more on von Neumann’s work on game theory, see Prisoner’s Dilemma: John von Neumann, Game Theory and the Puzzle of the Bomb, by William Poundstone, Anchor Books, 1993. 23 Interview with the author, August 2008. 24 Interview with the author, August 2007. 25 As recalled in an interview with the author, August 2008. 26 See “Conserved Currents and Associated Symmetries: Goldstone’s Theorem,” by Daniel Kastler, Derek W.


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Ten Billion Tomorrows: How Science Fiction Technology Became Reality and Shapes the Future by Brian Clegg

Albert Einstein, Alvin Toffler, anthropic principle, Apollo 11, Brownian motion, call centre, Carrington event, Charles Babbage, combinatorial explosion, don't be evil, Dr. Strangelove, Ernest Rutherford, experimental subject, Future Shock, game design, gravity well, Higgs boson, hive mind, invisible hand, Isaac Newton, Johannes Kepler, John von Neumann, Kickstarter, Large Hadron Collider, machine translation, Neil Armstrong, Nick Bostrom, nuclear winter, pattern recognition, quantum entanglement, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Schrödinger's Cat, Search for Extraterrestrial Intelligence, silicon-based life, speech recognition, stem cell, Stephen Hawking, Steve Jobs, Turing test

To have spread well across the galaxy, probes of this kind would have to have started out many thousands of years ago, and it’s entirely possible that if one did visit the Earth, it wouldn’t arrive during the few thousand years so far when human beings would have been able to record its visit. Such devices, sometimes called von Neumann probes after the mathematician John von Neumann who worked on the concept, do also have a practical problem that to make an easily replicable device mechanically would require it to be simple—and yet the task it has to perform, refining ores, producing complex machinery and electronics, is very complex. We simply couldn’t build a device that could replicate itself from raw materials like this at all, let alone one that then had the ability to power itself out of the Earth’s gravity well and navigate between the stars.

Babbage speculated that his mechanical programmable computer, the Analytical Engine, which was designed but never built, would be able to play chess, while Turing wrote a simple program for chess playing that was only ever executed by hand. More impetus was given by information theorist Claude Shannon in the 1950s. Shannon made use of John von Neumann’s minimax algorithm, which would give a score to different possible moves and used it to calculate what was thought to be the optimum strategy. Shannon never produced a workable program, but by the time 2001 was filmed, there were crude chess-playing programs running on mainframe computers, and in 1973, David Slate and Larry Atkin wrote Chess 4.0, the first truly effective software that was able to make use of a computer’s strengths and play a game that could beat most everyday players.


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Richard Dawkins: How a Scientist Changed the Way We Think by Alan Grafen; Mark Ridley

Alfred Russel Wallace, Arthur Eddington, bioinformatics, Charles Babbage, cognitive bias, computer age, Computing Machinery and Intelligence, conceptual framework, Dava Sobel, double helix, Douglas Hofstadter, Easter island, epigenetics, Fellow of the Royal Society, Haight Ashbury, interchangeable parts, Isaac Newton, Johann Wolfgang von Goethe, John von Neumann, loose coupling, Murray Gell-Mann, Necker cube, phenotype, profit maximization, public intellectual, Ronald Reagan, Stephen Hawking, Steven Pinker, the scientific method, theory of mind, Thomas Kuhn: the structure of scientific revolutions, Yogi Berra, zero-sum game

I am not concerned here with the psychology of motives.’14 Dawkins’ brilliant application of mentalistic behaviorism—what I call the intentional stance—to evolutionary biology was, like my own coinage, an articulation of ideas that were already proving themselves in the work of many other theorists. We are both clari-fiers and unifiers of practices and attitudes pioneered by others, and we share a pantheon: Alan Turing and John von Neumann on the one hand, and Bill Hamilton, John Maynard Smith, George Williams, and Bob Trivers on the other. We see computer science and evolutionary theory fitting together in excellent harmony; it’s algorithms all the way down. Dawkins and I have both had to defend our perspective against those who cannot fathom—or abide—this strategic approach to such deep matters.

He was particularly interested in accounting for the tendency of spiral patterns in many plant structures to obey the Fibonacci sequence (e.g. if you count the number of whirls running clockwise on a pine cone and the number running anticlockwise, the two numbers will be consecutive terms in Fibonacci’s famous sequence of integers: 0, 1, 1, 2, 3, 5, 8, 12, ...). At the same time, John von Neumann, one of history’s great polymaths and the man responsible for game theory and the architecture of the modern computer among many other things typically considered to lie far from the muddy field of biology, worked on the problem of selfreplication:2 over evolutionary time, simple life-forms have given rise to more complicated creatures, but how, von Neumann asked, could a machine (like a dog or an amoeba or a robot) make a more complex version of itself?


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Is God a Mathematician? by Mario Livio

Albert Einstein, Alvin Toffler, Antoine Gombaud: Chevalier de Méré, Brownian motion, cellular automata, correlation coefficient, correlation does not imply causation, cosmological constant, Dava Sobel, double helix, Edmond Halley, Eratosthenes, Future Shock, Georg Cantor, Gerolamo Cardano, Gregor Mendel, Gödel, Escher, Bach, Henri Poincaré, Isaac Newton, Johannes Kepler, John von Neumann, music of the spheres, Myron Scholes, Plato's cave, probability theory / Blaise Pascal / Pierre de Fermat, Russell's paradox, seminal paper, Thales of Miletus, The Design of Experiments, the scientific method, traveling salesman

Russell’s paradox was bypassed in this theory by a careful choice of construction principles that eliminated contradictory ideas such as “the set of all sets.” Zermelo’s scheme was further augmented in 1922 by the Israeli mathematician Abraham Fraenkel (1891–1965) to form what has become known as the Zermelo-Fraenkel set theory (other important changes were added by John von Neumann in 1925). Things would have been nearly perfect (consistency was yet to be demonstrated) were it not for some nagging suspicions. There was one axiom—the axiom of choice—that just like Euclid’s famous “fifth” was causing mathematicians serious heartburn. Put simply, the axiom of choice states: If X is a collection (set) of nonempty sets, then we can choose a single member from each and every set in X to form a new set Y.

I don’t see any reason why we should have less confidence in this kind of perception, i.e., in mathematical intuition, than in sense perception. By an ironic twist of fate, just as the formalists were getting ready for their victory march, Kurt Gödel—an avowed Platonist—came and rained on the parade of the formalist program. The famous mathematician John von Neumann (1903–57), who was lecturing on Hilbert’s work at the time, canceled the rest of his planned course and devoted the remaining time to Gödel’s findings. Gödel the man was every bit as complex as his theorems. In 1940, he and his wife Adele fled Nazi Austria so he could take up a position at the Institute for Advanced Study in Princeton, New Jersey.


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Sun in a Bottle: The Strange History of Fusion and the Science of Wishful Thinking by Charles Seife

Albert Einstein, anti-communist, Brownian motion, correlation does not imply causation, Dmitri Mendeleev, Dr. Strangelove, Ernest Rutherford, Fellow of the Royal Society, Gary Taubes, Isaac Newton, ITER tokamak, John von Neumann, Mikhail Gorbachev, Norman Macrae, Project Plowshare, Richard Feynman, Ronald Reagan, the scientific method, Yom Kippur War

Other facilities, such as one at Oak Ridge in Tennessee and another at Hanford in Washington, were crucial to figuring out the best way to separate bombworthy uranium-235 from the much more common uranium-238 and how to manufacture plutonium-239.2 However, the big minds roamed at Los Alamos: Oppenheimer, Hans Bethe, Richard Feynman, Stanislaw Ulam, John von Neumann, Enrico Fermi, and Edward Teller. Teller, a Hungarian émigré and, arguably, a better theoretician than Oppenheimer, was brought to the University of Chicago in mid-1942 by the Manhattan Project just as it was getting under way. When Teller arrived, nobody assigned him a task, so he set to work trying to design the ultimate weapon, more powerful even than the one the project’s scientists were trying to build.

“British-U.S. Data on Hydrogen Due.” New York Times, 13 January 1958. ———. “Briton 90% Sure Fusion Occurred.” New York Times, 25 January 1958. ———. “Butler Affirms Atom Fusion Lead.” New York Times, 31 January 1958. ———. “H-Bomb Untamed, Britain Admits.” New York Times, 17 May 1958. Macrae, Norman. John von Neumann. New York: Pantheon, 1992. Maddox, John. “What to Say about Cold Fusion.” Nature 338 (27 April 1989): 701. Magnetic Fusion Energy Engineering Act of 1980. Public Law 96-386 (7 October 1980). Malakoff, David. “DOE Slams Livermore for Hiding NIF Problems.” Science 285 (10 September 1999): 1647.


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Hacker's Delight by Henry S. Warren

Charles Babbage, Donald Knuth, Free Software Foundation, John von Neumann

[Bern] Bernstein, Robert. "Multiplication by Integer Constants." Software—Practice and Experience 16, 7 (July 1986), 641-652. [BGN] Burks, Arthur W., Goldstine, Herman H., and von Neumann, John. "Preliminary Discussion of the Logical Design of an Electronic Computing Instrument, Second Edition" (1947). In Papers of John von Neumann on Computing and Computing Theory, Volume 12 in the Charles Babbage Institute Reprint Series for the History of Computing, MIT Press, 1987. [CJS] Stephenson, Christopher J. Private communication. [Cohen] These rules were pointed out by Norman H. Cohen. [Cut] Cutland, Nigel J. Computability: An Introduction to Recursive Function Theory.

Oxford University Press, 1960. [IBM] From an IBM programming course, 1961. [Irvine] Irvine, M. M. "Early Digital Computers at Bell Telephone Laboratories." IEEE Annals of the History of Computing 23, 3 (July-September 2001), 22-42. [JVN] von Neumann, John. "First Draft of a Report on the EDVAC." In Papers of John von Neumann on Computing and Computing Theory, Volume 12 in the Charles Babbage Institute Reprint Series for the History of Computing, MIT Press, 1987. [Ken] Found in a GNU C compiler for the RS/6000 that was ported by Richard Kenner. He attributes this to a 1992 PLDI conference paper by him and Torbjörn Granlund.


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E=mc2: A Biography of the World's Most Famous Equation by David Bodanis

Albert Einstein, Arthur Eddington, Berlin Wall, British Empire, dark matter, Eddington experiment, Ernest Rutherford, Erwin Freundlich, Fellow of the Royal Society, Henri Poincaré, Isaac Newton, John von Neumann, Kickstarter, Mercator projection, Nelson Mandela, pre–internet, Richard Feynman, Silicon Valley, Silicon Valley startup, Stephen Hawking, Thorstein Veblen, time dilation

He nurtured the first theorists who proposed implosion; he assembled the right explosives experts; as the project grew to a level that under anyone else’s supervision it might have fallen apart in a mess of squabbling egos, he deftly manipulated the participants so that all the different groups involved worked together in parallel. At one point he had the top U.S. explosives expert, and the top UK explosives expert, and the Hungarian John von Neumann—the quickest mathematician anyone had met, who would also help create the computer in his long career—and a host of other nationalities all working on it. He even had Feynman joining in! The one prima donna who might have destroyed the effort was the embarrassingly egocentric Hungarian physicist Edward Teller.

Sticking out of the bomb’s back, near the spinning fins, were a number of whiplike thin radio antennae. Those collected the returning radio signals, and used the time lag each took 163 2 adulthood to return as a way of measuring the height remaining to the ground. At 1,900 feet the last rebounded radio signal arrived. John von Neumann and others had calculated that a bomb exploding much higher would dissipate much of its heat in the open air; exploding much lower, it would dig a huge crater in the ground. At just under 2,000 feet the height would be ideal. An electric impulse lit cordite sacs, producing a conventional artillery blast.


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Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy by George Gilder

23andMe, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AlphaGo, AltaVista, Amazon Web Services, AOL-Time Warner, Asilomar, augmented reality, Ben Horowitz, bitcoin, Bitcoin Ponzi scheme, Bletchley Park, blockchain, Bob Noyce, British Empire, Brownian motion, Burning Man, business process, butterfly effect, carbon footprint, cellular automata, Claude Shannon: information theory, Clayton Christensen, cloud computing, computer age, computer vision, crony capitalism, cross-subsidies, cryptocurrency, Danny Hillis, decentralized internet, deep learning, DeepMind, Demis Hassabis, disintermediation, distributed ledger, don't be evil, Donald Knuth, Donald Trump, double entry bookkeeping, driverless car, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, fake news, fault tolerance, fiat currency, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, floating exchange rates, Fractional reserve banking, game design, Geoffrey Hinton, George Gilder, Google Earth, Google Glasses, Google Hangouts, index fund, inflation targeting, informal economy, initial coin offering, Internet of things, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, Jim Simons, Joan Didion, John Markoff, John von Neumann, Julian Assange, Kevin Kelly, Law of Accelerating Returns, machine translation, Marc Andreessen, Mark Zuckerberg, Mary Meeker, means of production, Menlo Park, Metcalfe’s law, Money creation, money: store of value / unit of account / medium of exchange, move fast and break things, Neal Stephenson, Network effects, new economy, Nick Bostrom, Norbert Wiener, Oculus Rift, OSI model, PageRank, pattern recognition, Paul Graham, peer-to-peer, Peter Thiel, Ponzi scheme, prediction markets, quantitative easing, random walk, ransomware, Ray Kurzweil, reality distortion field, Recombinant DNA, Renaissance Technologies, Robert Mercer, Robert Metcalfe, Ronald Coase, Ross Ulbricht, Ruby on Rails, Sand Hill Road, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Singularitarianism, Skype, smart contracts, Snapchat, Snow Crash, software is eating the world, sorting algorithm, South Sea Bubble, speech recognition, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, stochastic process, Susan Wojcicki, TED Talk, telepresence, Tesla Model S, The Soul of a New Machine, theory of mind, Tim Cook: Apple, transaction costs, tulip mania, Turing complete, Turing machine, Vernor Vinge, Vitalik Buterin, Von Neumann architecture, Watson beat the top human players on Jeopardy!, WikiLeaks, Y Combinator, zero-sum game

In opposition to the foolish ignorabimus our slogan shall be: ‘We must know, we will know’ ”—Wir müssen wissen, wir werden wissen—a declaration that was inscribed on his tombstone.7 Preceding the conference was a smaller three-day meeting on the “Epistemology of the Exact Sciences” addressed by the rising mathematical stars Rudolf Carnap, a set theorist; Arend Heyting, a mathematical philosopher; and John von Neumann, a polymathic prodigy and Hilbert’s assistant. All were soldiers in Hilbert’s epistemological campaign, and all, like Hilbert, expected the pre-conference to be a warmup for the triumphalist celebration of the main conference. After the pre-conference ended, however, everyone might as well have gone home.

In developing his proof, Gödel (1906–1978) invented a mathematical machine that used numbers to embody axioms and thus anticipated the discoveries of computer science. By showing that mathematics could not be hermetically sealed or physically determinist, Gödel opened the way to postmodern mathematics: a mathematics of software and creativity. John von Neumann (1903–1957) was the first person to appreciate and publicize the importance of Gödel’s demonstration in 1931 that mathematical statements can be true but unprovable. As von Neumann saw, Gödel’s proof depended on his invention of a mathematical “machine” that used numbers to encode and prove algorithms also expressed in numbers.


pages: 625 words: 167,349

The Alignment Problem: Machine Learning and Human Values by Brian Christian

Albert Einstein, algorithmic bias, Alignment Problem, AlphaGo, Amazon Mechanical Turk, artificial general intelligence, augmented reality, autonomous vehicles, backpropagation, butterfly effect, Cambridge Analytica, Cass Sunstein, Claude Shannon: information theory, computer vision, Computing Machinery and Intelligence, data science, deep learning, DeepMind, Donald Knuth, Douglas Hofstadter, effective altruism, Elaine Herzberg, Elon Musk, Frances Oldham Kelsey, game design, gamification, Geoffrey Hinton, Goodhart's law, Google Chrome, Google Glasses, Google X / Alphabet X, Gödel, Escher, Bach, Hans Moravec, hedonic treadmill, ImageNet competition, industrial robot, Internet Archive, John von Neumann, Joi Ito, Kenneth Arrow, language acquisition, longitudinal study, machine translation, mandatory minimum, mass incarceration, multi-armed bandit, natural language processing, Nick Bostrom, Norbert Wiener, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, OpenAI, Panopticon Jeremy Bentham, pattern recognition, Peter Singer: altruism, Peter Thiel, precautionary principle, premature optimization, RAND corporation, recommendation engine, Richard Feynman, Rodney Brooks, Saturday Night Live, selection bias, self-driving car, seminal paper, side project, Silicon Valley, Skinner box, sparse data, speech recognition, Stanislav Petrov, statistical model, Steve Jobs, strong AI, the map is not the territory, theory of mind, Tim Cook: Apple, W. E. B. Du Bois, Wayback Machine, zero-sum game

Other material is drawn from oral histories of Pitts’s contemporaries, particularly Jerome (Jerry) Lettvin in Anderson and Rosenfeld, Talking Nets, as well as the essays and recollections in McCulloch, The Collected Works of Warren S. McCulloch. For other accounts of Pitts’s life, see, e.g., Smalheiser, “Walter Pitts”; Easterling, “Walter Pitts”; and Gefter, “The Man Who Tried to Redeem the World with Logic.” Further details exist in biographies of McCulloch, Norbert Wiener, and the cybernetics group—e.g., Heims, John von Neumann and Norbert Wiener and The Cybernetics Group, and Conway and Siegelman, Dark Hero of the Information Age. 2. Whitehead and Russell, Principia Mathematica. 3. Thanks to the staff at the Bertrand Russell Archives at McMaster University for their help in attempting to locate a copy of this letter; unfortunately, no extant copy is known. 4.

Some of the roots of this thinking predate McCulloch’s work with Pitts; see, e.g., McCulloch, “Recollections of the Many Sources of Cybernetics.” 8. See Piccinini, “The First Computational Theory of Mind and Brain,” and Lettvin, Introduction to McCulloch, The Collected Works of Warren S. McCulloch. 9. John von Neumann’s 1945 EDVAC report, the first description ever written of a stored-program computer, will contain—for all its 101 pages—a single citation: McCulloch and Pitts, 1943. (See Neumann, “First Draft of a Report on the EDVAC.” Von Neumann actually misspells it in the original text: “Following W. S.

Hastie, Trevor, and Robert Tibshirani. “Generalized Additive Models.” Statistical Science 1, no. 3 (1986): 297–318. Hebb, Donald Olding. The Organization of Behavior: A Neuropsychological Theory. New York: John Wiley & Sons, 1949. Heims, Steve Joshua. The Cybernetics Group. MIT Press, 1991. ———. John von Neumann and Norbert Wiener. MIT Press, 1980. Heine, Steven J., Timothy Takemoto, Sophia Moskalenko, Jannine Lasaleta, and Joseph Henrich. “Mirrors in the Head: Cultural Variation in Objective Self-Awareness.” Personality and Social Psychology Bulletin 34, no. 7 (2008): 879–87. Hendrycks, Dan, Mantas Mazeika, and Thomas Dietterich.


pages: 317 words: 101,074

The Road Ahead by Bill Gates, Nathan Myhrvold, Peter Rinearson

Albert Einstein, Apple's 1984 Super Bowl advert, Berlin Wall, Bill Gates: Altair 8800, Bob Noyce, Bonfire of the Vanities, business process, California gold rush, Charles Babbage, Claude Shannon: information theory, computer age, Donald Knuth, first square of the chessboard, first square of the chessboard / second half of the chessboard, glass ceiling, global village, informal economy, invention of movable type, invention of the printing press, invention of writing, John von Neumann, knowledge worker, medical malpractice, Mitch Kapor, new economy, packet switching, popular electronics, Richard Feynman, Ronald Reagan, SimCity, speech recognition, Steve Ballmer, Steve Jobs, Steven Pinker, Ted Nelson, telemarketer, the scientific method, The Wealth of Nations by Adam Smith, transaction costs, Turing machine, Turing test, Von Neumann architecture

For the next century mathematicians worked with the ideas Babbage had outlined and finally, by the mid-1940s, an electronic computer was built based on the principles of his Analytical Engine. It is hard to sort out the paternity of the modern computer, because much of the thinking and work was done in the United States and Britain during World War II under the cloak of wartime secrecy. Three major contributors were Alan Turing, Claude Shannon, and John von Neumann. In the mid-1930s, Alan Turing, like Babbage a superlative Cambridge-trained British mathematician, proposed what is known today as a Turing machine. It was his version of a completely general-purpose calculating machine that could be instructed to work with almost any kind of information. In the late 1930s, when Claude Shannon was still a student, he demonstrated that a machine executing logical instructions could manipulate information.

If this is true, it gives new meaning to the term "bugs" for the little glitches that can plague computer hardware or software. When all the tubes were working, a staff of engineers could set up ENIAC to solve a problem by laboriously plugging in 6,000 cables by hand. To make it perform another function, the staff had to reconfigure the cabling—every time. John von Neumann, a brilliant Hungarian-born American, who is known for many things, including the development of game theory and his contributions to nuclear weaponry, is credited with the leading role in figuring out a way around this problem. He created the paradigm that all digital computers still follow.


pages: 385 words: 98,015

Einstein's Unfinished Revolution: The Search for What Lies Beyond the Quantum by Lee Smolin

adjacent possible, Albert Einstein, Brownian motion, Claude Shannon: information theory, cosmic microwave background, cosmological constant, Ernest Rutherford, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Murray Gell-Mann, mutually assured destruction, quantum entanglement, Richard Feynman, Richard Florida, Schrödinger's Cat, Stephen Hawking, Stuart Kauffman, the scientific method, Turing machine

A complete elucidation of one and the same object may require diverse points of view which defy a unique description. Indeed, strictly speaking, the conscious analysis of any concept stands in a relation of exclusion to its immediate application.4 Other quantum luminaries, such as Wolfgang Pauli, a wunderkind who published a textbook on general relativity when he was twenty-one, and John von Neumann, a Hungarian mathematician who is famous for his inventions in a broad range of fields, from the architecture of computers to the mathematics of quantum theory, taught variants of these anti-realist philosophies. Their views differed in emphasis, but anything written by them was classified as part of the “Copenhagen interpretation” of quantum mechanics.

There were only Copenhagen textbooks. These either ignored the foundational issues with the theory or presented a confident assertion that all questions that were meaningful had already been answered by Bohr and Heisenberg. One important reason anti-realism triumphed was that the mathematician John von Neumann published a proof he claimed showed there could not be a consistent alternative to quantum mechanics. This was published a few years after the Solvay conference in a book on the mathematical structure of quantum mechanics. This claim had to be wrong, as it implied de Broglie’s pilot wave theory had to be inconsistent, which it wasn’t.


pages: 340 words: 97,723

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity by Amy Webb

"Friedman doctrine" OR "shareholder theory", Ada Lovelace, AI winter, air gap, Airbnb, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic bias, AlphaGo, Andy Rubin, artificial general intelligence, Asilomar, autonomous vehicles, backpropagation, Bayesian statistics, behavioural economics, Bernie Sanders, Big Tech, bioinformatics, Black Lives Matter, blockchain, Bretton Woods, business intelligence, Cambridge Analytica, Cass Sunstein, Charles Babbage, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, Computing Machinery and Intelligence, CRISPR, cross-border payments, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, Demis Hassabis, Deng Xiaoping, disinformation, distributed ledger, don't be evil, Donald Trump, Elon Musk, fail fast, fake news, Filter Bubble, Flynn Effect, Geoffrey Hinton, gig economy, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Herman Kahn, high-speed rail, Inbox Zero, Internet of things, Jacques de Vaucanson, Jeff Bezos, Joan Didion, job automation, John von Neumann, knowledge worker, Lyft, machine translation, Mark Zuckerberg, Menlo Park, move fast and break things, Mustafa Suleyman, natural language processing, New Urbanism, Nick Bostrom, one-China policy, optical character recognition, packet switching, paperclip maximiser, pattern recognition, personalized medicine, RAND corporation, Ray Kurzweil, Recombinant DNA, ride hailing / ride sharing, Rodney Brooks, Rubik’s Cube, Salesforce, Sand Hill Road, Second Machine Age, self-driving car, seminal paper, SETI@home, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart cities, South China Sea, sovereign wealth fund, speech recognition, Stephen Hawking, strong AI, superintelligent machines, surveillance capitalism, technological singularity, The Coming Technological Singularity, the long tail, theory of mind, Tim Cook: Apple, trade route, Turing machine, Turing test, uber lyft, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero day

Rather than focusing on the machine as hardware and the program as software, they imagined a new kind of symbiotic system capable of ingesting vast amounts of data, just like we humans do. Computers weren’t yet powerful enough to test this theory—but the paper did inspire others to start working toward a new kind of intelligent computer system. The link between intelligent computer systems and autonomous decision-making became clearer once John von Neumann, the Hungarian-American polymath with specializations in computer science, physics, and math, published a massive treatise of applied math. Cowritten with Princeton economist Oskar Morgenstern in 1944, the 641-page book explained, with painstaking detail, how the science of game theory revealed the foundation of all economic decisions.

The current AI architecture has been good enough to build products with artificial narrow intelligence, like the spam filter in Gmail or Apple’s “visual voicemail” transcription service. But it must also pursue artificial general intelligence (AGI), a longer-term play that is now visible on the horizon. And that requires customized AI hardware. The reason AGI requires customized hardware has something to do with John von Neumann, the computer scientist previously mentioned who developed the theory behind the architecture of modern computers. Remember, during von Neumann’s time, computers were fed separate programs and data for processing—in his architecture, computer programs and data were both held in the memory of the machine.


pages: 364 words: 101,286

The Misbehavior of Markets: A Fractal View of Financial Turbulence by Benoit Mandelbrot, Richard L. Hudson

Alan Greenspan, Albert Einstein, asset allocation, Augustin-Louis Cauchy, behavioural economics, Benoit Mandelbrot, Big bang: deregulation of the City of London, Black Monday: stock market crash in 1987, Black-Scholes formula, British Empire, Brownian motion, business cycle, buy and hold, buy low sell high, capital asset pricing model, carbon-based life, discounted cash flows, diversification, double helix, Edward Lorenz: Chaos theory, electricity market, Elliott wave, equity premium, equity risk premium, Eugene Fama: efficient market hypothesis, Fellow of the Royal Society, financial engineering, full employment, Georg Cantor, Henri Poincaré, implied volatility, index fund, informal economy, invisible hand, John Meriwether, John von Neumann, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, market bubble, market microstructure, Myron Scholes, new economy, paper trading, passive investing, Paul Lévy, Paul Samuelson, plutocrats, power law, price mechanism, quantitative trading / quantitative finance, Ralph Nelson Elliott, RAND corporation, random walk, risk free rate, risk tolerance, Robert Shiller, short selling, statistical arbitrage, statistical model, Steve Ballmer, stochastic volatility, transfer pricing, value at risk, Vilfredo Pareto, volatility smile

In 1945, he dropped out of France’s most prestigious school, the École Normale Supérieure, on the second day, to enroll at the less-exalted but more appropriate École Polytechnique. He proceeded to Caltech; then—after a Ph.D. in Paris—to MIT; then to the Institute for Advanced Study in Princeton, as the last post-doc to study with the great Hungarian-born mathematician, John von Neumann; then to Geneva and back to Paris for a time. Atypically for a scientist in those days, Mandelbrot ended up working, not in a university lecture hall, but in an industrial laboratory, IBM Research, up the Hudson River from Manhattan. At that time IBM’s bosses were drawing into that lab and its branches a number of brainy, unpredictable people, not doubting they would do something brilliant for the company.

I recall that by the end of one such series, I was his sole auditor; we could as easily have quit the auditorium and adjourned to his office for a chat. At seventy-eight, he received belated recognition by election to France’s Académie des Sciences. But he was ever an anomaly. As a later teacher of mine, John von Neumann, told me: “I think I understand how every other mathematician operates, but Lévy is like a visitor from a strange planet. He seems to have his own private methods of arriving at the truth, which leave me ill at ease.” Lévy did not “arrive at” probability theory until he was nearly forty, when he was asked shortly after World War I to lecture on targeting errors in gunnery.


pages: 282 words: 89,436

Einstein's Dice and Schrödinger's Cat: How Two Great Minds Battled Quantum Randomness to Create a Unified Theory of Physics by Paul Halpern

Albert Einstein, Albert Michelson, Arthur Eddington, Brownian motion, clockwork universe, cosmological constant, dark matter, double helix, Eddington experiment, Ernest Rutherford, Fellow of the Royal Society, Higgs boson, Isaac Newton, Johannes Kepler, John von Neumann, Large Hadron Collider, lone genius, luminiferous ether, Murray Gell-Mann, New Journalism, orbital mechanics / astrodynamics, quantum entanglement, Richard Feynman, Schrödinger's Cat, seminal paper, The Present Situation in Quantum Mechanics, time dilation

By touching the structure, it is in some sense taking a measurement. The house of cards topples over in one of the directions, collapsing into one of its constituent eigenstates. The process of measurement has triggered a collapse from the superposition into a single position. Hungarian mathematician John von Neumann would later show that all quantum processes obeyed one of two types of dynamics: the continuous, deterministic evolution governed by a wave equation (either the Schrödinger equation or a relativistic version such as the Dirac equation) and the discrete, probabilistic repositioning associated with wavefunction collapse.

Causality, he argued, was a local process involving interactions between adjacent entities, spreading through space from one point to the next at the speed of light or slower. Distant things must be treated as physically distinct, not as a linked system. Otherwise a kind of “telepathy” could exist between an electron on Earth and one on, say, Mars. How could each immediately “know” what the other is doing? By then, John von Neumann had formalized the notion of wavefunction collapse, originally suggested by Heisenberg. In that formalism, a particle’s wavefunction can be expressed in terms of either position eigenstates or momentum eigenstates, but not both at once. It is something like slicing an egg. You could slice it along its length or across its width, but unless you want it to be diced instead of sliced, you’d only do one or the other.


Fifty Challenging Problems in Probability With Solutions by Frederick Mosteller

Isaac Newton, John von Neumann, prisoner's dilemma, RAND corporation, stochastic process

As is not hard to see, this can occur only if y = x, in which case he can win y with a single bold gamble with the probability w given by (2). 57 37 The problem of an exact upper bound and optimum strategies for the gambler in Red-and-Black who wants to win an amount different from x is more difficult and will not be entered into here. 38. The Thick Coin How thick should a coin be to have a ! chance of landing on edge? Solution for The Thick Coin On first hearing this question, the late great mathematician, John von Neumann, was unkind enough to solve it-including a 3-decimal answerin his head in 20 seconds in the presence of some unfortunates who had labored much longer. ~ '-J- Edge This problem has no definite answer without some simplifying conditions. The elasticity of the coin, the intensity with which it is tossed, and the properties of the surface on which it lands combine to make the reallife question an empirical one.


The Art of Computer Programming by Donald Ervin Knuth

Abraham Wald, Brownian motion, Charles Babbage, complexity theory, correlation coefficient, Donald Knuth, Eratosthenes, G4S, Georg Cantor, information retrieval, Isaac Newton, iterative process, John von Neumann, Louis Pasteur, mandelbrot fractal, Menlo Park, NP-complete, P = NP, Paul Erdős, probability theory / Blaise Pascal / Pierre de Fermat, RAND corporation, random walk, sorting algorithm, Turing machine, Y2K

Fundamental Constants (octal) 727 3. Harmonic Numbers, Bernoulli Numbers, Fibonacci Numbers . . . 728 Appendix B — Index to Notations 730 Index and Glossary 735 CHAPTER THREE RANDOM NUMBERS Any one who considers arithmetical methods of producing random digits is, of course, in a state of sin. — JOHN VON NEUMANN A951) Lest men suspect your tale untrue, Keep probability in view. — JOHN GAY A727) There wanted not some beams of light to guide men in the exercise of their Stocastick faculty. — JOHN OWEN A662) 3.1. INTRODUCTION Numbers that are "chosen at random" are useful in many different kinds of applications.

George Marsaglia helped resuscitate random tables in 1995 by preparing a demonstration disk that contained 650 random megabytes, generated by combining the output of a noise-diode circuit with deterministically scrambled rap music. (He called it "white and black noise.") The inadequacy of mechanical methods in the early days led to an interest in the production of random numbers using a computer's ordinary arithmetic operations. John von Neumann first suggested this approach in about 1946; his idea was to take the square of the previous random number and to extract the middle digits. For example, if we are generating 10-digit numbers and the previous value was 5772156649, we square it to get 33317792380594909201; the next number is therefore 7923805949.

A new uniform deviate U is generated whenever we need it. These numbers are usually represented in a computer word with the radix point assumed at the left. 3.4.1. Numerical Distributions This section summarizes the best techniques known for producing numbers from various important distributions. Many of the methods were originally suggested by John von Neumann in the early 1950s, and they have gradually been improved upon by other people, notably George Marsaglia, J. H. Ahrens, and U. Dieter. A. Random choices from a finite set. The simplest and most common type of distribution required in practice is a random integer. An integer between 0 and 7 can be extracted from three bits of U on a binary computer; in such a case, these bits should be extracted from the most significant (left-hand) part of the computer word, since the least significant bits produced by many random number generators are not sufficiently random.


pages: 118 words: 35,663

Smart Machines: IBM's Watson and the Era of Cognitive Computing (Columbia Business School Publishing) by John E. Kelly Iii

AI winter, book value, call centre, carbon footprint, Computing Machinery and Intelligence, crowdsourcing, demand response, discovery of DNA, disruptive innovation, Erik Brynjolfsson, Fairchild Semiconductor, future of work, Geoffrey West, Santa Fe Institute, global supply chain, Great Leap Forward, Internet of things, John von Neumann, Large Hadron Collider, Mars Rover, natural language processing, optical character recognition, pattern recognition, planetary scale, RAND corporation, RFID, Richard Feynman, smart grid, smart meter, speech recognition, TED Talk, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!

People used them to organize data and make calculations that were helpful in everything from conducting a national population census to tracking the performance of a company’s sales force. The programmable computing era—today’s technologies—emerged in the 1940s. Programmable machines are still based on a design laid out by the Hungarian American mathematician John von Neumann. Electronic devices governed by software programs perform calculations, execute logical sequences of steps, and store information using millions of zeros and ones. Scientists built the first such computers for use in decrypting encoded messages in wartime. Successive generations of computing technology have enabled everything from space exploration to global manufacturing-supply chains to the Internet.


pages: 484 words: 104,873

Rise of the Robots: Technology and the Threat of a Jobless Future by Martin Ford

3D printing, additive manufacturing, Affordable Care Act / Obamacare, AI winter, algorithmic management, algorithmic trading, Amazon Mechanical Turk, artificial general intelligence, assortative mating, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Bernie Madoff, Bill Joy: nanobots, bond market vigilante , business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, Charles Babbage, Chris Urmson, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, commoditize, computer age, creative destruction, data science, debt deflation, deep learning, deskilling, digital divide, disruptive innovation, diversified portfolio, driverless car, Erik Brynjolfsson, factory automation, financial innovation, Flash crash, Ford Model T, Fractional reserve banking, Freestyle chess, full employment, general purpose technology, Geoffrey Hinton, Goldman Sachs: Vampire Squid, Gunnar Myrdal, High speed trading, income inequality, indoor plumbing, industrial robot, informal economy, iterative process, Jaron Lanier, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Kenneth Arrow, Khan Academy, Kiva Systems, knowledge worker, labor-force participation, large language model, liquidity trap, low interest rates, low skilled workers, low-wage service sector, Lyft, machine readable, machine translation, manufacturing employment, Marc Andreessen, McJob, moral hazard, Narrative Science, Network effects, new economy, Nicholas Carr, Norbert Wiener, obamacare, optical character recognition, passive income, Paul Samuelson, performance metric, Peter Thiel, plutocrats, post scarcity, precision agriculture, price mechanism, public intellectual, Ray Kurzweil, rent control, rent-seeking, reshoring, RFID, Richard Feynman, Robert Solow, Rodney Brooks, Salesforce, Sam Peltzman, secular stagnation, self-driving car, Silicon Valley, Silicon Valley billionaire, Silicon Valley startup, single-payer health, software is eating the world, sovereign wealth fund, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Steven Pinker, strong AI, Stuxnet, technological singularity, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Coming Technological Singularity, The Future of Employment, the long tail, Thomas L Friedman, too big to fail, Tragedy of the Commons, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, union organizing, Vernor Vinge, very high income, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, women in the workforce

Indeed, the arc of progress can be traced back in time at least as far as Charles Babbage’s mechanical difference engine in the early seventeenth century. The innovations that have resulted in fantastic wealth and influence in today’s information economy, while certainly significant, do not really compare in importance to the groundbreaking work done by pioneers like Alan Turing or John von Neumann. The difference is that even incremental advances are now able to leverage that extraordinary accumulated account balance. In a sense, the successful innovators of today are a bit like the Boston Marathon runner who in 1980 famously snuck into the race only half a mile from the finish line. Of course, all innovators stand on the shoulders of those who came before them.

In the words of futurist and inventor Ray Kurzweil, it would “rupture the fabric of history” and usher in an event—or perhaps an era—that has come to be called “the Singularity.” The Singularity The first application of the term “singularity” to a future technology-driven event is usually credited to computer pioneer John von Neumann, who reportedly said sometime in the 1950s that “ever accelerating progress . . . gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.”5 The theme was fleshed out in 1993 by San Diego State University mathematician Vernor Vinge, who wrote a paper entitled “The Coming Technological Singularity.”


pages: 389 words: 109,207

Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street by William Poundstone

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", Albert Einstein, anti-communist, asset allocation, Bear Stearns, beat the dealer, Benoit Mandelbrot, Black Monday: stock market crash in 1987, Black-Scholes formula, Bletchley Park, Brownian motion, buy and hold, buy low sell high, capital asset pricing model, Claude Shannon: information theory, computer age, correlation coefficient, diversified portfolio, Edward Thorp, en.wikipedia.org, Eugene Fama: efficient market hypothesis, financial engineering, Henry Singleton, high net worth, index fund, interest rate swap, Isaac Newton, Johann Wolfgang von Goethe, John Meriwether, John von Neumann, junk bonds, Kenneth Arrow, Long Term Capital Management, Louis Bachelier, margin call, market bubble, market fundamentalism, Marshall McLuhan, Michael Milken, Myron Scholes, New Journalism, Norbert Wiener, offshore financial centre, Paul Samuelson, publish or perish, quantitative trading / quantitative finance, random walk, risk free rate, risk tolerance, risk-adjusted returns, Robert Shiller, Ronald Reagan, Rubik’s Cube, short selling, speech recognition, statistical arbitrage, Teledyne, The Predators' Ball, The Wealth of Nations by Adam Smith, transaction costs, traveling salesman, value at risk, zero-coupon bond, zero-sum game

Nyquist had used intelligence, and Hartley had used information. In his earliest writings, Shannon favored Nyquist’s term. The military connotation of “intelligence” was fitting for the cryptographic work. “Intelligence” also implies meaning, however, which Shannon’s theory is pointedly not about. John von Neumann of Princeton’s Institute for Advanced Study advised Shannon to use the word entropy. Entropy is a physics term loosely described as a measure of randomness, disorder, or uncertainty. The concept of entropy grew out of the study of steam engines. It was learned that it is impossible to convert all the random energy of heat into useful work.

In the late 1950s, Shannon began an intensive study of the stock market that was motivated both by intellectual curiosity and desire for gain. He filled three library shelves with something like a hundred books on economics and investing. The titles included Adam Smith’s The Wealth of Nations, John von Neumann and Oskar Morgenstern’s Theory of Games and Economic Behavior, and Paul Samuelson’s Economics, as well as books with a more practical focus on investment. One book Shannon singled out as a favorite was Fred Schwed’s wry classic, Where Are the Customers’ Yachts? At the time he was designing the roulette computer with Thorp, Shannon kept notes in an MIT notebook.


pages: 370 words: 107,983

Rage Inside the Machine: The Prejudice of Algorithms, and How to Stop the Internet Making Bigots of Us All by Robert Elliott Smith

"World Economic Forum" Davos, Ada Lovelace, adjacent possible, affirmative action, AI winter, Alfred Russel Wallace, algorithmic bias, algorithmic management, AlphaGo, Amazon Mechanical Turk, animal electricity, autonomous vehicles, behavioural economics, Black Swan, Brexit referendum, British Empire, Cambridge Analytica, cellular automata, Charles Babbage, citizen journalism, Claude Shannon: information theory, combinatorial explosion, Computing Machinery and Intelligence, corporate personhood, correlation coefficient, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, desegregation, discovery of DNA, disinformation, Douglas Hofstadter, Elon Musk, fake news, Fellow of the Royal Society, feminist movement, Filter Bubble, Flash crash, Geoffrey Hinton, Gerolamo Cardano, gig economy, Gödel, Escher, Bach, invention of the wheel, invisible hand, Jacquard loom, Jacques de Vaucanson, John Harrison: Longitude, John von Neumann, Kenneth Arrow, Linda problem, low skilled workers, Mark Zuckerberg, mass immigration, meta-analysis, mutually assured destruction, natural language processing, new economy, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, On the Economy of Machinery and Manufactures, p-value, pattern recognition, Paul Samuelson, performance metric, Pierre-Simon Laplace, post-truth, precariat, profit maximization, profit motive, Silicon Valley, social intelligence, statistical model, Stephen Hawking, stochastic process, Stuart Kauffman, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, Turing test, twin studies, Vilfredo Pareto, Von Neumann architecture, warehouse robotics, women in the workforce, Yochai Benkler

In Turing’s posthumously published paper, Intelligent Machinery, which included ideas about neural networks, the father of computer science speculated that some form of “genetical search” could play a role in transforming and organising the random connections of his “unorganized machines.” While Turing was working on breaking WWII codes, John Von Neumann was working on the Manhattan Project. Von Neumann was an American-Hungarian genius and polymath, and his work designing nuclear weapons was only one of the ways in which he changed the world forever. The others include devising a way to make ENIAC (arguably the world’s first real computer) programmable; making substantial contributions to quantum physics6 and equilibrium theories in economics; and, inventing game theory, an area of mathematical research which shaped cold war politics for a generation through his descriptions of a game-theoretic construct he called “mutually assured destruction.”

Other scientific studies also show that striking a precise balance between the two may be the vital characteristic of living systems. The term edge of chaos was first used by the SFI researchers Doyne Farmer and Chris Langton, while looking at cellular automata models, simplified algorithms invented by John von Neumann to represent self-replicating biology.4 While experimenting with parameters that controlled these programs, they observed that for some parameter settings, the algorithms would settle into uninteresting equilibria, essentially static states. For others, the algorithms just generated complete randomness, never seeming to settle down into any recognizable patterns.


pages: 416 words: 112,268

Human Compatible: Artificial Intelligence and the Problem of Control by Stuart Russell

3D printing, Ada Lovelace, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alfred Russel Wallace, algorithmic bias, AlphaGo, Andrew Wiles, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, basic income, behavioural economics, Bletchley Park, blockchain, Boston Dynamics, brain emulation, Cass Sunstein, Charles Babbage, Claude Shannon: information theory, complexity theory, computer vision, Computing Machinery and Intelligence, connected car, CRISPR, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, deep learning, deepfake, DeepMind, delayed gratification, Demis Hassabis, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ernest Rutherford, fake news, Flash crash, full employment, future of work, Garrett Hardin, Geoffrey Hinton, Gerolamo Cardano, Goodhart's law, Hans Moravec, ImageNet competition, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the wheel, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Nash: game theory, John von Neumann, Kenneth Arrow, Kevin Kelly, Law of Accelerating Returns, luminiferous ether, machine readable, machine translation, Mark Zuckerberg, multi-armed bandit, Nash equilibrium, Nick Bostrom, Norbert Wiener, NP-complete, OpenAI, openstreetmap, P = NP, paperclip maximiser, Pareto efficiency, Paul Samuelson, Pierre-Simon Laplace, positional goods, probability theory / Blaise Pascal / Pierre de Fermat, profit maximization, RAND corporation, random walk, Ray Kurzweil, Recombinant DNA, recommendation engine, RFID, Richard Thaler, ride hailing / ride sharing, Robert Shiller, robotic process automation, Rodney Brooks, Second Machine Age, self-driving car, Shoshana Zuboff, Silicon Valley, smart cities, smart contracts, social intelligence, speech recognition, Stephen Hawking, Steven Pinker, superintelligent machines, surveillance capitalism, Thales of Miletus, The Future of Employment, The Theory of the Leisure Class by Thorstein Veblen, Thomas Bayes, Thorstein Veblen, Tragedy of the Commons, transport as a service, trolley problem, Turing machine, Turing test, universal basic income, uranium enrichment, vertical integration, Von Neumann architecture, Wall-E, warehouse robotics, Watson beat the top human players on Jeopardy!, web application, zero-sum game

It was all the more remarkable for the fact that, unlike monetary amounts, the utility values of various bets and prizes are not directly observable; instead, utilities are to be inferred from the preferences exhibited by an individual. It would be two centuries before the implications of the idea were fully worked out and it became broadly accepted by statisticians and economists. In the middle of the twentieth century, John von Neumann (a great mathematician after whom the standard “von Neumann architecture” for computers was named16) and Oskar Morgenstern published an axiomatic basis for utility theory.17 What this means is the following: as long as the preferences exhibited by an individual satisfy certain basic axioms that any rational agent should satisfy, then necessarily the choices made by that individual can be described as maximizing the expected value of a utility function.

The expected monetary value of the two solutions is the same, but Sempronius clearly prefers the two-ship solution. 16. By most accounts, von Neumann did not himself invent this architecture but his name was on an early draft of an influential report describing the EDVAC stored-program computer. 17. The work of von Neumann and Morgenstern is in many ways the foundation of modern economic theory: John von Neumann and Oskar Morgenstern, Theory of Games and Economic Behavior (Princeton University Press, 1944). 18. The proposal that utility is a sum of discounted rewards was put forward as a mathematically convenient hypothesis by Paul Samuelson, “A note on measurement of utility,” Review of Economic Studies 4 (1937): 155–61.


pages: 634 words: 185,116

From eternity to here: the quest for the ultimate theory of time by Sean M. Carroll

Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, Brownian motion, cellular automata, Claude Shannon: information theory, Columbine, cosmic microwave background, cosmological constant, cosmological principle, dark matter, dematerialisation, double helix, en.wikipedia.org, gravity well, Great Leap Forward, Harlow Shapley and Heber Curtis, heat death of the universe, Henri Poincaré, Isaac Newton, Johannes Kepler, John von Neumann, Lao Tzu, Laplace demon, Large Hadron Collider, lone genius, low earth orbit, New Journalism, Norbert Wiener, pets.com, Pierre-Simon Laplace, Richard Feynman, Richard Stallman, Schrödinger's Cat, Slavoj Žižek, Stephen Hawking, stochastic process, synthetic biology, the scientific method, time dilation, wikimedia commons

And that’s not the end of it; there are several other ways of thinking about entropy, and new ones are frequently being proposed in the literature. There’s nothing wrong with that; after all, Boltzmann and Gibbs were proposing definitions to supercede Clausius’s perfectly good definition of entropy, which is still used today under the rubric of “thermodynamic” entropy. After quantum mechanics came on the scene, John von Neumann proposed a formula for entropy that is specifically adapted to the quantum context. As we’ll discuss in the next chapter, Claude Shannon suggested a definition of entropy that was very similar in spirit to Gibbs’s, but in the framework of information theory rather than physics. The point is not to find the one true definition of entropy; it’s to come up with concepts that serve useful functions in the appropriate contexts.

9 INFORMATION AND LIFE You should call it entropy, for two reasons. In the first place, your uncertainty function has been used in statistical mechanics under that name, so it already has a name. In the second place, and more important, no one knows what entropy really is, so in a debate you will always have the advantage. —John von Neumann, to Claude Shannon144 In a celebrated episode in Swann’s Way, Marcel Proust’s narrator is feeling cold and somewhat depressed. His mother offers him tea, which he reluctantly accepts. He is then pulled into an involuntary recollection of his childhood by the taste of a traditional French teatime cake, the madeleine.

As a general rule, the more symmetries you have, the simpler things become. 110 This whole checkerboard-worlds idea sometimes goes by the name of cellular automata. A cellular automaton is just some discrete grid that follows a rule for determining the next row from the state of the previous row. They were first investigated in the 1960s, by John von Neumann, who is also the guy who figured out how entropy works in quantum mechanics. Cellular automata are fascinating for many reasons having little to do with the arrow of time; they can exhibit great complexity and can function as universal computers. See Poundstone (1984) or Shalizi (2009). Not only are we disrespecting cellular automata by pulling them out only to illustrate a few simple features of time reversal and information conservation, but we are also not speaking the usual language of cellular-automaton cognoscenti.


pages: 137 words: 36,231

Information: A Very Short Introduction by Luciano Floridi

agricultural Revolution, Albert Einstein, bioinformatics, Bletchley Park, carbon footprint, Claude Shannon: information theory, Computing Machinery and Intelligence, conceptual framework, digital divide, disinformation, double helix, Douglas Engelbart, Douglas Engelbart, George Akerlof, Gordon Gekko, Gregor Mendel, industrial robot, information asymmetry, intangible asset, Internet of things, invention of writing, John Nash: game theory, John von Neumann, Laplace demon, machine translation, moral hazard, Nash equilibrium, Nelson Mandela, Norbert Wiener, Pareto efficiency, phenotype, Pierre-Simon Laplace, prisoner's dilemma, RAND corporation, RFID, Thomas Bayes, Turing machine, Vilfredo Pareto

So MTC is commonly described as a study of information at the syntactic level. And since computers are syntactical devices, this is why MTC can be applied so successfully in ICT. Entropy and randomness Information in Shannon's sense is also known as entropy. It seems we owe this confusing label to John von Neumann (1903-1957), one of the most brilliant scientists of the 20th century, who recommended it to Shannon: You should call it entropy for two reasons: first, the function is already in use in thermodynamics under the same name; second, and more importantly, most people don't know what entropy really is, and if you use the word entropy in an argument you will win every time.


pages: 396 words: 117,149

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos

Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, backpropagation, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is not the new oil, data is the new oil, data science, deep learning, DeepMind, double helix, Douglas Hofstadter, driverless car, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, Geoffrey Hinton, global village, Google Glasses, Gödel, Escher, Bach, Hans Moravec, incognito mode, information retrieval, Jeff Hawkins, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, large language model, lone genius, machine translation, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, Nick Bostrom, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, power law, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, scientific worldview, Second Machine Age, self-driving car, Silicon Valley, social intelligence, speech recognition, Stanford marshmallow experiment, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the long tail, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, yottabyte, zero-sum game

The Bible Code, a 1998 bestseller, claimed that the Bible contains predictions of future events that you can find by skipping letters at regular intervals and assembling words from the letters you land on. Unfortunately, there are so many ways to do this that you’re guaranteed to find “predictions” in any sufficiently long text. Skeptics replied by finding them in Moby Dick and Supreme Court rulings, along with mentions of Roswell and UFOs in Genesis. John von Neumann, one of the founding fathers of computer science, famously said that “with four parameters I can fit an elephant, and with five I can make him wiggle his trunk.” Today we routinely learn models with millions of parameters, enough to give each elephant in the world his own distinctive wiggle.

His PhD advisor, Arthur Burks, nevertheless encouraged Holland’s interest in evolutionary computation and was instrumental in getting him a faculty job at Michigan and shielding him from senior colleagues who didn’t think that stuff was computer science. Burks himself was so open-minded because he had been a close collaborator of John von Neumann, who had proved the possibility of self-reproducing machines. Indeed, it had fallen to him to complete the work when von Neumann died of cancer in 1957. That von Neumann could prove that such machines are possible was quite remarkable, given the primitive state of genetics and computer science at the time.


Hacking Capitalism by Söderberg, Johan; Söderberg, Johan;

Abraham Maslow, air gap, Alvin Toffler, AOL-Time Warner, barriers to entry, Charles Babbage, collective bargaining, commoditize, computer age, corporate governance, creative destruction, Debian, deindustrialization, delayed gratification, Dennis Ritchie, deskilling, digital capitalism, digital divide, Donald Davies, Eben Moglen, Erik Brynjolfsson, Firefox, Free Software Foundation, frictionless, full employment, Garrett Hardin, Hacker Conference 1984, Hacker Ethic, Herbert Marcuse, Howard Rheingold, IBM and the Holocaust, informal economy, interchangeable parts, invention of radio, invention of the telephone, Jacquard loom, James Watt: steam engine, jimmy wales, John Markoff, John von Neumann, Joseph Schumpeter, Joseph-Marie Jacquard, Ken Thompson, knowledge economy, knowledge worker, labour market flexibility, late capitalism, Lewis Mumford, liberal capitalism, Marshall McLuhan, means of production, Mitch Kapor, mutually assured destruction, new economy, Norbert Wiener, On the Economy of Machinery and Manufactures, packet switching, patent troll, peer-to-peer, peer-to-peer model, planned obsolescence, post scarcity, post-Fordism, post-industrial society, price mechanism, Productivity paradox, profit motive, RFID, Richard Florida, Richard Stallman, Ronald Coase, safety bicycle, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Slavoj Žižek, software patent, Steven Levy, Stewart Brand, subscription business, tech worker, technological determinism, technoutopianism, the Cathedral and the Bazaar, The Nature of the Firm, the scientific method, The Theory of the Leisure Class by Thorstein Veblen, Thomas Davenport, Thorstein Veblen, tragedy of the anticommons, Tragedy of the Commons, transaction costs, Whole Earth Catalog, Yochai Benkler

Indeed, George Caffentzis has argued convincingly that the more technologically advanced the industrialised countries become, the worse the exploitation of labour gets in the remaining parts of the world. In an article in the Midnight Notes Collective, Caffentzis based his case on a vision of the computer scientist John von Neumann about a self-replicating, automatised factory. In this hypothetical scenario, where the production process involves no living labour whatsoever, there will be no value generated for the capitalist to exploit. The law of value postulates that only human labour can add value to a product. Human labour is unique in that it enlarges the value of a product above the sum of its own inputs.

The expectations of early Marxists, that capitalism would spiral downwards into aggravated crises and eventually self-destruct because of falling profitability, has by now been thoroughly discredited. Nevertheless, the law of the falling rate of profit does portray a gradual movement towards a logical endpoint, suggested by Ernest Mandel—total automation, which simultaneously is inconceivable with capitalism. A state of total automation, as it was envisioned already by John von Neumann, would be reached when machinery, without any injection of living labour, spits out an infinite volume of goods at instant speed. It is hard to imagine a machine with such dimensions, less than visualising science fiction gadgets or, just slightly more down-to-earth, nanotechnologic fantasies.


pages: 144 words: 43,356

Surviving AI: The Promise and Peril of Artificial Intelligence by Calum Chace

3D printing, Ada Lovelace, AI winter, Airbnb, Alvin Toffler, artificial general intelligence, augmented reality, barriers to entry, basic income, bitcoin, Bletchley Park, blockchain, brain emulation, Buckminster Fuller, Charles Babbage, cloud computing, computer age, computer vision, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, deep learning, DeepMind, dematerialisation, Demis Hassabis, discovery of the americas, disintermediation, don't be evil, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, everywhere but in the productivity statistics, Flash crash, friendly AI, Geoffrey Hinton, Google Glasses, hedonic treadmill, hype cycle, industrial robot, Internet of things, invention of agriculture, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, life extension, low skilled workers, machine translation, Mahatma Gandhi, means of production, mutually assured destruction, Neil Armstrong, Nicholas Carr, Nick Bostrom, paperclip maximiser, pattern recognition, peer-to-peer, peer-to-peer model, Peter Thiel, radical life extension, Ray Kurzweil, Robert Solow, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, Skype, South Sea Bubble, speech recognition, Stanislav Petrov, Stephen Hawking, Steve Jobs, strong AI, technological singularity, TED Talk, The future is already here, The Future of Employment, theory of mind, Turing machine, Turing test, universal basic income, Vernor Vinge, wage slave, Wall-E, zero-sum game

But the first general-purpose computer to be completed was ENIAC (Electronic Numerical Integrator And Computer), built at the Moore School of Electrical Engineering in Philadelphia, and unveiled in 1946. Like so many technological advances, it was funded by the military, and one of its first assignments was a feasibility study of the hydrogen bomb. While working on ENIAC’s successor, EDVAC (Electronic Discrete Variable Automatic Computer), the brilliant mathematician and polymath John von Neumann wrote a paper describing an architecture for computers which remains the basis for today’s machines. The Dartmouth Conference The arrival of computers combined with a series of ideas about thinking by Turing and others led to “the conjecture that every . . . feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”


pages: 124 words: 40,697

The Grand Design by Stephen Hawking, Leonard Mlodinow

airport security, Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, Buckminster Fuller, conceptual framework, cosmic microwave background, cosmological constant, dark matter, fudge factor, invention of the telescope, Isaac Newton, Johannes Kepler, John Conway, John von Neumann, Large Hadron Collider, luminiferous ether, Mercator projection, Richard Feynman, Stephen Hawking, Thales of Miletus, the scientific method, Turing machine

In fact, all the basic functions of a modern computer, such as AND and OR gates, can also be created from gliders. In this manner, just as electrical signals are employed in a physical computer, streams of gliders can be employed to send and process information. In the Game of Life, as in our world, self-reproducing patterns are complex objects. One estimate, based on the earlier work of mathematician John von Neumann, places the minimum size of a self-replicating pattern in the Game of Life at ten trillion squares—roughly the number of molecules in a single human cell. One can define living beings as complex systems of limited size that are stable and that reproduce themselves. The objects described above satisfy the reproduction condition but are probably not stable: A small disturbance from outside would probably wreck the delicate mechanism.


pages: 410 words: 119,823

Radical Technologies: The Design of Everyday Life by Adam Greenfield

3D printing, Airbnb, algorithmic bias, algorithmic management, AlphaGo, augmented reality, autonomous vehicles, bank run, barriers to entry, basic income, bitcoin, Black Lives Matter, blockchain, Boston Dynamics, business intelligence, business process, Californian Ideology, call centre, cellular automata, centralized clearinghouse, centre right, Chuck Templeton: OpenTable:, circular economy, cloud computing, Cody Wilson, collective bargaining, combinatorial explosion, Computer Numeric Control, computer vision, Conway's Game of Life, CRISPR, cryptocurrency, David Graeber, deep learning, DeepMind, dematerialisation, digital map, disruptive innovation, distributed ledger, driverless car, drone strike, Elon Musk, Ethereum, ethereum blockchain, facts on the ground, fiat currency, fulfillment center, gentrification, global supply chain, global village, Goodhart's law, Google Glasses, Herman Kahn, Ian Bogost, IBM and the Holocaust, industrial robot, informal economy, information retrieval, Internet of things, Jacob Silverman, James Watt: steam engine, Jane Jacobs, Jeff Bezos, Jeff Hawkins, job automation, jobs below the API, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Perry Barlow, John von Neumann, joint-stock company, Kevin Kelly, Kickstarter, Kiva Systems, late capitalism, Leo Hollis, license plate recognition, lifelogging, M-Pesa, Mark Zuckerberg, means of production, megacity, megastructure, minimum viable product, money: store of value / unit of account / medium of exchange, natural language processing, Network effects, New Urbanism, Nick Bostrom, Occupy movement, Oculus Rift, off-the-grid, PalmPilot, Pareto efficiency, pattern recognition, Pearl River Delta, performance metric, Peter Eisenman, Peter Thiel, planetary scale, Ponzi scheme, post scarcity, post-work, printed gun, proprietary trading, RAND corporation, recommendation engine, RFID, rolodex, Rutger Bregman, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, sharing economy, Shenzhen special economic zone , Sidewalk Labs, Silicon Valley, smart cities, smart contracts, social intelligence, sorting algorithm, special economic zone, speech recognition, stakhanovite, statistical model, stem cell, technoutopianism, Tesla Model S, the built environment, The Death and Life of Great American Cities, The Future of Employment, Tony Fadell, transaction costs, Uber for X, undersea cable, universal basic income, urban planning, urban sprawl, vertical integration, Vitalik Buterin, warehouse robotics, When a measure becomes a target, Whole Earth Review, WikiLeaks, women in the workforce

But 3D printers like the Replicator 2, as well as the computer numerically controlled (CNC) milling machines and laser cutters elsewhere in the building, might just be the most visible sign of a coming revolution: the digital fabrication of all the things we encounter in the world. We owe the conceptual genesis of the digital fabrication device to the legendary twentieth-century mathematician John von Neumann, who first broached the notion in a thought experiment he entertained as early as the mid-1940s. Von Neumann’s Theory of Self-Reproducing Automata,1 published posthumously in 1966, outlined the principles of a “universal constructor” able to pluck resources from its environment and, given enough time, arrange them into anything desired—including, crucially, exact copies of itself.

This is, of course, an entirely reasonable expectation, not merely in the liminal space of a dive bar but anywhere in the city. Casey Newton, “Seattle dive bar becomes first to ban Google Glass,” CNET, March 8, 2013. 23.Dan Wasserman, “Google Glass Rolls Out Diane von Furstenberg frames,” Mashable, June 23, 2014. 4Digital fabrication 1.John Von Neumann, Theory of Self-Reproducing Automata, Urbana: University of Illinois Press, 1966, cba.mit.edu/events/03.11.ASE/docs/VonNeumann.pdf. 2.You may be familiar with cellular automata from John Conway’s 1970 Game of Life, certainly the best-known instance of the class. See Bitstorm.org, “John Conway’s Game of Life,” undated, bitstorm.org. 3.Adrian Bowyer, “Wealth Without Money: The Background to the Bath Replicating Rapid Prototyper Project,” February 2, 2004, reprap.org/wiki/Wealth_Without_Money; RepRap Project, “Cost Reduction,” December 30, 2014, reprap.org/wiki/Cost_Reduction.


Prime Obsession:: Bernhard Riemann and the Greatest Unsolved Problem in Mathematics by John Derbyshire

Albert Einstein, Andrew Wiles, Bletchley Park, Charles Babbage, Colonization of Mars, Eratosthenes, Ernest Rutherford, four colour theorem, Georg Cantor, Henri Poincaré, Isaac Newton, John Conway, John von Neumann, Paul Erdős, Richard Feynman, Turing machine, Turing test

It is not impossible for a mathematician to be worldly, and there are many 164 PRIME OBSESSION counterexamples. René Descartes was a soldier and a courtier. (He survived the first but not the second.) Karl Weierstrass spent his years at university drinking and fighting and left without a degree. John von Neumann, one of the greatest of twentieth-century mathematicians, was quite a boulevardier, fond of pretty women and fast cars. Jacques Hadamard, on the evidence, was not one of those counterexamples. Even discounting the apocrypha that develop around any great man, it seems plain that Hadamard could not knot his tie without assistance.

Hilbert’s “metamathematics” program tried to encompass both logic and mathematics in a more waterproof symbolism. This inspired the work of Kurt Gödel and Alan Turing. Gödel proved important theorems by attaching numbers to Hilbert-type symbols; Turing coded both instructions and data as arbitrary numbers in his “Turing machine” concept. Picking up on this idea, John von Neumann developed the stored-program concept on which all modern software is based, that code and data can be represented in the same way in a computer’s memory…. EPILOGUE 138. In a letter to his brother dated June 26, 1854, he mentioned a recurrence of mein altes Übel—“my old malady”—brought on by a spell of bad weather. 139.


pages: 823 words: 220,581

Debunking Economics - Revised, Expanded and Integrated Edition: The Naked Emperor Dethroned? by Steve Keen

accounting loophole / creative accounting, Alan Greenspan, banking crisis, banks create money, barriers to entry, behavioural economics, Benoit Mandelbrot, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, book value, business cycle, butterfly effect, capital asset pricing model, cellular automata, central bank independence, citizen journalism, clockwork universe, collective bargaining, complexity theory, correlation coefficient, creative destruction, credit crunch, David Ricardo: comparative advantage, debt deflation, diversification, double entry bookkeeping, en.wikipedia.org, equity risk premium, Eugene Fama: efficient market hypothesis, experimental subject, Financial Instability Hypothesis, fixed income, Fractional reserve banking, full employment, Glass-Steagall Act, Greenspan put, Henri Poincaré, housing crisis, Hyman Minsky, income inequality, information asymmetry, invisible hand, iterative process, John von Neumann, Kickstarter, laissez-faire capitalism, liquidity trap, Long Term Capital Management, low interest rates, mandelbrot fractal, margin call, market bubble, market clearing, market microstructure, means of production, minimum wage unemployment, Money creation, money market fund, open economy, Pareto efficiency, Paul Samuelson, Phillips curve, place-making, Ponzi scheme, Post-Keynesian economics, power law, profit maximization, quantitative easing, RAND corporation, random walk, risk free rate, risk tolerance, risk/return, Robert Shiller, Robert Solow, Ronald Coase, Savings and loan crisis, Schrödinger's Cat, scientific mainstream, seigniorage, six sigma, South Sea Bubble, stochastic process, The Great Moderation, The Wealth of Nations by Adam Smith, Thorstein Veblen, time value of money, total factor productivity, tulip mania, wage slave, zero-sum game

The concept of expected value is thus not a good arbiter for rational behavior in the way it is normally presented in Behavioral Economics and Finance experiments – why, then, is it used? If you’ve read this far into this book, you won’t be surprised to learn that it’s because economists have misread the foundation research on this topic by the mathematician John von Neumann, and his economist collaborator Oskar Morgenstern, The Theory of Games and Economic Behavior (Von Neumann and Morgenstern 1953). Misunderstanding von Neumann John von Neumann was one of the greatest intellects of all time, a child prodigy who went on to make numerous pivotal contributions to a vast range of fields in mathematics, physics, and computer science. He was a polymath at a time when it was far more difficult to make contributions across a range of fields than it had been in earlier centuries.

However, subsequent economists have applied this theory to all behavior, including interpersonal relations. 4 Cardinal refers to the ability to attach a precise quantity, whereas ordinal refers to the ability to rank things in size order, without necessarily being able to ascribe a numeric value to each. 5 As I point out later, the mathematician John von Neumann developed a way that a cardinal measure of utility could be derived, but this was ignored by neoclassical economists (Von Neumann and Morgenstern 1953: 17–29). 6 At its base (where, using my ‘bananas and biscuits’ example, zero bananas and zero biscuits were consumed), its height was zero. Then as you walked in the bananas direction only (eating bananas but no biscuits), the mountain rose, but at an ever-diminishing rate – it was its steepest at its base, because the very first units consumed gave the greatest ‘marginal utility.’


pages: 159 words: 45,073

GDP: A Brief but Affectionate History by Diane Coyle

Alan Greenspan, Asian financial crisis, Berlin Wall, big-box store, Bletchley Park, Bretton Woods, BRICs, business cycle, clean water, computer age, conceptual framework, crowdsourcing, Diane Coyle, double entry bookkeeping, driverless car, en.wikipedia.org, endogenous growth, Erik Brynjolfsson, Fall of the Berlin Wall, falling living standards, financial intermediation, global supply chain, happiness index / gross national happiness, hedonic treadmill, income inequality, income per capita, informal economy, Johannes Kepler, John von Neumann, Kevin Kelly, Les Trente Glorieuses, Long Term Capital Management, Mahbub ul Haq, mutually assured destruction, Nathan Meyer Rothschild: antibiotics, new economy, Occupy movement, Phillips curve, purchasing power parity, Robert Shiller, Robert Solow, Ronald Reagan, shareholder value, Silicon Valley, Simon Kuznets, The Wealth of Nations by Adam Smith, Thorstein Veblen, University of East Anglia, working-age population

The electronic programmable computer was one of the basic innovations of World War II. It emerged from the wartime code-breaking work at Bletchley Park in the United Kingdom and the brilliant conceptual leaps made by Alan Turing, and, across the Atlantic during and after the war, from the work of John Von Neumann and others involved in the development of nuclear weapons. Computers began as military and academic machines, then came into use in big businesses, and in the 1980s finally became small and cheap enough to spread to all offices and gradually individual homes. Separately, the communications protocols between computers were developed in the United States in the 1970s, by DARPA (the Defense Advanced Research Projects Agency) among other groups.


pages: 469 words: 142,230

The Planet Remade: How Geoengineering Could Change the World by Oliver Morton

Albert Einstein, Anthropocene, Apollo 13, Asilomar, Boeing 747, British Empire, Buckminster Fuller, carbon credits, carbon tax, Cesare Marchetti: Marchetti’s constant, colonial rule, Colonization of Mars, Columbian Exchange, decarbonisation, demographic transition, Dr. Strangelove, electricity market, Elon Musk, energy transition, Ernest Rutherford, Garrett Hardin, germ theory of disease, Haber-Bosch Process, Intergovernmental Panel on Climate Change (IPCC), James Watt: steam engine, Jeff Bezos, John Harrison: Longitude, John von Neumann, Kim Stanley Robinson, Kintsugi, late capitalism, Louis Pasteur, megaproject, Michael Shellenberger, military-industrial complex, moral hazard, Naomi Klein, negative emissions, nuclear winter, ocean acidification, oil shale / tar sands, orbital mechanics / astrodynamics, Philip Mirowski, planetary scale, plutocrats, public intellectual, renewable energy transition, rewilding, scientific management, Scramble for Africa, Search for Extraterrestrial Intelligence, Silicon Valley, smart grid, South China Sea, Stewart Brand, systems thinking, tech billionaire, Ted Nordhaus, Thomas Malthus, Virgin Galactic

The idea of deliberate climate change was bound up with thinking about nuclear weaponry from the very beginning of the cold war. Control and Catastrophe In 1945 ENIAC, the first fully programmable electronic computer, was given its first problem: a simulation of the hydrogen-bomb design then being touted by Edward Teller. The task was set by John von Neumann, a mathematician at the Princeton Institute for Advanced Study who was attached to the Manhattan Project. Von Neumann was determined that the computer’s potential for solving problems should be applied to the most pressing issues of the day. And that was why, even as the million-punch-card H-bomb explosion was trundling through ENIAC’s circuits, he was already working out how the machine and its successors could be programmed to predict the weather, and produce new insights into controlling it.

Chapter Eleven: The Ends of the World Badash (2009) provides a very full account of the origins of and arguments over nuclear winter; the key papers are Crutzen and Birks (1982) and Turco et al. (1983) – the TTAPS paper. Levenson (1990) provides excellent context. Weart (1988) and Brians (1987) are useful on the cultural ramifications of nuclear fear; Johan Rockström is quoted in Rayner and Heyward (2013). For more on Huxley’s speech, see Deese (2010). Of many sources available on John von Neumann, Dyson (2012) stands out; his supernova fears are quoted in Smith (2007) and the proceedings of the ‘Infinite Forecast’ meeting are in Pfeffer (1956). The point about the different academic milieux of weather modification and climate modelling is made in Hart and Victor (1993), and Paul Edwards’ dissection of climate-nuclear doublethink is in Edwards (2012).


pages: 500 words: 145,005

Misbehaving: The Making of Behavioral Economics by Richard H. Thaler

3Com Palm IPO, Alan Greenspan, Albert Einstein, Alvin Roth, Amazon Mechanical Turk, Andrei Shleifer, Apple's 1984 Super Bowl advert, Atul Gawande, behavioural economics, Berlin Wall, Bernie Madoff, Black-Scholes formula, book value, business cycle, capital asset pricing model, Cass Sunstein, Checklist Manifesto, choice architecture, clean water, cognitive dissonance, conceptual framework, constrained optimization, Daniel Kahneman / Amos Tversky, delayed gratification, diversification, diversified portfolio, Edward Glaeser, endowment effect, equity premium, equity risk premium, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, George Akerlof, hindsight bias, Home mortgage interest deduction, impulse control, index fund, information asymmetry, invisible hand, Jean Tirole, John Nash: game theory, John von Neumann, Kenneth Arrow, Kickstarter, late fees, law of one price, libertarian paternalism, Long Term Capital Management, loss aversion, low interest rates, market clearing, Mason jar, mental accounting, meta-analysis, money market fund, More Guns, Less Crime, mortgage debt, Myron Scholes, Nash equilibrium, Nate Silver, New Journalism, nudge unit, PalmPilot, Paul Samuelson, payday loans, Ponzi scheme, Post-Keynesian economics, presumed consent, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, random walk, randomized controlled trial, Richard Thaler, risk free rate, Robert Shiller, Robert Solow, Ronald Coase, Silicon Valley, South Sea Bubble, Stanford marshmallow experiment, statistical model, Steve Jobs, sunk-cost fallacy, Supply of New York City Cabdrivers, systematic bias, technology bubble, The Chicago School, The Myth of the Rational Market, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, transaction costs, ultimatum game, Vilfredo Pareto, Walter Mischel, zero-sum game

This implies that if your wealth is $100,000 and I offer you a choice between an additional $1,000 for sure or a 50% chance to win $2,000, you will take the sure thing because you value the second thousand you would win less than the first thousand, so you are not willing to risk losing that first $1,000 prize in an attempt to get $2,000. The full treatment of the formal theory of how to make decisions in risky situations—called expected utility theory—was published in 1944 by the mathematician John von Neumann and the economist Oskar Morgenstern. John von Neumann, one of the greatest mathematicians of the twentieth century, was a contemporary of Albert Einstein at the Institute of Advanced Study at Princeton University, and during World War II he decided to devote himself to practical problems. The result was the 600-plus-page opus The Theory of Games and Economic Behavior, in which the development of expected utility theory was just a sideline.


From Airline Reservations to Sonic the Hedgehog: A History of the Software Industry by Martin Campbell-Kelly

Apple II, Apple's 1984 Super Bowl advert, barriers to entry, Bill Gates: Altair 8800, business process, card file, Charles Babbage, computer age, computer vision, continuous integration, Dennis Ritchie, deskilling, Donald Knuth, Gary Kildall, Grace Hopper, history of Unix, hockey-stick growth, independent contractor, industrial research laboratory, information asymmetry, inventory management, John Markoff, John von Neumann, Larry Ellison, linear programming, longitudinal study, machine readable, Menlo Park, Mitch Kapor, Multics, Network effects, popular electronics, proprietary trading, RAND corporation, Robert X Cringely, Ronald Reagan, seminal paper, Silicon Valley, SimCity, software patent, Steve Jobs, Steve Wozniak, Steven Levy, Thomas Kuhn: the structure of scientific revolutions, vertical integration

From Airline Reservations to Sonic the Hedgehog History of Computing I. Bernard Cohen and William Aspray, editors William Aspray, John von Neumann and the Origins of Modern Computing Charles J. Bashe, Lyle R. Johnson, John H. Palmer, and Emerson W. Pugh, IBM’s Early Computers Martin Campbell-Kelly, From Airline Reservations to Sonic the Hedgehog: A History of the Software Industry Paul E. Ceruzzi, A History of Modern Computing I. Bernard Cohen, Howard Aiken: Portrait of a Computer Pioneer I. Bernard Cohen and Gregory W. Welch, editors, Makin’ Numbers: Howard Aiken and the Computer John Hendry, Innovating for Failure: Government Policy and the Early British Computer Industry Michael Lindgren, Glory and Failure: The Difference Engines of Johann Müller, Charles Babbage, and Georg and Edvard Scheutz David E.

The Technical Computing Bureau was allocated the first production 701, which was located in IBM’s world headquarters on Madison Avenue in New York. The machine was inaugurated in April 1953 with enormous publicity to herald IBM’s arrival on the computer scene. Among the 200 guests were J. Robert Oppenheimer (the former director of the Manhattan Project), John von Neumann (one of the inventors of the stored-program computer), and William Shockley (coinventor of the transistor). The Technical Computing Bureau’s machine was in place about 6 months before the first deliveries of 701s to customers, so customers’ programmers were able to become familiar with the 701 before their machines arrived.


pages: 476 words: 132,042

What Technology Wants by Kevin Kelly

Albert Einstein, Alfred Russel Wallace, Apollo 13, Boeing 747, Buckminster Fuller, c2.com, carbon-based life, Cass Sunstein, charter city, classic study, Clayton Christensen, cloud computing, computer vision, cotton gin, Danny Hillis, dematerialisation, demographic transition, digital divide, double entry bookkeeping, Douglas Engelbart, Edward Jenner, en.wikipedia.org, Exxon Valdez, Fairchild Semiconductor, Ford Model T, George Gilder, gravity well, Great Leap Forward, Gregor Mendel, hive mind, Howard Rheingold, interchangeable parts, invention of air conditioning, invention of writing, Isaac Newton, Jaron Lanier, Joan Didion, John Conway, John Markoff, John von Neumann, Kevin Kelly, knowledge economy, Lao Tzu, life extension, Louis Daguerre, Marshall McLuhan, megacity, meta-analysis, new economy, off grid, off-the-grid, out of africa, Paradox of Choice, performance metric, personalized medicine, phenotype, Picturephone, planetary scale, precautionary principle, quantum entanglement, RAND corporation, random walk, Ray Kurzweil, recommendation engine, refrigerator car, rewilding, Richard Florida, Rubik’s Cube, Silicon Valley, silicon-based life, skeuomorphism, Skype, speech recognition, Stephen Hawking, Steve Jobs, Stewart Brand, Stuart Kauffman, technological determinism, Ted Kaczynski, the built environment, the long tail, the scientific method, Thomas Malthus, Vernor Vinge, wealth creators, Whole Earth Catalog, Y2K, yottabyte

When two world wars unleashed the full killing power of this inventiveness, it cemented the reputation of technology as a beguiling satan. As we refined this stuff through generations of technological evolution, it lost much of its hardness. We began to see through technology’s disguise as material and began to see it primarily as action. While it inhabited a body, its heart was something softer. In 1949, John von Neumann, the brainy genius behind the first useful computer, realized what computers were teaching us about technology: “Technology will in the near and in the farther future increasingly turn from problems of intensity, substance, and energy, to problems of structure, organization, information, and control.”

Synchronicity is not just a phenomenon of the past, when communication was poor, but very much part of the present. Scientists at AT&T Bell Labs won a Nobel Prize for inventing the transistor in 1948, but two German physicists independently invented a transistor two months later at a Westinghouse laboratory in Paris. Popular accounts credit John von Neumann with the invention of a programmable binary computer during the last years of World War II, but the idea and a working punched-tape prototype were developed quite separately in Germany a few years earlier, in 1941, by Konrad Zuse. In a verifiable case of modern parallelism, Zuse’s pioneering binary computer went completely unnoticed in the United States and the UK until many decades later.


pages: 462 words: 129,022

People, Power, and Profits: Progressive Capitalism for an Age of Discontent by Joseph E. Stiglitz

affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, AlphaGo, antiwork, barriers to entry, basic income, battle of ideas, behavioural economics, Berlin Wall, Bernie Madoff, Bernie Sanders, Big Tech, business cycle, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, carried interest, central bank independence, clean water, collective bargaining, company town, corporate governance, corporate social responsibility, creative destruction, Credit Default Swap, crony capitalism, DeepMind, deglobalization, deindustrialization, disinformation, disintermediation, diversified portfolio, Donald Trump, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, fake news, Fall of the Berlin Wall, financial deregulation, financial innovation, financial intermediation, Firefox, Fractional reserve banking, Francis Fukuyama: the end of history, full employment, George Akerlof, gig economy, Glass-Steagall Act, global macro, global supply chain, greed is good, green new deal, income inequality, information asymmetry, invisible hand, Isaac Newton, Jean Tirole, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John von Neumann, Joseph Schumpeter, labor-force participation, late fees, low interest rates, low skilled workers, Mark Zuckerberg, market fundamentalism, mass incarceration, meta-analysis, minimum wage unemployment, moral hazard, new economy, New Urbanism, obamacare, opioid epidemic / opioid crisis, patent troll, Paul Samuelson, pension reform, Peter Thiel, postindustrial economy, price discrimination, principal–agent problem, profit maximization, purchasing power parity, race to the bottom, Ralph Nader, rent-seeking, Richard Thaler, Robert Bork, Robert Gordon, Robert Mercer, Robert Shiller, Robert Solow, Ronald Reagan, Savings and loan crisis, search costs, secular stagnation, self-driving car, shareholder value, Shoshana Zuboff, Silicon Valley, Simon Kuznets, South China Sea, sovereign wealth fund, speech recognition, Steve Bannon, Steve Jobs, surveillance capitalism, TED Talk, The Chicago School, The Future of Employment, The Great Moderation, the market place, The Rise and Fall of American Growth, the scientific method, The Wealth of Nations by Adam Smith, too big to fail, trade liberalization, transaction costs, trickle-down economics, two-sided market, universal basic income, Unsafe at Any Speed, Upton Sinclair, uranium enrichment, War on Poverty, working-age population, Yochai Benkler

Robert Gordon of Northwestern University in his bestselling book The Rise and Fall of American Growth: The US Standard of Living Since the Civil War argues that the pace of innovation has actually slowed.2 Yes, we have Facebook and Google, but these innovations pale in comparison with the importance of electricity, or even indoor toilets and clean water that played such an important role in improving health and longevity. These past experiences may, however, not be a good guide for the future. More than a half century ago, John von Neumann, one of the leading mathematicians of the mid-twentieth century, suggested that there might be a point3 where it becomes less expensive to produce a machine to replace a human than to hire and train a human. These machines will, in turn, be produced by other machines that learn how to produce them.

Some suggest that there are significant measurement errors in GDP, so that it underestimates the true rate of growth, but in my judgment, while there are significant measurement problems, they do not change the overall picture, in particular, the pace of increase in GDP today is lower than it was in earlier periods. Of course, by its very nature, we cannot be sure about the future pace of innovation. 3.Referred to as the “singularity.” See also Stanislaw Ulam, “Tribute to John von Neumann,” Bulletin of the American Mathematical Society 64, no. 3, part 2 (1958): 5. See also Anton Korinek and Joseph E. Stiglitz, “Artificial Intelligence and Its Implications for Income Distribution and Unemployment,” in Economics of Artificial Intelligence (Chicago: University of Chicago Press, forthcoming). 4.Rapid advances in artificial intelligence in the last five years has led to extensive speculation about when AI will exceed human performance in a range of jobs.


pages: 214 words: 14,382

Monadic Design Patterns for the Web by L.G. Meredith

barriers to entry, domain-specific language, don't repeat yourself, finite state, functional programming, Georg Cantor, ghettoisation, higher-order functions, John von Neumann, Kickstarter, semantic web, seminal paper, social graph, type inference, web application, WebSocket

Further, we can use our case class, Game, together with zero, to make the Conway game that represents unity, aka one. We could write this at the Scala Read-Evaluate-Print-Loop (REPL) prompt with the following: scala> val one = Game( Set( EmptyGame ), Set.empty ) one: Game = Game(Set(EmptyGame),Set()) Anyone familiar with the John von Neumann encoding of the Naturals can see where this is going. (And anyone not will get the gist with the next bit.) We’ll skip ahead soon and talk about how to model addition, but first, let’s look at Conway’s own notation. He writes games like this: G = { GL, . . . | GR, . . . } The notation is much like set (comprehension) notation except that the bar in the middle of braces denotes the separation of the left and right components.


pages: 158 words: 49,168

Infinite Ascent: A Short History of Mathematics by David Berlinski

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Andrew Wiles, Benoit Mandelbrot, Douglas Hofstadter, Eratosthenes, four colour theorem, Georg Cantor, Gödel, Escher, Bach, Henri Poincaré, Isaac Newton, John von Neumann, Murray Gell-Mann, Stephen Hawking, Turing machine, William of Occam

We ourselves may allow Pedro or Fedro to suffer a cut all his own, restoring to prominence in Kurt Gödel the twenty-three-year-old director of record. The unpurged images of this spectacular argument recede; so, too, the details of Gödel’s first theorem. Directly, the second theorem appears, this one dealing directly with the issue of consistency. It is a theorem that John von Neumann noticed after Gödel had communicated his first theorem to various mathematicians; but when he wrote eagerly to Gödel to convey his discovery, he learned that Gödel had already discovered the same thing. The import of Gödel’s second theorem can be conveyed by means of only a few strokes. The first incompleteness theorem affirms that if the system of the Principia is consistent, then there exists an undecidable proposition, one that may be expressed from within the cage of its symbols.


pages: 170 words: 51,205

Information Doesn't Want to Be Free: Laws for the Internet Age by Cory Doctorow, Amanda Palmer, Neil Gaiman

Airbnb, barriers to entry, Big Tech, Brewster Kahle, cloud computing, Dean Kamen, Edward Snowden, game design, general purpose technology, Internet Archive, John von Neumann, Kickstarter, Large Hadron Collider, machine readable, MITM: man-in-the-middle, optical character recognition, plutocrats, pre–internet, profit maximization, recommendation engine, rent-seeking, Saturday Night Live, Skype, Steve Jobs, Steve Wozniak, Stewart Brand, Streisand effect, technological determinism, transfer pricing, Whole Earth Catalog, winner-take-all economy

They figured out how to do it with ease. 1.5 Understanding General-Purpose Computers BACK AT THE dawn of mechanical computation, computers were “special-purpose.” One computer would solve one kind of mathematical problem, and if you had a different problem, you’d build a different computer. But during World War II, thanks to the government-funded advancements made by such scientific luminaries as Alan Turing and John von Neumann, a new kind of computer came into existence: the “general-purpose” digital computer. These machines arose from a theory of general-purpose computation that showed that, with a simple set of “logic gates” and enough memory and time, you could “compute” any program that could be represented symbolically.


pages: 180 words: 55,805

The Price of Tomorrow: Why Deflation Is the Key to an Abundant Future by Jeff Booth

3D printing, Abraham Maslow, activist fund / activist shareholder / activist investor, additive manufacturing, AI winter, Airbnb, Albert Einstein, AlphaGo, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, Bretton Woods, business intelligence, butterfly effect, Charles Babbage, Claude Shannon: information theory, clean water, cloud computing, cognitive bias, collapse of Lehman Brothers, Computing Machinery and Intelligence, corporate raider, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, currency manipulation / currency intervention, dark matter, deep learning, DeepMind, deliberate practice, digital twin, distributed ledger, Donald Trump, Elon Musk, fiat currency, Filter Bubble, financial engineering, full employment, future of work, game design, gamification, general purpose technology, Geoffrey Hinton, Gordon Gekko, Great Leap Forward, Hyman Minsky, hype cycle, income inequality, inflation targeting, information asymmetry, invention of movable type, Isaac Newton, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, John von Neumann, Joseph Schumpeter, late fees, low interest rates, Lyft, Maslow's hierarchy, Milgram experiment, Minsky moment, Modern Monetary Theory, moral hazard, Nelson Mandela, Network effects, Nick Bostrom, oil shock, OpenAI, pattern recognition, Ponzi scheme, quantitative easing, race to the bottom, ride hailing / ride sharing, self-driving car, software as a service, technoutopianism, TED Talk, the long tail, the scientific method, Thomas Bayes, Turing test, Uber and Lyft, uber lyft, universal basic income, winner-take-all economy, X Prize, zero-sum game

For a moment, though, let’s assume that we are always completely rational, making decisions that are best for ourselves, our families, our countries, and the world around us—in that order. On the face of it, it sounds simple enough—until we consider that the decisions that are best for us are oftentimes at odds with each other. Game theory applies to almost everything when competing for scarce resources. It was developed in 1928 by John von Neumann (1903–1957) and was further refined in 1944 with Oskar Morgenstern (1902–1977) and has broad implication in business, economics, biology, and war—whenever our own actions depend critically on other participants. As different “actors” or “agents” (game theory speak—in this case, you could use “individuals” or “countries”) choose different strategies to maximize their own benefit, a “game” is developed where understanding what each actor or agent will do becomes critical to who wins the game.


pages: 519 words: 142,646

Track Changes by Matthew G. Kirschenbaum

active measures, Alvin Toffler, Apollo 11, Apple II, Apple's 1984 Super Bowl advert, Bill Gates: Altair 8800, Buckminster Fuller, Charles Babbage, commoditize, computer age, Computer Lib, corporate governance, David Brooks, dematerialisation, Donald Knuth, Douglas Hofstadter, Dynabook, East Village, en.wikipedia.org, feminist movement, forensic accounting, future of work, Future Shock, Google Earth, Gödel, Escher, Bach, Haight Ashbury, HyperCard, Jason Scott: textfiles.com, Joan Didion, John Markoff, John von Neumann, Kickstarter, low earth orbit, machine readable, machine translation, mail merge, Marshall McLuhan, Mother of all demos, Neal Stephenson, New Journalism, Norman Mailer, off-the-grid, pattern recognition, pink-collar, planned obsolescence, popular electronics, Project Xanadu, RAND corporation, rolodex, Ronald Reagan, scientific management, self-driving car, Shoshana Zuboff, Silicon Valley, social web, Stephen Fry, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, systems thinking, tacit knowledge, technoutopianism, Ted Nelson, TED Talk, text mining, thinkpad, Turing complete, Vannevar Bush, Whole Earth Catalog, Y2K, Year of Magical Thinking

read the ad that was posted around Silicon Valley in February 1975.3 Computers themselves, of course, compute: which is to say they work by fundamentally arithmetical principles. An algorithm is a sequence of arithmetical steps. A program is a sequence of algorithms. The basic architecture of input, processing, storage, and output has been canonical in computer science since John von Neumann published his “draft” report on the EDVAC in 1945.4 All of those different abstract components, however, require a corresponding instantiation in some physical medium. Computer storage, for example, has historically taken the form of everything from disks and tape to punched cards to magnetic drums, wires, mesh, and ringlets, even cathode ray tubes (before they were used as output devices).

The principle of storing data in the same medium and format as the programs that make use of it is a bedrock principle of computer architecture, formally instantiated in the so-called Von Neumann model that dominated computer systems design throughout the second half of the twentieth century. (As John von Neumann himself was wont to put it, it was all the same “organ.”)42 As early as 2001 the State Library of Victoria in Melbourne purchased the Macintosh laptop—reportedly missing its “o” key—that the Australian novelist Peter Carey used to write The True History of the Kelly Gang (2000); it is currently on display there under glass, alongside samples from his literary papers.43 Similar to the work at Emory, archivists there contemplate making a “clone” of the machine available so visitors can explore its electronic innards.


pages: 523 words: 148,929

Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100 by Michio Kaku

agricultural Revolution, AI winter, Albert Einstein, Alvin Toffler, Apollo 11, Asilomar, augmented reality, Bill Joy: nanobots, bioinformatics, blue-collar work, British Empire, Brownian motion, caloric restriction, caloric restriction, cloud computing, Colonization of Mars, DARPA: Urban Challenge, data science, delayed gratification, digital divide, double helix, Douglas Hofstadter, driverless car, en.wikipedia.org, Ford Model T, friendly AI, Gödel, Escher, Bach, Hans Moravec, hydrogen economy, I think there is a world market for maybe five computers, industrial robot, Intergovernmental Panel on Climate Change (IPCC), invention of movable type, invention of the telescope, Isaac Newton, John Markoff, John von Neumann, Large Hadron Collider, life extension, Louis Pasteur, Mahatma Gandhi, Mars Rover, Mars Society, mass immigration, megacity, Mitch Kapor, Murray Gell-Mann, Neil Armstrong, new economy, Nick Bostrom, oil shale / tar sands, optical character recognition, pattern recognition, planetary scale, postindustrial economy, Ray Kurzweil, refrigerator car, Richard Feynman, Rodney Brooks, Ronald Reagan, Search for Extraterrestrial Intelligence, Silicon Valley, Simon Singh, social intelligence, SpaceShipOne, speech recognition, stem cell, Stephen Hawking, Steve Jobs, synthetic biology, telepresence, The future is already here, The Wealth of Nations by Adam Smith, Thomas L Friedman, Thomas Malthus, trade route, Turing machine, uranium enrichment, Vernor Vinge, Virgin Galactic, Wall-E, Walter Mischel, Whole Earth Review, world market for maybe five computers, X Prize

The word originally came from the world of relativistic physics, my personal specialty, where a singularity represents a point of infinite gravity, from which nothing can escape, such as a black hole. Because light itself cannot escape, it is a horizon beyond which we cannot see. The idea of an AI singularity was first mentioned in 1958, in a conversation between two mathematicians, Stanislaw Ulam (who made the key breakthrough in the design of the hydrogen bomb) and John von Neumann. Ulam wrote, “One conversation centered on the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the human race beyond which human affairs, as we know them, could not continue.”

Matching the computing speed of the brain is just the humble beginning. Third, even if intelligent robots are possible, it is not clear if a robot can make a copy of itself that is smarter than the original. The mathematics behind self-replicating robots was first developed by the mathematician John von Neumann, who invented game theory and helped to develop the electronic computer. He pioneered the question of determining the minimum number of assumptions before a machine could create a copy of itself. However, he never addressed the question of whether a robot can make a copy of itself that is smarter than it.


pages: 205 words: 18,208

The Transparent Society: Will Technology Force Us to Choose Between Privacy and Freedom? by David Brin

affirmative action, airport security, Ayatollah Khomeini, clean water, cognitive dissonance, corporate governance, data acquisition, death of newspapers, Extropian, Garrett Hardin, Howard Rheingold, illegal immigration, informal economy, information asymmetry, information security, Iridium satellite, Jaron Lanier, John Gilmore, John Markoff, John Perry Barlow, John von Neumann, Kevin Kelly, Marshall McLuhan, means of production, mutually assured destruction, Neal Stephenson, offshore financial centre, Oklahoma City bombing, open economy, packet switching, pattern recognition, pirate software, placebo effect, plutocrats, prediction markets, Ralph Nader, RAND corporation, Robert Bork, Saturday Night Live, Search for Extraterrestrial Intelligence, Steve Jobs, Steven Levy, Stewart Brand, telepresence, The Turner Diaries, Timothy McVeigh, trade route, Tragedy of the Commons, UUNET, Vannevar Bush, Vernor Vinge, Whole Earth Catalog, Whole Earth Review, workplace surveillance , Yogi Berra, zero-sum game, Zimmermann PGP

In those days, long-distance call routing was a laborious task of negotiation, planned well in advance by human operators arranging connections from one zone to the next. But this drudgery might be avoided in a dispersed computer network if the messages themselves could navigate, finding their own way from node to node, carrying destination information in their lead bits like the address on the front of an envelope. Early theoretical work by Alan Turing and John Von Neumann hinted this to be possible by allowing each part of a network to guess the best way to route a message past any damaged area and eventually reach its goal. In theory, such a system might keep operating even when others lay in tatters. In retrospect, the advantages of Baranʼs insight seem obvious.

(See the section on “public feedback regulation” in chapter 8.) Right now we should focus on the evolving way in which researchers have come to view the concept of risk and how people respond to it. Until recently, most models were based on classical decision theory, supplemented by the later game theory that John Von Neumann developed after World War II. These are essentially mathematical approaches to betting— calculating odds for success or failure when contributing factors are either well known, or partly unknown. For instance, a problem called “the prisonersʼ dilemma” explores how two parties might behave when each can make a quick, temporary score by betraying the other, or else both might prosper, moderately but indefinitely, by deciding to cooperate.


pages: 688 words: 147,571

Robot Rules: Regulating Artificial Intelligence by Jacob Turner

"World Economic Forum" Davos, Ada Lovelace, Affordable Care Act / Obamacare, AI winter, algorithmic bias, algorithmic trading, AlphaGo, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, autonomous vehicles, backpropagation, Basel III, bitcoin, Black Monday: stock market crash in 1987, blockchain, brain emulation, Brexit referendum, Cambridge Analytica, Charles Babbage, Clapham omnibus, cognitive dissonance, Computing Machinery and Intelligence, corporate governance, corporate social responsibility, correlation does not imply causation, crowdsourcing, data science, deep learning, DeepMind, Demis Hassabis, distributed ledger, don't be evil, Donald Trump, driverless car, easy for humans, difficult for computers, effective altruism, Elon Musk, financial exclusion, financial innovation, friendly fire, future of work, hallucination problem, hive mind, Internet of things, iterative process, job automation, John Markoff, John von Neumann, Loebner Prize, machine readable, machine translation, medical malpractice, Nate Silver, natural language processing, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, nudge unit, obamacare, off grid, OpenAI, paperclip maximiser, pattern recognition, Peace of Westphalia, Philippa Foot, race to the bottom, Ray Kurzweil, Recombinant DNA, Rodney Brooks, self-driving car, Silicon Valley, Stanislav Petrov, Stephen Hawking, Steve Wozniak, strong AI, technological singularity, Tesla Model S, The Coming Technological Singularity, The Future of Employment, The Signal and the Noise by Nate Silver, trolley problem, Turing test, Vernor Vinge

Alt and M. Ruminoff, Vol. 6 (New York: Academic Press, 1965). 106Nick Bostrom, “How Long Before Superintelligence?”, International Journal of Future Studies, 1998, vol. 2.. 107 The singularity was conceived of shortly after the advent of modern AI studies, having been introduced by John von Neumann in 1958 and then popularised by Vernor Vinge, in “The Coming Technological Singularity: How to Survive in the Post-human Era” (1993), available at: https://​edoras.​sdsu.​edu/​~vinge/​misc/​singularity.​html, accessed 22 June 2018 and subsequently by Ray Kurzweil, The Singularity Is Near: When Humans Transcend Biology (New York: Viking Press, 2005). 108In 1968, a Scottish chess champion bet AI pioneer John McCarthy £500 that a computer would not be able to beat him by 1979.

, Scientific American, Vol. 314 (June 2016), 58–59. 140Nate Soares and Benja Fallenstein, “Aligning Superintelligence with Human Interests: A Technical Research Agenda”, in The Technological Singularity (Berlin and Heidelberg: Springer, 2017), 103–125. See also Stephen M. Omohundro, “The Basic AI Drives”, in Proceedings of the First Conference on Artificial General Intelligence, 2008. 141Ibid. 142Nick Bostrom, Superintelligence : Paths, Dangers, Strategies (Oxford: Oxford University Press, 2014), Chapter 9. 143See John von Neumann and Oskar Morgenstern, Theory of Games and Economic Behavior (Princeton, NJ: Princeton University Press, 1944). 144Nate Soares and Benja Fallenstein, “Toward Idealized Decision Theory”, Technical Report 2014–7 (Berkeley, CA: Machine Intelligence Research Institute, 2014), https://​arxiv.​org/​abs/​1507.​01986, accessed 1 June 2018. 145See, for example, Thomas Harris, The Silence of the Lambs (London: St.


pages: 489 words: 148,885

Accelerando by Stross, Charles

book value, business cycle, call centre, carbon-based life, cellular automata, cognitive dissonance, commoditize, Conway's Game of Life, dark matter, disinformation, dumpster diving, Extropian, financial engineering, finite state, flag carrier, Flynn Effect, Future Shock, glass ceiling, gravity well, John von Neumann, junk bonds, Kickstarter, knapsack problem, Kuiper Belt, machine translation, Magellanic Cloud, mandelbrot fractal, market bubble, means of production, military-industrial complex, MITM: man-in-the-middle, Neal Stephenson, orbital mechanics / astrodynamics, packet switching, performance metric, phenotype, planetary scale, Pluto: dwarf planet, quantum entanglement, reversible computing, Richard Stallman, satellite internet, SETI@home, Silicon Valley, Singularitarianism, Skinner box, slashdot, South China Sea, stem cell, technological singularity, telepresence, The Chicago School, theory of mind, Turing complete, Turing machine, Turing test, upwardly mobile, Vernor Vinge, Von Neumann architecture, warehouse robotics, web of trust, Y2K, zero-sum game

"Oh, one of Johnny's toys – a micromechanical digital phonograph player," Gianni says dismissively. "He used to design Babbage engines for the Pentagon – stealth computers. (No van Eck radiation, you know.) Look." He carefully pulls a fabric-bound document out of the obsolescent data wall and shows the spine to Manfred: "On the Theory of Games, by John von Neumann. Signed first edition." Aineko meeps and dumps a slew of confusing purple finite state automata into Manfred's left eye. The hardback is dusty and dry beneath his fingertips as he remembers to turn the pages gently. "This copy belonged to the personal library of Oleg Kordiovsky. A lucky man is Oleg: He bought it in 1952, while on a visit to New York, and the MVD let him to keep it."

Presently a braid of processes running on an abstract virtual machine asks him a question that cannot be encoded in any human grammar. Watch and wait, he replies to his passenger. They'll figure out what we are sooner or later. Part 2 Point of Inflexion Life is a process which may be abstracted from other media. – John Von Neumann Chapter 1 Halo The asteroid is running Barney: it sings of love on the high frontier, of the passion of matter for replicators, and its friendship for the needy billions of the Pacific Rim. "I love you," it croons in Amber's ears as she seeks a precise fix on it: "Let me give you a big hug … " A fraction of a light-second away, Amber locks a cluster of cursors together on the signal, trains them to track its Doppler shift, and reads off the orbital elements.


pages: 807 words: 154,435

Radical Uncertainty: Decision-Making for an Unknowable Future by Mervyn King, John Kay

Airbus A320, Alan Greenspan, Albert Einstein, Albert Michelson, algorithmic trading, anti-fragile, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, autonomous vehicles, availability heuristic, banking crisis, Barry Marshall: ulcers, battle of ideas, Bear Stearns, behavioural economics, Benoit Mandelbrot, bitcoin, Black Swan, Boeing 737 MAX, Bonfire of the Vanities, Brexit referendum, Brownian motion, business cycle, business process, capital asset pricing model, central bank independence, collapse of Lehman Brothers, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, DeepMind, demographic transition, discounted cash flows, disruptive innovation, diversification, diversified portfolio, Donald Trump, Dutch auction, easy for humans, difficult for computers, eat what you kill, Eddington experiment, Edmond Halley, Edward Lloyd's coffeehouse, Edward Thorp, Elon Musk, Ethereum, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, fear of failure, feminist movement, financial deregulation, George Akerlof, germ theory of disease, Goodhart's law, Hans Rosling, Helicobacter pylori, high-speed rail, Ignaz Semmelweis: hand washing, income per capita, incomplete markets, inflation targeting, information asymmetry, invention of the wheel, invisible hand, Jeff Bezos, Jim Simons, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, John von Neumann, Kenneth Arrow, Kōnosuke Matsushita, Linda problem, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, market bubble, market fundamentalism, military-industrial complex, Money creation, Moneyball by Michael Lewis explains big data, Monty Hall problem, Nash equilibrium, Nate Silver, new economy, Nick Leeson, Northern Rock, nudge theory, oil shock, PalmPilot, Paul Samuelson, peak oil, Peter Thiel, Philip Mirowski, Phillips curve, Pierre-Simon Laplace, popular electronics, power law, price mechanism, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, railway mania, RAND corporation, reality distortion field, rent-seeking, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Solow, Ronald Coase, sealed-bid auction, shareholder value, Silicon Valley, Simon Kuznets, Socratic dialogue, South Sea Bubble, spectrum auction, Steve Ballmer, Steve Jobs, Steve Wozniak, Suez crisis 1956, Tacoma Narrows Bridge, Thales and the olive presses, Thales of Miletus, The Chicago School, the map is not the territory, The Market for Lemons, The Nature of the Firm, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Thomas Malthus, Toyota Production System, transaction costs, ultimatum game, urban planning, value at risk, world market for maybe five computers, World Values Survey, Yom Kippur War, zero-sum game

Supermarket shoppers filled their trolleys as if they maximised their utility. And decision-makers faced with radical uncertainty behaved as if they maximised their subjective expected utility. This extension of the axiomatic approach from the analysis of consumer choice to decision-making under uncertainty was the result of the work of several US-based scholars. John von Neumann was a polymathic genius who worked on the Manhattan Project and subsequently helped to develop the hydrogen bomb. In their classic work The Theory of Games and Economic Behavior , von Neumann and his Princeton colleague Oskar Morgenstern sought to establish that probabilistic reasoning could provide a coherent and rigorous framework for rational decision-making in a world of uncertainty.

On what basis can we conclude that the men who attended the Paris symposium, among the cleverest people on the planet, were failing to act ‘in accordance with reason or logic’? Rational behaviour is not defined by conformity with a set of axioms set down even by such distinguished thinkers as John von Neumann and Milton Friedman. Styles of reasoning At the end of the nineteenth century, Charles Sanders Pierce, a founder of the American school of pragmatist philosophy, distinguished three broad styles of reasoning. Deductive reasoning reaches logical conclusions from stated premises. For example, ‘Evangelical Christians are Republican.


pages: 211 words: 57,618

Quantum Computing for Everyone by Chris Bernhardt

Albert Einstein, complexity theory, correlation does not imply causation, discrete time, John von Neumann, low earth orbit, P = NP, quantum cryptography, quantum entanglement, reversible computing, Richard Feynman, selection bias, Turing machine, Von Neumann architecture

Entropy is also defined in thermodynamics. In fact, this is where Shannon got the idea. How closely are these two entropies related to one another? Can some of the theory of computation be expressed in terms of thermodynamics? In particular, can one talk about the minimum energy required performing a calculation? John von Neumann conjectured that when information was lost energy is expended—it dissipates as heat. Rolf Landauer proved the result and gave the minimum possible amount of energy to erase one bit of information. This amount of energy is called the Landauer limit. If the computation is reversible, however, no information is lost and theoretically it can be performed with no energy loss.


pages: 230 words: 61,702

The Internet of Us: Knowing More and Understanding Less in the Age of Big Data by Michael P. Lynch

Affordable Care Act / Obamacare, Amazon Mechanical Turk, big data - Walmart - Pop Tarts, bitcoin, Cass Sunstein, Claude Shannon: information theory, cognitive load, crowdsourcing, data science, Edward Snowden, Firefox, Google Glasses, hive mind, income inequality, Internet of things, John von Neumann, meta-analysis, Nate Silver, new economy, Nick Bostrom, Panopticon Jeremy Bentham, patient HM, prediction markets, RFID, sharing economy, Steve Jobs, Steven Levy, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Twitter Arab Spring, WikiLeaks

Is it possible that the smartest guy in the room is the room? That is, can networks themselves know? There are a few different ways to approach this question. One way has to do with what those in the AI (artificial intelligence) biz call “the singularity”—a term usually credited to the mathematician John von Neumann. The basic idea is that at some point machines—particularly computer networks—will become intelligent enough to become self-aware, and powerful enough to take control. The possibility of the singularity raises a host of interesting philosophical questions, but I want to focus on one issue that is already with us.


pages: 544 words: 168,076

Red Plenty by Francis Spufford

Adam Curtis, affirmative action, anti-communist, Anton Chekhov, asset allocation, Buckminster Fuller, clean water, cognitive dissonance, computer age, double helix, Fellow of the Royal Society, John von Neumann, Kickstarter, Kim Stanley Robinson, Kitchen Debate, linear programming, lost cosmonauts, market clearing, MITM: man-in-the-middle, New Journalism, oil shock, Philip Mirowski, plutocrats, profit motive, RAND corporation, scientific management, Simon Kuznets, the scientific method

He could tune up the whole Soviet orchestra, if they’d let him. His left foot dripped. He really must find a way to get new shoes. Notes – I.1 The Prodigy, 1938 1 Without thinking about it, Leonid Vitalevich: Leonid Vitalevich Kantorich (1912–86), mathematician and economist, nearest Soviet equivalent to John von Neumann, later (1975) to be the only Soviet winner of the Nobel Prize for Economics (shared with Tjalling Koopmans). Calling someone by first name and patronymic expresses formal esteem, in Russian; he is mostly referred to that way here, to suggest that he is being viewed with respectful acquaintance but not intimacy.

There are many, many editions, but see, for example, V.I.Lenin, Selected Works vol. 2 (Moscow: Progress Publishers, 1970). I.1 The Prodigy, 1938 1 Without thinking about it, Leonid Vitalevich: Leonid Vitalevich Kantorovich (1912–86), mathematician and economist, nearest Soviet equivalent to John von Neumann, later (1975) to be the only Soviet winner of the Nobel Prize for Economics (shared with Tjalling Koopmans). Calling someone by first name and patronymic expresses formal esteem, in Russian; he is mostly referred to that way here, to suggest that he is being viewed with respectful acquaintance but not intimacy.


pages: 578 words: 168,350

Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies by Geoffrey West

"World Economic Forum" Davos, Alfred Russel Wallace, Anthropocene, Anton Chekhov, Benoit Mandelbrot, Black Swan, British Empire, butterfly effect, caloric restriction, caloric restriction, carbon footprint, Cesare Marchetti: Marchetti’s constant, clean water, coastline paradox / Richardson effect, complexity theory, computer age, conceptual framework, continuous integration, corporate social responsibility, correlation does not imply causation, cotton gin, creative destruction, dark matter, Deng Xiaoping, double helix, driverless car, Dunbar number, Edward Glaeser, endogenous growth, Ernest Rutherford, first square of the chessboard, first square of the chessboard / second half of the chessboard, Frank Gehry, Geoffrey West, Santa Fe Institute, Great Leap Forward, Guggenheim Bilbao, housing crisis, Index librorum prohibitorum, invention of agriculture, invention of the telephone, Isaac Newton, Jane Jacobs, Jeff Bezos, Johann Wolfgang von Goethe, John von Neumann, Kenneth Arrow, laissez-faire capitalism, Large Hadron Collider, Larry Ellison, Lewis Mumford, life extension, Mahatma Gandhi, mandelbrot fractal, Marc Benioff, Marchetti’s constant, Masdar, megacity, Murano, Venice glass, Murray Gell-Mann, New Urbanism, Oklahoma City bombing, Peter Thiel, power law, profit motive, publish or perish, Ray Kurzweil, Richard Feynman, Richard Florida, Salesforce, seminal paper, Silicon Valley, smart cities, Stephen Hawking, Steve Jobs, Stewart Brand, Suez canal 1869, systematic bias, systems thinking, technological singularity, The Coming Technological Singularity, The Death and Life of Great American Cities, the scientific method, the strength of weak ties, time dilation, too big to fail, transaction costs, urban planning, urban renewal, Vernor Vinge, Vilfredo Pareto, Von Neumann architecture, Whole Earth Catalog, Whole Earth Review, wikimedia commons, working poor

Soon it will have to take twenty-five, then twenty, then seventeen, and so on, and like Sisyphus we are destined to go on doing it, if we insist on continually growing and expanding. The resulting sequence of singularities, each of which threatens stagnation and collapse, will continue to pile up, leading to what mathematicians call an essential singularity—a sort of mother of all singularities. The great John von Neumann, mathematician, physicist, computer scientist, and polymath, a man whose ideas and accomplishments have had a huge influence on your life, made the following remarkably prescient observation more than seventy years ago: “The ever accelerating progress of technology and changes in the mode of human life . . . gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.”7 Among von Neumann’s many accomplishments before he died at the relatively young age of fifty-three in 1957 are his seminal role in the early development of quantum mechanics, his invention of game theory, which is a major tool in economic modeling, and the conceptual design of modern computers universally referred to as the von Neumann architecture.

Kurzweil, The Singularity Is Near: When Humans Transcend Biology (New York: Viking, 2005). 6. V. Vinge, “The Coming Technological Singularity: How to Survive in the Post-Human Era,” Whole Earth Review (1993). 7. This is quoted by the great mathematician Stanislaw Ulam in a eulogy to von Neumann following his death in 1957: “Tribute to John von Neumann,” Bulletin of the American Mathematical Society 5(3), part 2 (1958): 64. 8. C. McCarthy, The Road (New York: Alfred A. Knopf, 2006). AFTERWORD 1. Two popular nontechnical books that present a broad overview of the enormously exciting quest for the fundamental constituents of matter and a grand unified theory for understanding their interactions, including its extension to the evolution of the cosmos and the origin of space-time itself, are S.


pages: 604 words: 161,455

The Moral Animal: Evolutionary Psychology and Everyday Life by Robert Wright

agricultural Revolution, Andrei Shleifer, Apollo 13, Asian financial crisis, British Empire, centre right, cognitive dissonance, cotton gin, double entry bookkeeping, double helix, Easter island, fault tolerance, Francis Fukuyama: the end of history, Garrett Hardin, George Gilder, global village, Great Leap Forward, invention of gunpowder, invention of movable type, invention of the telegraph, invention of writing, invisible hand, John Nash: game theory, John von Neumann, Marshall McLuhan, Multics, Norbert Wiener, planetary scale, planned obsolescence, pre–internet, profit motive, Ralph Waldo Emerson, random walk, Richard Thaler, rising living standards, Robert Solow, Silicon Valley, social intelligence, social web, Steven Pinker, talking drums, technological determinism, the medium is the message, The Wealth of Nations by Adam Smith, trade route, Tragedy of the Commons, your tax dollars at work, zero-sum game

THE SECRET OF LIFE On the day James Watson and Francis Crick discovered the structure of DNA, Crick, as Watson later recalled it, walked into their regular lunch place and announced that they had “found the secret of life.” With all due respect for DNA, I would like to nominate another candidate for the secret of life. Unlike Francis Crick, I can’t claim to have discovered the secret I’m touting. It was discovered—or, if you prefer, invented—about half a century ago by the founders of game theory, John von Neumann and Oskar Morgenstern. They made a basic distinction between “zero-sum” games and “non-zero-sum” games. In zero-sum games, the fortunes of the players are inversely related. In tennis, in chess, in boxing, one contestant’s gain is the other’s loss. In non-zero-sum games, one player’s gain needn’t be bad news for the other(s).

Schelling is surely right that a zero-sum game is merely a special case of a fixed-sum game—the case in which the sum is fixed at zero. So the “fixed-sum/variable-sum” terminology is, strictly speaking, more generally applicable to life. But “zero-sum/non-zero-sum” is the terminology used by the founders of game theory, John von Neumann and Oskar Morgenstern, and it remains in common use. And its implication that there are negative-sum and positive-sum games—though slippery on close inspection—is useful for present purposes. Sun Tzu’s advice: Cotterell (1995), p. 243. †heedlessly launching war: The reasons for this are complex and variable, but one is that within a given society, per pectives differ.


pages: 442 words: 39,064

Why Stock Markets Crash: Critical Events in Complex Financial Systems by Didier Sornette

Alan Greenspan, Asian financial crisis, asset allocation, behavioural economics, Berlin Wall, Black Monday: stock market crash in 1987, Bretton Woods, Brownian motion, business cycle, buy and hold, buy the rumour, sell the news, capital asset pricing model, capital controls, continuous double auction, currency peg, Deng Xiaoping, discrete time, diversified portfolio, Elliott wave, Erdős number, experimental economics, financial engineering, financial innovation, floating exchange rates, frictionless, frictionless market, full employment, global village, implied volatility, index fund, information asymmetry, intangible asset, invisible hand, John von Neumann, joint-stock company, law of one price, Louis Bachelier, low interest rates, mandelbrot fractal, margin call, market bubble, market clearing, market design, market fundamentalism, mental accounting, moral hazard, Network effects, new economy, oil shock, open economy, pattern recognition, Paul Erdős, Paul Samuelson, power law, quantitative trading / quantitative finance, random walk, risk/return, Ronald Reagan, Schrödinger's Cat, selection bias, short selling, Silicon Valley, South Sea Bubble, statistical model, stochastic process, stocks for the long run, Tacoma Narrows Bridge, technological singularity, The Coming Technological Singularity, The Wealth of Nations by Adam Smith, Tobin tax, total factor productivity, transaction costs, tulip mania, VA Linux, Y2K, yield curve

The most important tool in this analysis was game theory: the study of situations, like poker or chess games, in which players have to make their decisions based on guesses about what the other player is going to do next. Game theory was first adapted to economics in the 1940s by mathematician John von Neumann (the same von Neumann whose theoretical insights made the computer possible) and economist O. Morgenstern. Since then, the standard economics and social science model of a human agent is that it is like a general-purpose logic machine. All decision tasks, regardless of context, constitute optimization problems subject to external constraints whether from the physical environment or from the reaction functions of other agents.

Gambling with the house money and trying to break even: The effects of prior outcomes on risky choice, Management Science 36, 643–660. 426. Toner, J. and Tu, Y. H. (1998). Flocks, herds, and schools: A quantitative theory of flocking, Physical Review E 58, 4828–4858. 427. Trueman, B. (1994). Analyst forecasts and herding behavior, The Review of Financial Studies 7, 97–124. 428. Ulam, S. (1959). Tribute to John von Neumann, Bulletin of the American Mathematical Society 64, 1–49. 429. U.S. Committee of the Global Atmospheric Research Program (1975). Understanding Climatic Change—A Program for Action (National Research Council, National Academy of Sciences, Washington, D.C.). 430. U.S. Postage Release No. 99-045, May 21, 1999. 431.


pages: 391 words: 71,600

Hit Refresh: The Quest to Rediscover Microsoft's Soul and Imagine a Better Future for Everyone by Satya Nadella, Greg Shaw, Jill Tracie Nichols

3D printing, AlphaGo, Amazon Web Services, anti-globalists, artificial general intelligence, augmented reality, autonomous vehicles, basic income, Bretton Woods, business process, cashless society, charter city, cloud computing, complexity theory, computer age, computer vision, corporate social responsibility, crowdsourcing, data science, DeepMind, Deng Xiaoping, Donald Trump, Douglas Engelbart, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, equal pay for equal work, everywhere but in the productivity statistics, fault tolerance, fulfillment center, Gini coefficient, global supply chain, Google Glasses, Grace Hopper, growth hacking, hype cycle, industrial robot, Internet of things, Jeff Bezos, job automation, John Markoff, John von Neumann, knowledge worker, late capitalism, Mars Rover, Minecraft, Mother of all demos, Neal Stephenson, NP-complete, Oculus Rift, pattern recognition, place-making, Richard Feynman, Robert Gordon, Robert Solow, Ronald Reagan, Salesforce, Second Machine Age, self-driving car, side project, Silicon Valley, Skype, Snapchat, Snow Crash, special economic zone, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, subscription business, TED Talk, telepresence, telerobotics, The Rise and Fall of American Growth, The Soul of a New Machine, Tim Cook: Apple, trade liberalization, two-sided market, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, young professional, zero-sum game

In other words, how can I solve a problem that has limitless possibilities in a way that is fast and good but not always optimal? Do we solve this as best we can right now, or work forever for the best solution? Theoretical computer science really grabbed me because it showed the limits to what today’s computers can do. It led me to become fascinated by mathematicians and computer scientists John Von Neumann and Alan Turing, and by quantum computing, which I will write about later as we look ahead to artificial intelligence and machine learning. And, if you think about it, this was great training for a CEO—nimbly managing within constraints. I completed my master’s in computer science at Wisconsin and even managed to work for what Microsoft would now call an independent software vendor (ISV).


pages: 222 words: 70,132

Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy by Jonathan Taplin

"Friedman doctrine" OR "shareholder theory", "there is no alternative" (TINA), 1960s counterculture, affirmative action, Affordable Care Act / Obamacare, Airbnb, AlphaGo, Amazon Mechanical Turk, American Legislative Exchange Council, AOL-Time Warner, Apple's 1984 Super Bowl advert, back-to-the-land, barriers to entry, basic income, battle of ideas, big data - Walmart - Pop Tarts, Big Tech, bitcoin, Brewster Kahle, Buckminster Fuller, Burning Man, Clayton Christensen, Cody Wilson, commoditize, content marketing, creative destruction, crony capitalism, crowdsourcing, data is the new oil, data science, David Brooks, David Graeber, decentralized internet, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, equal pay for equal work, Erik Brynjolfsson, Fairchild Semiconductor, fake news, future of journalism, future of work, George Akerlof, George Gilder, Golden age of television, Google bus, Hacker Ethic, Herbert Marcuse, Howard Rheingold, income inequality, informal economy, information asymmetry, information retrieval, Internet Archive, Internet of things, invisible hand, Jacob Silverman, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John Perry Barlow, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kickstarter, labor-force participation, Larry Ellison, life extension, Marc Andreessen, Mark Zuckerberg, Max Levchin, Menlo Park, Metcalfe’s law, military-industrial complex, Mother of all demos, move fast and break things, natural language processing, Network effects, new economy, Norbert Wiener, offshore financial centre, packet switching, PalmPilot, Paul Graham, paypal mafia, Peter Thiel, plutocrats, pre–internet, Ray Kurzweil, reality distortion field, recommendation engine, rent-seeking, revision control, Robert Bork, Robert Gordon, Robert Metcalfe, Ronald Reagan, Ross Ulbricht, Sam Altman, Sand Hill Road, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skinner box, smart grid, Snapchat, Social Justice Warrior, software is eating the world, Steve Bannon, Steve Jobs, Stewart Brand, tech billionaire, techno-determinism, technoutopianism, TED Talk, The Chicago School, the long tail, The Market for Lemons, The Rise and Fall of American Growth, Tim Cook: Apple, trade route, Tragedy of the Commons, transfer pricing, Travis Kalanick, trickle-down economics, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, unpaid internship, vertical integration, We are as Gods, We wanted flying cars, instead we got 140 characters, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator, you are the product

Ready or not, computers are coming to the people. That’s good news, maybe the best since psychedelics. It’s way off the track of the “Computers—Threat or menace?” school of liberal criticism but surprisingly in line with the romantic fantasies of the forefathers of the science such as Norbert Wiener, Warren McCulloch, J.C.R. Licklider, John von Neumann and Vannevar Bush. The trend owes its health to an odd array of influences: The youthful fervor and firm dis-Establishmentarianism of the freaks who design computer science; an astonishingly enlightened research program from the very top of the Defense Department; an unexpected market-Banking movement by the manufacturers of small calculating machines; and an irrepressible midnight phenomenon known as Spacewar.


pages: 212 words: 65,900

Symmetry and the Monster by Ronan, Mark

Albert Einstein, Andrew Wiles, Bletchley Park, conceptual framework, Everything should be made as simple as possible, G4S, Henri Poincaré, John Conway, John von Neumann, Kickstarter, New Journalism, Pierre-Simon Laplace, Richard Feynman, V2 rocket

The Moonshine connections have spawned conferences where mathematicians and mathematical physicists meet to discuss these things, but let us begin with the study of symmetry itself, starting with the work of the ancient Greeks. 1 Theaetetus’s Icosahedron In mathematics you don’t understand things. You just get used to them. John von Neumann (1903–57) In 369 BCE an Athenian philosopher named Theaetetus was wounded in a battle at Corinth, and carried home. He contracted dysentery and died in Athens. None of his writings survive, but we know of his work through later commentators, and know about him personally from Plato, who records two dialogues with Theaetetus as the main character.


pages: 224 words: 64,156

You Are Not a Gadget by Jaron Lanier

1960s counterculture, Abraham Maslow, accounting loophole / creative accounting, additive manufacturing, Albert Einstein, Bear Stearns, call centre, cloud computing, commoditize, crowdsourcing, death of newspapers, different worldview, digital Maoism, Douglas Hofstadter, Extropian, follow your passion, General Magic , hive mind, Internet Archive, Jaron Lanier, jimmy wales, John Conway, John Perry Barlow, John von Neumann, Kevin Kelly, Long Term Capital Management, Neal Stephenson, Network effects, new economy, packet switching, PageRank, pattern recognition, Ponzi scheme, Project Xanadu, Ray Kurzweil, Richard Stallman, Savings and loan crisis, Silicon Valley, Silicon Valley startup, slashdot, social graph, stem cell, Steve Jobs, Stewart Brand, Stuart Kauffman, synthetic biology, technological determinism, Ted Nelson, telemarketer, telepresence, the long tail, The Wisdom of Crowds, trickle-down economics, Turing test, Vernor Vinge, Whole Earth Catalog

CHAPTER 2 An Apocalypse of Self-Abdication THE IDEAS THAT I hope will not be locked in rest on a philosophical foundation that I sometimes call cybernetic totalism. It applies metaphors from certain strains of computer science to people and the rest of reality. Pragmatic objections to this philosophy are presented. What Do You Do When the Techies Are Crazier Than the Luddites? The Singularity is an apocalyptic idea originally proposed by John von Neumann, one of the inventors of digital computation, and elucidated by figures such as Vernor Vinge and Ray Kurzweil. There are many versions of the fantasy of the Singularity. Here’s the one Marvin Minsky used to tell over the dinner table in the early 1980s: One day soon, maybe twenty or thirty years into the twenty-first century, computers and robots will be able to construct copies of themselves, and these copies will be a little better than the originals because of intelligent software.


pages: 239 words: 64,812

Geek Sublime: The Beauty of Code, the Code of Beauty by Vikram Chandra

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Apple II, barriers to entry, Berlin Wall, Big Tech, British Empire, business process, Californian Ideology, Charles Babbage, conceptual framework, create, read, update, delete, crowdsourcing, don't repeat yourself, Donald Knuth, East Village, European colonialism, finite state, Firefox, Flash crash, functional programming, glass ceiling, Grace Hopper, Hacker News, haute couture, hype cycle, iterative process, Jaron Lanier, John von Neumann, land reform, London Whale, Norman Mailer, Paul Graham, pink-collar, revision control, Silicon Valley, Silicon Valley ideology, Skype, Steve Jobs, Steve Wozniak, supercomputer in your pocket, synthetic biology, tech worker, the Cathedral and the Bazaar, theory of mind, Therac-25, Turing machine, wikimedia commons, women in the workforce

“The telephone switchboard-like appearance of the ENIAC programming cable-and-plug panels,” Ensmenger writes, “reinforced the notion that programmers were mere machine operators, that programming was more handicraft than science, more feminine than masculine, more mechanical than intellectual.”18 The planners considered the coding process so transparently simple that they couldn’t imagine that once in the machines, their algorithms might fault and hang, might need to be stopped. One of the ENIAC programmers, Betty Holberton, had to work very hard to convince John von Neumann that programs were complex and therefore fragile: But to my astonishment, [Dr von Neumann] never mentioned a stop instruction. So I did coyly say, “Don’t we need a stop instruction in this machine?” He said, “No we don’t need a stop instruction. We have all these empty sockets here that just let it go to bed.”


pages: 239 words: 56,531

The Secret War Between Downloading and Uploading: Tales of the Computer as Culture Machine by Peter Lunenfeld

Albert Einstein, Andrew Keen, anti-globalists, Apple II, Berlin Wall, British Empire, Brownian motion, Buckminster Fuller, Burning Man, business cycle, business logic, butterfly effect, Charles Babbage, computer age, Computing Machinery and Intelligence, creative destruction, crowdsourcing, cuban missile crisis, Dissolution of the Soviet Union, don't be evil, Douglas Engelbart, Douglas Engelbart, Dynabook, East Village, Edward Lorenz: Chaos theory, Fairchild Semiconductor, Fall of the Berlin Wall, folksonomy, Francis Fukuyama: the end of history, Frank Gehry, Free Software Foundation, Grace Hopper, gravity well, Guggenheim Bilbao, Herman Kahn, Honoré de Balzac, Howard Rheingold, Ian Bogost, invention of movable type, Isaac Newton, Ivan Sutherland, Jacquard loom, Jane Jacobs, Jeff Bezos, John Markoff, John von Neumann, Jon Ronson, Kickstarter, Mark Zuckerberg, Marshall McLuhan, Mercator projection, Metcalfe’s law, Mother of all demos, mutually assured destruction, Neal Stephenson, Nelson Mandela, Network effects, new economy, Norbert Wiener, PageRank, pattern recognition, peer-to-peer, planetary scale, plutocrats, post-materialism, Potemkin village, RFID, Richard Feynman, Richard Stallman, Robert Metcalfe, Robert X Cringely, Schrödinger's Cat, Search for Extraterrestrial Intelligence, seminal paper, SETI@home, Silicon Valley, Skype, social bookmarking, social software, spaced repetition, Steve Ballmer, Steve Jobs, Steve Wozniak, technological determinism, Ted Nelson, the built environment, the Cathedral and the Bazaar, The Death and Life of Great American Cities, the medium is the message, Thomas L Friedman, Turing machine, Turing test, urban planning, urban renewal, Vannevar Bush, walkable city, Watson beat the top human players on Jeopardy!, William Shockley: the traitorous eight

—Vannevar Bush People tend to overestimate what can be done in one year and underestimate what can be done in five to ten years. —J.C.R. Licklider 147 GENERATIONS There are many mathematicians, early computer scientists, and engineers who deserve to be considered part of the first generation of pioneering Patriarchs. They include Alan Turing, already discussed in chapter 2; mathematician and quantum theorist John von Neumann; cyberneticist Norbert Wiener; information theorist Claude Shannon; and computer architects like the German Konrad Zuse, and Americans J. Presper Eckert and John Mauchly, who developed ENIAC, the room-sized machine at the University of Pennsylvania that we recognize as the first general-purpose electronic computer.


pages: 239 words: 70,206

Data-Ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else by Steve Lohr

"World Economic Forum" Davos, 23andMe, Abraham Maslow, Affordable Care Act / Obamacare, Albert Einstein, Alvin Toffler, Bear Stearns, behavioural economics, big data - Walmart - Pop Tarts, bioinformatics, business cycle, business intelligence, call centre, Carl Icahn, classic study, cloud computing, computer age, conceptual framework, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, Danny Hillis, data is the new oil, data science, David Brooks, driverless car, East Village, Edward Snowden, Emanuel Derman, Erik Brynjolfsson, everywhere but in the productivity statistics, financial engineering, Frederick Winslow Taylor, Future Shock, Google Glasses, Ida Tarbell, impulse control, income inequality, indoor plumbing, industrial robot, informal economy, Internet of things, invention of writing, Johannes Kepler, John Markoff, John von Neumann, lifelogging, machine translation, Mark Zuckerberg, market bubble, meta-analysis, money market fund, natural language processing, obamacare, pattern recognition, payday loans, personalized medicine, planned obsolescence, precision agriculture, pre–internet, Productivity paradox, RAND corporation, rising living standards, Robert Gordon, Robert Solow, Salesforce, scientific management, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, SimCity, six sigma, skunkworks, speech recognition, statistical model, Steve Jobs, Steven Levy, The Design of Experiments, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Tony Fadell, unbanked and underbanked, underbanked, Von Neumann architecture, Watson beat the top human players on Jeopardy!, yottabyte

The big-data era is the next evolutionary upheaval in the landscape of computing. The things people want to do with data, like real-time analysis of data streams or continuously running machine-learning software, pose a threat to the traditional computer industry. Conventional computing—the Von Neumann architecture, named for mathematician and computer scientist John von Neumann—operates according to discrete steps of program, store, and process. Major companies and markets were built around those tiers of computing—software, disk drives, and microprocessors, respectively. Modern data computing, according to John Kelly, IBM’s senior vice president in charge of research, will “completely disrupt the industry as we know it, creating new platforms and players.”


Work in the Future The Automation Revolution-Palgrave MacMillan (2019) by Robert Skidelsky Nan Craig

3D printing, Airbnb, algorithmic trading, AlphaGo, Alvin Toffler, Amazon Web Services, anti-work, antiwork, artificial general intelligence, asset light, autonomous vehicles, basic income, behavioural economics, business cycle, cloud computing, collective bargaining, Computing Machinery and Intelligence, correlation does not imply causation, creative destruction, data is the new oil, data science, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, disintermediation, do what you love, Donald Trump, driverless car, Erik Brynjolfsson, fake news, feminist movement, Ford Model T, Frederick Winslow Taylor, future of work, Future Shock, general purpose technology, gig economy, global supply chain, income inequality, independent contractor, informal economy, Internet of things, Jarndyce and Jarndyce, Jarndyce and Jarndyce, job automation, job polarisation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, knowledge economy, Loebner Prize, low skilled workers, Lyft, Mark Zuckerberg, means of production, moral panic, Network effects, new economy, Nick Bostrom, off grid, pattern recognition, post-work, Ronald Coase, scientific management, Second Machine Age, self-driving car, sharing economy, SoftBank, Steve Jobs, strong AI, tacit knowledge, technological determinism, technoutopianism, TED Talk, The Chicago School, The Future of Employment, the market place, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, Turing test, Uber for X, uber lyft, universal basic income, wealth creators, working poor

Pew Research Center. Retrieved from http://www.pewresearch.org/fact-tank/2017/10/09/most-americanswould-favor-policies-to-limit-job-and-wage-lossescaused-by-automation/ Part IV Possibilities and Limitations for AI: What Can’t Machines Do? 11 What Computers Will Never Be Able To Do Thomas Tozer In 1948, John von Neumann, a father of the computer revolution, claimed that for anything he was told a computer could not do, after this ‘thing’ had been explained to him precisely he would be able to make a machine capable of doing it. Many scientists and philosophers strongly rejected this. For, they responded, there was something unique to humans that neither von Neumann, nor anyone else, would ever be able to replicate in a computer.


pages: 256 words: 67,563

Explaining Humans: What Science Can Teach Us About Life, Love and Relationships by Camilla Pang

autism spectrum disorder, backpropagation, bioinformatics, Brownian motion, correlation does not imply causation, data science, deep learning, driverless car, frictionless, job automation, John Nash: game theory, John von Neumann, Kickstarter, Nash equilibrium, neurotypical, phenotype, random walk, self-driving car, stem cell, Stephen Hawking

For that we need to delve into the science of game theory, which maps not just how different agents in a system interact, but what their motivations are, and why they make certain decisions. Game theory was pioneered by two mathematicians whose work helped lay the foundations for the modern study of artificial intelligence: John von Neumann and John Nash. Like agent-based models, it looks at how different players within a certain, rules-based system interact. But it goes further by looking at the consequences of their various choices: how will a decision by one or several players in the game affect everyone else? Game theory looks at the whole picture, assuming a player doesn’t just consider their own decisions and their consequences, but those of the other players as well – predicting both what they may know, and how they are likely to act.


The Art of Computer Programming: Fundamental Algorithms by Donald E. Knuth

Charles Babbage, discrete time, distributed generation, Donald Knuth, fear of failure, Fermat's Last Theorem, G4S, Gerard Salton, Isaac Newton, Ivan Sutherland, Jacquard loom, Johannes Kepler, John von Neumann, linear programming, linked data, Menlo Park, probability theory / Blaise Pascal / Pierre de Fermat, sorting algorithm, stochastic process, Turing machine

Dijkstra, CACM 18 A975), 453-457; A Discipline of Programming (Prentice-Hall, 1976).] 18 BASIC CONCEPTS 1.2.1 The concept of inductive assertions actually appeared in embryonic form in 1946, at the same time as flow charts were introduced by H. H. Goldstine and J. von Neumann. Their original flow charts included "assertion boxes" that are in close analogy with the assertions in Fig. 4. [See John von Neumann, Collected Works 5 (New York: Macmillan, 1963), 91-99. See also A. M. Turing's early comments about verification in Report of a Conference on High Speed Automatic Calculating Machines (Cambridge Univ., 1949), 67-68 and figures; reprinted with commentary by F. L. Morris and C. B. Jones in Annals of the History of Computing 6 A984), 139-143.]

Babbage's planned machine was controlled by sequences of punched cards, as on the Jacquard loom; the Mark I was controlled by a number of paper tapes. Thus they were quite different from today's stored- program computers. Subroutine linkage appropriate to stored-program machines, with the return address supplied as a parameter, was discussed by Herman H. Goldstine and John von Neumann in their widely circulated monograph on programming, written during 1946 and 1947; see von Neumann's Collected Works 5 (New York: Macmillan, 1963), 215-235. The main routine of their programs was responsible for storing parameters into the body of the subroutine, instead of passing the necessary information in registers.

The paper "Input- Output Buffering and FORTRAN" by David E. Ferguson, JACM 7 A960), 1-9, describes buffer circles and gives a detailed description of simple buffering with many units at once. About 1000 instructions is a reasonable upper limit for the complexity of the problems new envisioned. — HERMAN GOLDSTINE and JOHN VON NEUMANN A946) CHAPTER TWO INFORMATION STRUCTURES / think that I shall never see A poem lovely as a tree. — JOYCE KILMER A913) Yea, from the table of my memory I'll wipe away all trivial fond records. — Hamlet (Act I, Scene 5, Line 98) 2.1. INTRODUCTION Computer programs usually operate on tables of information.


pages: 1,073 words: 314,528

Strategy: A History by Lawrence Freedman

Albert Einstein, anti-communist, Anton Chekhov, Ayatollah Khomeini, barriers to entry, battle of ideas, behavioural economics, Black Swan, Blue Ocean Strategy, British Empire, business process, butterfly effect, centre right, Charles Lindbergh, circulation of elites, cognitive dissonance, coherent worldview, collective bargaining, complexity theory, conceptual framework, Cornelius Vanderbilt, corporate raider, correlation does not imply causation, creative destruction, cuban missile crisis, Daniel Kahneman / Amos Tversky, defense in depth, desegregation, disinformation, Dr. Strangelove, Edward Lorenz: Chaos theory, en.wikipedia.org, endogenous growth, endowment effect, escalation ladder, Ford Model T, Ford paid five dollars a day, framing effect, Frederick Winslow Taylor, Gordon Gekko, greed is good, Herbert Marcuse, Herman Kahn, Ida Tarbell, information retrieval, interchangeable parts, invisible hand, John Nash: game theory, John von Neumann, Kenneth Arrow, lateral thinking, linear programming, loose coupling, loss aversion, Mahatma Gandhi, means of production, mental accounting, Murray Gell-Mann, mutually assured destruction, Nash equilibrium, Nelson Mandela, Norbert Wiener, Norman Mailer, oil shock, Pareto efficiency, performance metric, Philip Mirowski, prisoner's dilemma, profit maximization, race to the bottom, Ralph Nader, RAND corporation, Richard Thaler, road to serfdom, Ronald Reagan, Rosa Parks, scientific management, seminal paper, shareholder value, social contagion, social intelligence, Steven Pinker, strikebreaker, The Chicago School, The Myth of the Rational Market, the scientific method, theory of mind, Thomas Davenport, Thomas Kuhn: the structure of scientific revolutions, Torches of Freedom, Toyota Production System, transaction costs, Twitter Arab Spring, ultimatum game, unemployed young men, Upton Sinclair, urban sprawl, Vilfredo Pareto, W. E. B. Du Bois, War on Poverty, women in the workforce, Yogi Berra, zero-sum game

Nonetheless, game theory represented a way of thinking about strategic issues that was abstract and formal. Its influence on the social sciences eventually became significant. It emerged as the result of collaboration between two European émigrés working at Princeton during the war. From Hungary came John von Neumann. As a child he could astound with feats of memory and computation, and he was soon recognized as one of the mathematical geniuses of his age. He had developed the basic principle of game theory in the 1920s by contemplating poker. When Oskar Morgenstern, an economist from Vienna, got to know von Neumann at Princeton he saw the broader significance of his ideas and helped give them structure.

In this they were influenced by Friedrich Hayek, an Austrian who had acquired British citizenship in 1938 and had been teaching at the London School of Economics until he was recruited to Chicago, though not by the economics department, in 1950. His most famous book, The Road to Serfdom, was published during the war and warned against the inclination to central planning that was gathering momentum under the combined influence of socialism and the wartime experience. Meanwhile, the Cowles Commission, influenced by John von Neumann and sponsored by RAND, was up for new methodological challenges and was more inclined to believe that robust models could support enlightened policy. Either way the assumptions and methods associated with game theory became part of a wider project to develop new forms of social science. Economics into Business The Ford Foundation was at the fore in exploring how management within big government and big business could become vital instruments of efficiency and progress.

For a critique of the role of systems analysis, see Stephen Rosen, “Systems Analysis and the Quest for Rational Defense,” The Public Interest 76 (Summer 1984): 121–159. 17. Bernard Brodie, War and Politics (London: Cassell, 1974), 474–475. 18. Cited in William Poundstone, Prisoner’s Dilemma (New York: Doubleday, 1992), 6. 19. Oskar Morgenstern, “The Collaboration between Oskar Morgenstern and John von Neumann,” Journal of Economic Literature 14, no. 3 (September 1976): 805–816. E. Roy Weintraub, Toward a History of Game Theory (London: Duke University Press, 1992); R. Duncan Luce and Howard Raiffa, Games and Decisions; Introduction and Critical Survey (New York: John Wiley & Sons, 1957). 20. Poundstone, Prisoner’s Dilemma, 8. 21.


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Time Travel: A History by James Gleick

Ada Lovelace, Albert Einstein, Albert Michelson, Arthur Eddington, augmented reality, butterfly effect, Charles Babbage, crowdsourcing, Doomsday Book, Eddington experiment, index card, Isaac Newton, John von Neumann, luminiferous ether, Marshall McLuhan, Norbert Wiener, pattern recognition, Plato's cave, pneumatic tube, Richard Feynman, Schrödinger's Cat, self-driving car, Stephen Fry, Stephen Hawking, telepresence, The future is already here, time dilation, Wayback Machine, wikimedia commons

Only at the last instant does he realize whose death he had witnessed as a child. * * * *1 A rebellious elector in Virginia refused to cast his ballot for the vote winners, Richard Nixon and Spiro Agnew, in 1972 and voted instead for John Hospers, on the Libertarian line. *2 Gödel’s proof “is more than a monument,” said John von Neumann, “it is a landmark which will remain visible far in space and time….The subject of logic has completely changed its nature and possibilities with Gödel’s achievement.” *3 Also, the Gödelian universe does not expand, whereas most cosmologists are pretty sure that ours does. *4 Gödel’s biographer Rebecca Goldstein remarked, “As a physicist and a man of common sense, Einstein would have preferred that his field equations excluded such an Alice-in-Wonderland possibility as looping time


pages: 285 words: 78,180

Life at the Speed of Light: From the Double Helix to the Dawn of Digital Life by J. Craig Venter

Albert Einstein, Alfred Russel Wallace, Apollo 11, Asilomar, Barry Marshall: ulcers, bioinformatics, borderless world, Brownian motion, clean water, Computing Machinery and Intelligence, discovery of DNA, double helix, dual-use technology, epigenetics, experimental subject, global pandemic, Gregor Mendel, Helicobacter pylori, Isaac Newton, Islamic Golden Age, John von Neumann, Louis Pasteur, Mars Rover, Mikhail Gorbachev, phenotype, precautionary principle, Recombinant DNA, Richard Feynman, stem cell, Stuart Kauffman, synthetic biology, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Turing machine

Turing also defined a universal Turing machine, which can carry out any computation for which an instruction set can be written. This is the theoretical foundation of the digital computer. Turing’s ideas were developed further in the 1940s, by the remarkable American mathematician and polymath John von Neumann, who conceived of a self-replicating machine. Just as Turing had envisaged a universal machine, so von Neumann envisaged a universal constructor. The Hungarian-born genius outlined his ideas in a lecture, “The General and Logical Theory of Automata,” at the 1948 Hixon Symposium, in Pasadena, California.


pages: 252 words: 73,131

The Inner Lives of Markets: How People Shape Them—And They Shape Us by Tim Sullivan

Abraham Wald, Airbnb, airport security, Al Roth, Alvin Roth, Andrei Shleifer, attribution theory, autonomous vehicles, barriers to entry, behavioural economics, Brownian motion, business cycle, buy and hold, centralized clearinghouse, Chuck Templeton: OpenTable:, classic study, clean water, conceptual framework, congestion pricing, constrained optimization, continuous double auction, creative destruction, data science, deferred acceptance, Donald Trump, Dutch auction, Edward Glaeser, experimental subject, first-price auction, framing effect, frictionless, fundamental attribution error, George Akerlof, Goldman Sachs: Vampire Squid, Gunnar Myrdal, helicopter parent, information asymmetry, Internet of things, invisible hand, Isaac Newton, iterative process, Jean Tirole, Jeff Bezos, Johann Wolfgang von Goethe, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, late fees, linear programming, Lyft, market clearing, market design, market friction, medical residency, multi-sided market, mutually assured destruction, Nash equilibrium, Occupy movement, opioid epidemic / opioid crisis, Pareto efficiency, Paul Samuelson, Peter Thiel, pets.com, pez dispenser, power law, pre–internet, price mechanism, price stability, prisoner's dilemma, profit motive, proxy bid, RAND corporation, ride hailing / ride sharing, Robert Shiller, Robert Solow, Ronald Coase, school choice, school vouchers, scientific management, sealed-bid auction, second-price auction, second-price sealed-bid, sharing economy, Silicon Valley, spectrum auction, Steve Jobs, Tacoma Narrows Bridge, techno-determinism, technoutopianism, telemarketer, The Market for Lemons, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, trade route, transaction costs, two-sided market, uber lyft, uranium enrichment, Vickrey auction, Vilfredo Pareto, WarGames: Global Thermonuclear War, winner-take-all economy

The foundation’s founding motto was “Science is Measurement.”11 The second, the RAND Corporation, first established as a joint project by the Douglas Aircraft Company and the US Department of War in 1945, used game theory to analyze the United States’s geopolitical position relative to the Soviet Union. Game theory—a mathematical approach to analyzing strategic choices—emerged from the work of Princeton mathematician John von Neumann in the 1930s, who collaborated with his economist colleague Oskar Morgenstern to write Theory of Games and Economic Behavior (published in 1944), which launched the field. Their book provided an analytical framework for figuring out, say, what Pepsi should do if Coke lowers its prices. That depends on how Pepsi’s CEO thinks Coke will respond, which in turn depends on what Coke’s CEO expects that Pepsi’s response to their price reduction will be.


pages: 477 words: 75,408

The Economic Singularity: Artificial Intelligence and the Death of Capitalism by Calum Chace

"World Economic Forum" Davos, 3D printing, additive manufacturing, agricultural Revolution, AI winter, Airbnb, AlphaGo, Alvin Toffler, Amazon Robotics, Andy Rubin, artificial general intelligence, augmented reality, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Boston Dynamics, bread and circuses, call centre, Chris Urmson, congestion charging, credit crunch, David Ricardo: comparative advantage, deep learning, DeepMind, Demis Hassabis, digital divide, Douglas Engelbart, Dr. Strangelove, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Fairchild Semiconductor, Flynn Effect, full employment, future of work, Future Shock, gender pay gap, Geoffrey Hinton, gig economy, Google Glasses, Google X / Alphabet X, Hans Moravec, Herman Kahn, hype cycle, ImageNet competition, income inequality, industrial robot, Internet of things, invention of the telephone, invisible hand, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, Kiva Systems, knowledge worker, lifelogging, lump of labour, Lyft, machine translation, Marc Andreessen, Mark Zuckerberg, Martin Wolf, McJob, means of production, Milgram experiment, Narrative Science, natural language processing, Neil Armstrong, new economy, Nick Bostrom, Occupy movement, Oculus Rift, OpenAI, PageRank, pattern recognition, post scarcity, post-industrial society, post-work, precariat, prediction markets, QWERTY keyboard, railway mania, RAND corporation, Ray Kurzweil, RFID, Rodney Brooks, Sam Altman, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, SoftBank, software is eating the world, speech recognition, Stephen Hawking, Steve Jobs, TaskRabbit, technological singularity, TED Talk, The future is already here, The Future of Employment, Thomas Malthus, transaction costs, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber for X, uber lyft, universal basic income, Vernor Vinge, warehouse automation, warehouse robotics, working-age population, Y Combinator, young professional

[iii] There is no general agreement about when the information revolution started. In his 1962 book “The Production and Distribution of Knowledge in the United States”, the Austrian economist Fritz Machler suggested that with 29% of GDP accounted for by the knowledge industry, it had begun. [iv] The term was first applied to human affairs back in the 1950s by John von Neumann, a key figure in the development of the computer. The physicist and science fiction author Vernor Vinge argued in 1993 that artificial intelligence and other technologies would cause a singularity in human affairs within 30 years. This idea was picked up and popularised by the inventor and futurist Ray Kurzweil, who believes that computers will overtake humans in general intelligence in 1929, and a singularity will arrive in 2045. https://en.wikipedia.org/wiki/Technological_singularity [v] The event horizon of a black hole is the point beyond which events cannot affect an outside observer, or in other words, the point of no return.


pages: 260 words: 77,007

Are You Smart Enough to Work at Google?: Trick Questions, Zen-Like Riddles, Insanely Difficult Puzzles, and Other Devious Interviewing Techniques You ... Know to Get a Job Anywhere in the New Economy by William Poundstone

affirmative action, Albert Einstein, big-box store, Buckminster Fuller, car-free, cloud computing, creative destruction, digital rights, en.wikipedia.org, full text search, hiring and firing, How many piano tuners are there in Chicago?, index card, Isaac Newton, Johannes Kepler, John von Neumann, lateral thinking, loss aversion, mental accounting, Monty Hall problem, new economy, off-the-grid, Paul Erdős, RAND corporation, random walk, Richard Feynman, rolodex, Rubik’s Cube, Silicon Valley, Silicon Valley startup, sorting algorithm, Steve Ballmer, Steve Jobs, The Spirit Level, Tony Hsieh, why are manhole covers round?, William Shockley: the traitorous eight

Another idea is to roll the die twice and total the numbers, or multiply them, or otherwise generate a large number. Then divide by 7, taking only the remainder. The remainder will be in the range of 0 to 6. We don’t need a 0, so pretend it’s a 7. That gives a “random” number in the range of 1 to 7. I put “random” in scare quotes because, as the mathematician John von Neumann wrote, “Any one who considers arithmetical methods of producing random digits is, of course, in a state of sin.” While this trick may be good enough for some purposes, the result isn’t truly random, and so this answer is not rated highly at Google or Amazon. On the web, random numbers had better be random.


pages: 267 words: 71,941

How to Predict the Unpredictable by William Poundstone

accounting loophole / creative accounting, Albert Einstein, Bernie Madoff, Brownian motion, business cycle, butter production in bangladesh, buy and hold, buy low sell high, call centre, centre right, Claude Shannon: information theory, computer age, crowdsourcing, Daniel Kahneman / Amos Tversky, Edward Thorp, Firefox, fixed income, forensic accounting, high net worth, index card, index fund, Jim Simons, John von Neumann, market bubble, money market fund, pattern recognition, Paul Samuelson, Ponzi scheme, power law, prediction markets, proprietary trading, random walk, Richard Thaler, risk-adjusted returns, Robert Shiller, Rubik’s Cube, statistical model, Steven Pinker, subprime mortgage crisis, transaction costs

To add to the mystique, Shannon alone was able to beat his outguessing machine. Shannon described his device in a March 18, 1953, Bell Laboratories memorandum with the title “A Mind-Reading (?) Machine.” There he noted that the matching game had a distinguished and somewhat literary history. It was “discussed from the game theoretic angle by [John] von Neumann and [Oskar] Morgenstern and from the psychological point of view by Edgar Allan Poe in ‘The Purloined Letter.’ Oddly enough, the machine is aimed more nearly at Poe’s method than von Neumann’s.” The hero of Poe’s psychological detective tale solves crimes on the premise that people are predictable when they try not to be.


pages: 256 words: 73,068

12 Bytes: How We Got Here. Where We Might Go Next by Jeanette Winterson

"Margaret Hamilton" Apollo, "World Economic Forum" Davos, 3D printing, Ada Lovelace, Airbnb, Albert Einstein, Alignment Problem, Amazon Mechanical Turk, Anthropocene, Apollo 11, Apple's 1984 Super Bowl advert, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, basic income, Big Tech, bitcoin, Bletchley Park, blockchain, Boston Dynamics, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, cashless society, Charles Babbage, computer age, Computing Machinery and Intelligence, coronavirus, COVID-19, CRISPR, cryptocurrency, dark matter, Dava Sobel, David Graeber, deep learning, deskilling, digital rights, discovery of DNA, Dominic Cummings, Donald Trump, double helix, driverless car, Elon Musk, fake news, flying shuttle, friendly AI, gender pay gap, global village, Grace Hopper, Gregor Mendel, hive mind, housing crisis, Internet of things, Isaac Newton, Jacquard loom, James Hargreaves, Jeff Bezos, Johannes Kepler, John von Neumann, Joseph-Marie Jacquard, Kickstarter, Large Hadron Collider, life extension, lockdown, lone genius, Mark Zuckerberg, means of production, microdosing, more computing power than Apollo, move fast and break things, natural language processing, Nick Bostrom, Norbert Wiener, off grid, OpenAI, operation paperclip, packet switching, Peter Thiel, pink-collar, Plato's cave, public intellectual, QAnon, QWERTY keyboard, Ray Kurzweil, rewilding, ride hailing / ride sharing, Rutger Bregman, Sam Altman, self-driving car, sharing economy, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, Skype, Snapchat, SoftBank, SpaceX Starlink, speech recognition, spinning jenny, stem cell, Stephen Hawking, Steve Bannon, Steve Jobs, Steven Levy, Steven Pinker, superintelligent machines, surveillance capitalism, synthetic biology, systems thinking, tech billionaire, tech worker, TED Talk, telepresence, telepresence robot, TikTok, trade route, Turing test, universal basic income, Virgin Galactic, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator

The German mathematician and philosopher Leibniz was the first champion of binary calculations, unless we go back to the Chinese and their classic book of wisdom and divination, the I Ching. Leibniz was an enthusiastic I Ching explorer. While decimal was the system initially used in computer programming and calculations, the Hungarian-American John von Neumann realised that Leibniz’s binary form was the best solution for stored-programme computing. Binary uses only two digits – zero and one. The ENIAC, launched at the University of Pennsylvania in 1946, and programmed by 6 women, used decimal. Using decimal digits, the number 128 needed 30 vacuum tubes (on/off switches that preceded transistors) to represent it.


pages: 250 words: 79,360

Escape From Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It by Erica Thompson

Alan Greenspan, Bayesian statistics, behavioural economics, Big Tech, Black Swan, butterfly effect, carbon tax, coronavirus, correlation does not imply causation, COVID-19, data is the new oil, data science, decarbonisation, DeepMind, Donald Trump, Drosophila, Emanuel Derman, Financial Modelers Manifesto, fudge factor, germ theory of disease, global pandemic, hindcast, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, implied volatility, Intergovernmental Panel on Climate Change (IPCC), John von Neumann, junk bonds, Kim Stanley Robinson, lockdown, Long Term Capital Management, moral hazard, mouse model, Myron Scholes, Nate Silver, Neal Stephenson, negative emissions, paperclip maximiser, precautionary principle, RAND corporation, random walk, risk tolerance, selection bias, self-driving car, social distancing, Stanford marshmallow experiment, statistical model, systematic bias, tacit knowledge, tail risk, TED Talk, The Great Moderation, The Great Resignation, the scientific method, too big to fail, trolley problem, value at risk, volatility smile, Y2K

More complicated models may have many thousands of parameters with much more complicated effects, but the process of fitting or calibrating the model to the observed data remains the same: change the parameters until you get a model output that is closest (in some way) to the observations. The more parameters a model has, in general, the more control we have over its behaviour and the more opportunity the model has to fit the data. Hungarian-American polymath John von Neumann is reputed to have said, ‘With four parameters I can fit an elephant. With five I can make him wiggle his trunk.’ The implication is that if we can fit anything, then the model has no explanatory power. If we can fit nothing, of course, it equally has no explanatory power. We gain confidence in a model by being able to fit the observations without going through great contortions to do so, because this shows that the variation in the observations is in some sense contained within the simple principles expressed by the model.


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The Signal and the Noise: Why So Many Predictions Fail-But Some Don't by Nate Silver

airport security, Alan Greenspan, Alvin Toffler, An Inconvenient Truth, availability heuristic, Bayesian statistics, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, big-box store, Black Monday: stock market crash in 1987, Black Swan, Boeing 747, book value, Broken windows theory, business cycle, buy and hold, Carmen Reinhart, Charles Babbage, classic study, Claude Shannon: information theory, Climategate, Climatic Research Unit, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, computer age, correlation does not imply causation, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, Daniel Kahneman / Amos Tversky, disinformation, diversification, Donald Trump, Edmond Halley, Edward Lorenz: Chaos theory, en.wikipedia.org, equity premium, Eugene Fama: efficient market hypothesis, everywhere but in the productivity statistics, fear of failure, Fellow of the Royal Society, Ford Model T, Freestyle chess, fudge factor, Future Shock, George Akerlof, global pandemic, Goodhart's law, haute cuisine, Henri Poincaré, high batting average, housing crisis, income per capita, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, invention of the printing press, invisible hand, Isaac Newton, James Watt: steam engine, Japanese asset price bubble, John Bogle, John Nash: game theory, John von Neumann, Kenneth Rogoff, knowledge economy, Laplace demon, locking in a profit, Loma Prieta earthquake, market bubble, Mikhail Gorbachev, Moneyball by Michael Lewis explains big data, Monroe Doctrine, mortgage debt, Nate Silver, negative equity, new economy, Norbert Wiener, Oklahoma City bombing, PageRank, pattern recognition, pets.com, Phillips curve, Pierre-Simon Laplace, Plato's cave, power law, prediction markets, Productivity paradox, proprietary trading, public intellectual, random walk, Richard Thaler, Robert Shiller, Robert Solow, Rodney Brooks, Ronald Reagan, Saturday Night Live, savings glut, security theater, short selling, SimCity, Skype, statistical model, Steven Pinker, The Great Moderation, The Market for Lemons, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, Timothy McVeigh, too big to fail, transaction costs, transfer pricing, University of East Anglia, Watson beat the top human players on Jeopardy!, Wayback Machine, wikimedia commons

But computers are very good at computing: at repeating the same arithmetic tasks over and over again and doing so quickly and accurately. Tasks like chess that abide by relatively simple rules, but which are difficult computationally, are right in their wheelhouse. So, potentially, was the weather. The first computer weather forecast was made in 1950 by the mathematician John von Neumann, who used a machine that could make about 5,000 calculations per second.17 That was a lot faster than Richardson could manage with a pencil and paper in a French hay field. Still, the forecast wasn’t any good, failing to do any better than a more-or-less random guess. Eventually, by the mid-1960s, computers would start to demonstrate some skill at weather forecasting.

It actually does a much worse job of explaining the real world.58 As obvious as this might seem when explained in this way, many forecasters completely ignore this problem. The wide array of statistical methods available to researchers enables them to be no less fanciful—and no more scientific—than a child finding animal patterns in clouds.* “With four parameters I can fit an elephant,” the mathematician John von Neumann once said of this problem.59 “And with five I can make him wiggle his trunk.” Overfitting represents a double whammy: it makes our model look better on paper but perform worse in the real world. Because of the latter trait, an overfit model eventually will get its comeuppance if and when it is used to make real predictions.


The Supermen: The Story of Seymour Cray and the Technical Wizards Behind the Supercomputer by Charles J. Murray

Albert Einstein, Berlin Wall, Charles Babbage, Fairchild Semiconductor, fear of failure, John von Neumann, lateral thinking, pattern recognition, Ralph Waldo Emerson, Salesforce, Silicon Valley

The release of energy was simply beyond the bounds of human imagination. Being anywhere near a nuclear blast was probably the closest thing on earth to hell itself. That knowledge had, in fact, been one of the driving forces behind the formation of the new lab. Legend held that on his deathbed, world-renowned mathematician John von Neumann had called for a greater push in the area of computational study of nuclear weapons. "Never let the lab be like the aircraft industry," he had said, "building, crash- ing, and then fixing." The concept of computing was not new to nuclear scientists. Those at Los Alamos National Laboratory-or more accurately, their wives-had used primitive calculating machinery to work through the mysteries of Fat Man and Little Boy.


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Erwin Schrodinger and the Quantum Revolution by John Gribbin

Albert Einstein, Albert Michelson, All science is either physics or stamp collecting, Arthur Eddington, British Empire, Brownian motion, double helix, Drosophila, Eddington experiment, Edmond Halley, Ernest Rutherford, Fellow of the Royal Society, Gregor Mendel, Henri Poincaré, Isaac Newton, Johannes Kepler, John von Neumann, Large Hadron Collider, lateral thinking, quantum cryptography, quantum entanglement, Richard Feynman, Schrödinger's Cat, The Present Situation in Quantum Mechanics, the scientific method, trade route, upwardly mobile

As the Oxford physicist David Deutsch (b. 1953) has put it, “a non-local hidden variable theory means, in ordinary language, a theory in which influences propagate across space and time without passing through the space in between: [in other words] they propagate instantaneously.”1 Apart from the momentum of the Copenhagen juggernaut, there was another reason why most physicists did not take hidden variables theory seriously in the 1950s. In 1932, John von Neumann (1903–57), a Hungarian-born mathematical genius, had published a book in which, among other things, he “proved” that hidden variables theories could not work. His contemporaries were so in awe of von Neumann’s ability that for a generation this proof was barely questioned, and it was widely cited as gospel, without being spelled out in full, in standard texts such as Max Born’s Natural Philosophy of Cause and Chance, published in 1949.


pages: 261 words: 86,261

The Pleasure of Finding Things Out: The Best Short Works of Richard P. Feynman by Richard P. Feynman, Jeffrey Robbins

Albert Einstein, Brownian motion, impulse control, index card, John von Neumann, Murray Gell-Mann, pattern recognition, Pepto Bismol, Richard Feynman, Richard Feynman: Challenger O-ring, scientific worldview, the scientific method

Ultimately, for fun again and intellectual pleasure, we could imagine machines as tiny as a few microns across, with wheels and cables all interconnected by wires, silicon connections, so that the thing as a whole, a very large device, moves not like the awkward motions of our present stiff machines but in the smooth way of the neck of a swan, which after all is a lot of little machines, the cells all interconnected and all controlled in a smooth way. Why can’t we do that ourselves? ______ *John von Neumann (1903–1957), a Hungarian-American mathematician who is credited as being one of the fathers of the computer. Ed. *The jerky movements of particles caused by the constant random collisions of molecules, first noted in print in 1928 by botanist Robert Brown, and explained by Albert Einstein in a 1905 paper in Annalen der Physik.


pages: 362 words: 83,464

The New Class Conflict by Joel Kotkin

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, affirmative action, Affordable Care Act / Obamacare, Alvin Toffler, American Society of Civil Engineers: Report Card, back-to-the-city movement, Bob Noyce, Boston Dynamics, California gold rush, Californian Ideology, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, classic study, Cornelius Vanderbilt, creative destruction, crony capitalism, David Graeber, degrowth, deindustrialization, do what you love, don't be evil, Downton Abbey, driverless car, Edward Glaeser, Elon Musk, energy security, falling living standards, future of work, Future Shock, Gini coefficient, Google bus, Herman Kahn, housing crisis, income inequality, independent contractor, informal economy, Internet of things, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kevin Roose, labor-force participation, Larry Ellison, Lewis Mumford, low interest rates, low-wage service sector, Marc Andreessen, Mark Zuckerberg, Mary Meeker, mass affluent, McJob, McMansion, medical bankruptcy, microapartment, Nate Silver, National Debt Clock, New Economic Geography, new economy, New Urbanism, obamacare, offshore financial centre, Paul Buchheit, payday loans, Peter Calthorpe, plutocrats, post-industrial society, public intellectual, RAND corporation, Ray Kurzweil, rent control, rent-seeking, Report Card for America’s Infrastructure, Richard Florida, Sheryl Sandberg, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Solyndra, Steve Jobs, stock buybacks, tech worker, techlash, technoutopianism, The Death and Life of Great American Cities, Thomas L Friedman, Tony Fadell, too big to fail, transcontinental railway, trickle-down economics, Tyler Cowen, Tyler Cowen: Great Stagnation, upwardly mobile, urban planning, urban sprawl, Virgin Galactic, War on Poverty, women in the workforce, working poor, young professional

Clerical Dreams: A High-Tech Nirvana For at least a century or more, some scientists have dreamed of a society that was driven by the imperatives of technology, as opposed to the often messy, frequently irrational dynamics of mass democracy. This notion was noted in 1950 by the early computer designer John von Neumann, who saw that “the ever accelerating progress of technology . . . gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.”83 In this new formulation, technology essentially supplants divinity, community, and family as the driving force in history.


pages: 272 words: 83,798

A Little History of Economics by Niall Kishtainy

Alvin Roth, behavioural economics, British Empire, Capital in the Twenty-First Century by Thomas Piketty, car-free, carbon tax, central bank independence, clean water, Corn Laws, Cornelius Vanderbilt, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, Dr. Strangelove, Eugene Fama: efficient market hypothesis, first-price auction, floating exchange rates, follow your passion, full employment, George Akerlof, Great Leap Forward, greed is good, Hyman Minsky, inflation targeting, invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, loss aversion, low interest rates, market clearing, market design, means of production, Minsky moment, moral hazard, Nash equilibrium, new economy, Occupy movement, Pareto efficiency, Paul Samuelson, Phillips curve, prisoner's dilemma, RAND corporation, rent-seeking, Richard Thaler, rising living standards, road to serfdom, Robert Shiller, Robert Solow, Ronald Reagan, sealed-bid auction, second-price auction, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, trade route, Vickrey auction, Vilfredo Pareto, washing machines reduced drudgery, wealth creators, Winter of Discontent

Many game theorists worked for the RAND (‘research and development’) Corporation, a military research organisation. In the film, Dr Strangelove is the American president’s director of weapons research, an eccentric genius with dark glasses and a funny accent who advises on military tactics. He’s said to have been inspired by a real genius, the Hungarian-born mathematician John von Neumann (1903–57), one of the founders of game theory who worked for RAND and became President Eisenhower’s adviser on defence strategy. Von Neumann was so clever that at the age of eight he could divide eight-digit numbers in his head. As an adult he wrote scientific papers on shockwaves, aerodynamics and the distribution of stars.


pages: 313 words: 84,312

We-Think: Mass Innovation, Not Mass Production by Charles Leadbeater

1960s counterculture, Andrew Keen, barriers to entry, bioinformatics, c2.com, call centre, citizen journalism, clean water, cloud computing, complexity theory, congestion charging, death of newspapers, Debian, digital divide, digital Maoism, disruptive innovation, double helix, Douglas Engelbart, Edward Lloyd's coffeehouse, folksonomy, frictionless, frictionless market, future of work, game design, Garrett Hardin, Google Earth, Google X / Alphabet X, Hacker Ethic, Herbert Marcuse, Hernando de Soto, hive mind, Howard Rheingold, interchangeable parts, Isaac Newton, James Watt: steam engine, Jane Jacobs, Jaron Lanier, Jean Tirole, jimmy wales, Johannes Kepler, John Markoff, John von Neumann, Joi Ito, Kevin Kelly, knowledge economy, knowledge worker, lateral thinking, lone genius, M-Pesa, Mark Shuttleworth, Mark Zuckerberg, Marshall McLuhan, Menlo Park, microcredit, Mitch Kapor, new economy, Nicholas Carr, online collectivism, Paradox of Choice, planetary scale, post scarcity, public intellectual, Recombinant DNA, Richard Stallman, Shoshana Zuboff, Silicon Valley, slashdot, social web, software patent, Steven Levy, Stewart Brand, supply-chain management, synthetic biology, the Cathedral and the Bazaar, The Death and Life of Great American Cities, the long tail, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Tragedy of the Commons, Whole Earth Catalog, work culture , Yochai Benkler, Zipcar

Just as the fax machine, printer and photocopier have spread the world over, so could low-cost manufacturing of machines that make reliable products, customised to local needs. One such machine could be based on Bath University’s RepRap, which looks like a large photocopier and can make three-dimensional objects from designs stored inside its computer. In the 1950s the mathematician John von Neumann imagined a universal constructor: a computer linked to a manufacturing robot that could make virtually any physical object, including replicating itself. The closest the world got to such a machine was the replicator in Star Wars, which could make any object out of thin air; the RepRap might make that a reality.


pages: 245 words: 83,272

Artificial Unintelligence: How Computers Misunderstand the World by Meredith Broussard

"Susan Fowler" uber, 1960s counterculture, A Declaration of the Independence of Cyberspace, Ada Lovelace, AI winter, Airbnb, algorithmic bias, AlphaGo, Amazon Web Services, autonomous vehicles, availability heuristic, barriers to entry, Bernie Sanders, Big Tech, bitcoin, Buckminster Fuller, Charles Babbage, Chris Urmson, Clayton Christensen, cloud computing, cognitive bias, complexity theory, computer vision, Computing Machinery and Intelligence, crowdsourcing, Danny Hillis, DARPA: Urban Challenge, data science, deep learning, Dennis Ritchie, digital map, disruptive innovation, Donald Trump, Douglas Engelbart, driverless car, easy for humans, difficult for computers, Electric Kool-Aid Acid Test, Elon Musk, fake news, Firefox, gamification, gig economy, global supply chain, Google Glasses, Google X / Alphabet X, Greyball, Hacker Ethic, independent contractor, Jaron Lanier, Jeff Bezos, Jeremy Corbyn, John Perry Barlow, John von Neumann, Joi Ito, Joseph-Marie Jacquard, life extension, Lyft, machine translation, Mark Zuckerberg, mass incarceration, Minecraft, minimum viable product, Mother of all demos, move fast and break things, Nate Silver, natural language processing, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, One Laptop per Child (OLPC), opioid epidemic / opioid crisis, PageRank, Paradox of Choice, payday loans, paypal mafia, performance metric, Peter Thiel, price discrimination, Ray Kurzweil, ride hailing / ride sharing, Ross Ulbricht, Saturday Night Live, school choice, self-driving car, Silicon Valley, Silicon Valley billionaire, speech recognition, statistical model, Steve Jobs, Steven Levy, Stewart Brand, TechCrunch disrupt, Tesla Model S, the High Line, The Signal and the Noise by Nate Silver, theory of mind, traumatic brain injury, Travis Kalanick, trolley problem, Turing test, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, We are as Gods, Whole Earth Catalog, women in the workforce, work culture , yottabyte

Together, they created HAL 9000, a computer that even today embodies all of the promise and terror of what machines might do. Most people remember HAL’s single, glowing red “eye.” That ominous eye is almost identical to an eyeball (actually, a display unit) on ENIAC, which is considered the world’s first programmable, general-purpose digital computer. John von Neumann, who came up with one of the core concepts of computer storage that led to ENIAC, was one of Minsky’s mentors. Minsky’s literary taste ran almost exclusively to science fiction. He wrote his own, and he was also friends with Isaac Asimov and other prominent science fiction writers. Sometimes in the friendships, the lines between science fiction and reality became blurred.


The Ages of Globalization by Jeffrey D. Sachs

Admiral Zheng, AlphaGo, Big Tech, biodiversity loss, British Empire, Cape to Cairo, circular economy, classic study, colonial rule, Columbian Exchange, Commentariolus, coronavirus, cotton gin, COVID-19, cuban missile crisis, decarbonisation, DeepMind, demographic transition, Deng Xiaoping, domestication of the camel, Donald Trump, en.wikipedia.org, endogenous growth, European colonialism, general purpose technology, global supply chain, Great Leap Forward, greed is good, income per capita, invention of agriculture, invention of gunpowder, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, James Watt: steam engine, job automation, John von Neumann, joint-stock company, lockdown, Louis Pasteur, low skilled workers, mass immigration, Nikolai Kondratiev, ocean acidification, out of africa, packet switching, Pax Mongolica, precision agriculture, profit maximization, profit motive, purchasing power parity, rewilding, South China Sea, spinning jenny, Suez canal 1869, systems thinking, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Wealth of Nations by Adam Smith, trade route, transatlantic slave trade, Turing machine, Turing test, urban planning, warehouse robotics, Watson beat the top human players on Jeopardy!, wikimedia commons, zoonotic diseases

(For all his genius and his contributions, a towering figure in the entire history of mathematics, Turing was hounded by British authorities after World War II for his homosexuality, and possibly driven to suicide, as the cause of his death remains disputed.) The next step in the digital revolution came out of another remarkable mind, that of John von Neumann, who conceptualized in 1945 the basic architecture of the modern computer, with a processing unit, control unit, working memory, input and output devices, and external mass storage. Von Neumann’s computer architecture became the design of the first computers, devices using vacuum tubes to implement the computer’s logical circuitry.


pages: 371 words: 93,570

Broad Band: The Untold Story of the Women Who Made the Internet by Claire L. Evans

4chan, Ada Lovelace, air gap, Albert Einstein, Bletchley Park, British Empire, Charles Babbage, colonial rule, Colossal Cave Adventure, computer age, crowdsourcing, D. B. Cooper, dark matter, dematerialisation, Doomsday Book, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, East Village, Edward Charles Pickering, game design, glass ceiling, Grace Hopper, Gödel, Escher, Bach, Haight Ashbury, Harvard Computers: women astronomers, Honoré de Balzac, Howard Rheingold, HyperCard, hypertext link, index card, information retrieval, Internet Archive, Jacquard loom, John von Neumann, Joseph-Marie Jacquard, junk bonds, knowledge worker, Leonard Kleinrock, machine readable, Mahatma Gandhi, Mark Zuckerberg, Menlo Park, military-industrial complex, Mondo 2000, Mother of all demos, Network effects, old-boy network, On the Economy of Machinery and Manufactures, packet switching, PalmPilot, pets.com, rent control, RFC: Request For Comment, rolodex, San Francisco homelessness, semantic web, side hustle, Silicon Valley, Skype, South of Market, San Francisco, Steve Jobs, Steven Levy, Stewart Brand, subscription business, tech worker, technoutopianism, Ted Nelson, telepresence, The Soul of a New Machine, Wayback Machine, Whole Earth Catalog, Whole Earth Review, women in the workforce, Works Progress Administration, Y2K

During the war, the Computation Laboratory was isolated from the handful of other computing projects in the world, and Grace Hopper, handling the lab’s everyday computational needs, had neither the time nor the opportunity to see what the rest of the field was doing. But sometimes the field came to her. Grace had been working in the Computation Laboratory for only a few months, for instance, when the physicist John von Neumann came to visit. Von Neumann had mobility; he spent much of 1944 visiting different computing projects in the United States, looking for a machine brawny enough to crack a complex partial differential equation. The Mark I was the first large-scale computer on his tour, and for three months that summer he decamped in a conference room at Harvard, outlining his problem on a blackboard while Richard Bloch set it up on the computer.


pages: 322 words: 88,197

Wonderland: How Play Made the Modern World by Steven Johnson

"hyperreality Baudrillard"~20 OR "Baudrillard hyperreality", Ada Lovelace, adjacent possible, Alfred Russel Wallace, Antoine Gombaud: Chevalier de Méré, Berlin Wall, bitcoin, Book of Ingenious Devices, Buckminster Fuller, Charles Babbage, Claude Shannon: information theory, Clayton Christensen, colonial exploitation, computer age, Computing Machinery and Intelligence, conceptual framework, cotton gin, crowdsourcing, cuban missile crisis, Drosophila, Edward Thorp, Fellow of the Royal Society, flying shuttle, game design, global village, Great Leap Forward, Hedy Lamarr / George Antheil, HyperCard, invention of air conditioning, invention of the printing press, invention of the telegraph, Islamic Golden Age, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, Jane Jacobs, John von Neumann, joint-stock company, Joseph-Marie Jacquard, land value tax, Landlord’s Game, Lewis Mumford, lone genius, mass immigration, megacity, Minecraft, moral panic, Murano, Venice glass, music of the spheres, Necker cube, New Urbanism, Oculus Rift, On the Economy of Machinery and Manufactures, pattern recognition, peer-to-peer, pets.com, placebo effect, pneumatic tube, probability theory / Blaise Pascal / Pierre de Fermat, profit motive, QWERTY keyboard, Ray Oldenburg, SimCity, spice trade, spinning jenny, statistical model, Steve Jobs, Steven Pinker, Stewart Brand, supply-chain management, talking drums, the built environment, The Great Good Place, the scientific method, The Structural Transformation of the Public Sphere, trade route, Turing machine, Turing test, Upton Sinclair, urban planning, vertical integration, Victor Gruen, Watson beat the top human players on Jeopardy!, white flight, white picket fence, Whole Earth Catalog, working poor, Wunderkammern

Turing’s speculations form a kind of origin point for two parallel paths that would run through the rest of the century: building intelligence into computers by teaching them to play chess, and studying humans playing chess as a way of understanding our own intelligence. Those interpretative paths would lead to some extraordinary breakthroughs: from the early work on cybernetics and game theory from people like Claude Shannon and John von Neumann, to machines like IBM’s Deep Blue that could defeat grandmasters with ease. In cognitive science, the litany of insights that derived from the study of chess could almost fill an entire textbook, insights that have helped us understand the human capacity for problem solving, pattern recognition, visual memory, and the crucial skill that scientists call, somewhat awkwardly, chunking, which involves grouping a collection of ideas or facts into a single “chunk” so that they can be processed and remembered as a unit.


pages: 294 words: 96,661

The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity by Byron Reese

"World Economic Forum" Davos, agricultural Revolution, AI winter, Apollo 11, artificial general intelligence, basic income, bread and circuses, Buckminster Fuller, business cycle, business process, Charles Babbage, Claude Shannon: information theory, clean water, cognitive bias, computer age, CRISPR, crowdsourcing, dark matter, DeepMind, Edward Jenner, Elon Musk, Eratosthenes, estate planning, financial independence, first square of the chessboard, first square of the chessboard / second half of the chessboard, flying shuttle, full employment, Hans Moravec, Hans Rosling, income inequality, invention of agriculture, invention of movable type, invention of the printing press, invention of writing, Isaac Newton, Islamic Golden Age, James Hargreaves, job automation, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, lateral thinking, life extension, Louis Pasteur, low interest rates, low skilled workers, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Mary Lou Jepsen, Moravec's paradox, Nick Bostrom, On the Revolutions of the Heavenly Spheres, OpenAI, pattern recognition, profit motive, quantum entanglement, radical life extension, Ray Kurzweil, recommendation engine, Rodney Brooks, Sam Altman, self-driving car, seminal paper, Silicon Valley, Skype, spinning jenny, Stephen Hawking, Steve Wozniak, Steven Pinker, strong AI, technological singularity, TED Talk, telepresence, telepresence robot, The Future of Employment, the scientific method, Timothy McVeigh, Turing machine, Turing test, universal basic income, Von Neumann architecture, Wall-E, warehouse robotics, Watson beat the top human players on Jeopardy!, women in the workforce, working poor, Works Progress Administration, Y Combinator

Everything your smartphone can do can be programmed on a Turing machine, and everything IBM Watson can do can be programmed on a Turing machine. Who could have guessed that such a humble little device could do all that? Well, Turing could, of course. But no one else seems to have had that singular idea. Exit Turing. Enter John von Neumann, whom we call the father of modern computing. In 1945, he developed the von Neumann architecture for computers. While Turing machines are purely theoretical, designed to frame the question of what computers can do, the von Neumann architecture is about how to build actual computers. He suggested an internal processor and computer memory that holds both programs and data.


pages: 321 words: 89,109

The New Gold Rush: The Riches of Space Beckon! by Joseph N. Pelton

"World Economic Forum" Davos, 3D printing, Any sufficiently advanced technology is indistinguishable from magic, Biosphere 2, Buckminster Fuller, business logic, Carrington event, Colonization of Mars, Dennis Tito, disruptive innovation, Donald Trump, driverless car, Elon Musk, en.wikipedia.org, full employment, global pandemic, Google Earth, GPS: selective availability, gravity well, Iridium satellite, Jeff Bezos, job automation, Johannes Kepler, John von Neumann, life extension, low earth orbit, Lyft, Mark Shuttleworth, Mark Zuckerberg, megacity, megastructure, new economy, Peter H. Diamandis: Planetary Resources, Planet Labs, post-industrial society, private spaceflight, Ray Kurzweil, Scaled Composites, Silicon Valley, Silicon Valley billionaire, skunkworks, space junk, SpaceShipOne, Stephen Hawking, Steve Jobs, Strategic Defense Initiative, Thomas Malthus, Tim Cook: Apple, Tunguska event, uber lyft, urban planning, urban sprawl, vertical integration, Virgin Galactic, wikimedia commons, X Prize

Yet as just noted these service jobs are increasingly being automated or turned over to devices or robots that are artificially intelligent. Ray Kurzweil, the artificial intelligence guru that invented “Siri,” who so sweetly and competently responds to inquiries on smart phones, believes that the “singularity” is coming within the next few years. The term “singularity” was first used by John von Neumann in 1958. It was then amplified by Vernon Verre of Hungary and even more recently given a more focused meaning by Kurzweil, especially in his book The Singularity Is Near , published in 2005. Kurzweil predicted high speed processors, memory storage and artificially intelligent algorithms that would not only duplicate human reasoning, memory and processing capabilities but would be commercially available at $1000 per unit by 2029.


pages: 313 words: 91,098

The Knowledge Illusion by Steven Sloman

Affordable Care Act / Obamacare, Air France Flight 447, attribution theory, bitcoin, Black Swan, Cass Sunstein, combinatorial explosion, computer age, Computing Machinery and Intelligence, CRISPR, crowdsourcing, Dmitri Mendeleev, driverless car, Dunning–Kruger effect, Elon Musk, Ethereum, Flynn Effect, Great Leap Forward, Gregor Mendel, Hernando de Soto, Higgs boson, hindsight bias, hive mind, indoor plumbing, Isaac Newton, John von Neumann, libertarian paternalism, Mahatma Gandhi, Mark Zuckerberg, meta-analysis, Nick Bostrom, obamacare, Peoples Temple, prediction markets, randomized controlled trial, Ray Kurzweil, Richard Feynman, Richard Thaler, Rodney Brooks, Rosa Parks, seminal paper, single-payer health, speech recognition, stem cell, Stephen Hawking, Steve Jobs, technological singularity, The Coming Technological Singularity, The Wisdom of Crowds, Vernor Vinge, web application, Whole Earth Review, Y Combinator

Landauer was a pioneer of cognitive science, holding academic appointments at Harvard, Dartmouth, Stanford, and Princeton and also spending twenty-five years trying to apply his insights at Bell Labs. He started his career in the 1960s, a time when cognitive scientists took seriously the idea that the mind is a kind of computer. Cognitive science emerged as a field in sync with the modern computer. As great mathematical minds like John von Neumann and Alan Turing developed the foundations of computing as we know it, the question arose whether the human mind works in the same way. Computers have an operating system that is run by a central processor that reads and writes to a digital memory using a small set of rules. Early cognitive scientists ran with the idea that the mind does too.


Concentrated Investing by Allen C. Benello

activist fund / activist shareholder / activist investor, asset allocation, barriers to entry, beat the dealer, Benoit Mandelbrot, Bob Noyce, Boeing 747, book value, business cycle, buy and hold, carried interest, Claude Shannon: information theory, corporate governance, corporate raider, delta neutral, discounted cash flows, diversification, diversified portfolio, Dutch auction, Edward Thorp, family office, fixed income, Henry Singleton, high net worth, index fund, John Bogle, John von Neumann, junk bonds, Louis Bachelier, margin call, merger arbitrage, Paul Samuelson, performance metric, prudent man rule, random walk, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, shareholder value, Sharpe ratio, short selling, survivorship bias, technology bubble, Teledyne, transaction costs, zero-sum game

In one of his earlier flights of fancy, Shannon had begun an intensive study of the stock market in the late 1950s.6 He wanted to know if his information theory could help him decode the market’s random walk. His research led him to fill three library shelves with books, including Adam Smith’s Wealth of Nations, John von Neumann and Oskar Morgenstern’s Theory of Games and Economic Behavior, Paul Samuelson’s Economics, and Fred Schwed’s Where Are the Customer’s Yachts? In a notebook Shannon recorded a varied list of thinkers, including French mathematician Louis Bachelier, Benjamin 74 Concentrated Investing Graham, and Benoit Mandelbrot.


The Internet Trap: How the Digital Economy Builds Monopolies and Undermines Democracy by Matthew Hindman

A Declaration of the Independence of Cyberspace, accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, AltaVista, Amazon Web Services, barriers to entry, Benjamin Mako Hill, bounce rate, business logic, Cambridge Analytica, cloud computing, computer vision, creative destruction, crowdsourcing, David Ricardo: comparative advantage, death of newspapers, deep learning, DeepMind, digital divide, discovery of DNA, disinformation, Donald Trump, fake news, fault tolerance, Filter Bubble, Firefox, future of journalism, Ida Tarbell, incognito mode, informal economy, information retrieval, invention of the telescope, Jeff Bezos, John Perry Barlow, John von Neumann, Joseph Schumpeter, lake wobegon effect, large denomination, longitudinal study, loose coupling, machine translation, Marc Andreessen, Mark Zuckerberg, Metcalfe’s law, natural language processing, Netflix Prize, Network effects, New Economic Geography, New Journalism, pattern recognition, peer-to-peer, Pepsi Challenge, performance metric, power law, price discrimination, recommendation engine, Robert Metcalfe, search costs, selection bias, Silicon Valley, Skype, sparse data, speech recognition, Stewart Brand, surveillance capitalism, technoutopianism, Ted Nelson, The Chicago School, the long tail, The Soul of a New Machine, Thomas Malthus, web application, Whole Earth Catalog, Yochai Benkler

In general, though, there are good reasons to prefer the power law label, even when other distributions may fit the data slightly better. Of course other related distributions often fit better: they have two or more parameters, while pure power laws have only one. Parsimony is a cardinal virtue in model building, and each additional parameter provides latitude for mischief. As John von Neumann reportedly said, “With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.”1 In any case, our data show a good fit to a pure power law, the discussion in the previous paragraphs notwithstanding. A simple way to check the regularity of the traffic distribution is to estimate the exponent of the power law for each day in our data.


pages: 360 words: 100,991

Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence by Richard Yonck

3D printing, AI winter, AlphaGo, Apollo 11, artificial general intelligence, Asperger Syndrome, augmented reality, autism spectrum disorder, backpropagation, Berlin Wall, Bletchley Park, brain emulation, Buckminster Fuller, call centre, cognitive bias, cognitive dissonance, computer age, computer vision, Computing Machinery and Intelligence, crowdsourcing, deep learning, DeepMind, Dunning–Kruger effect, Elon Musk, en.wikipedia.org, epigenetics, Fairchild Semiconductor, friendly AI, Geoffrey Hinton, ghettoisation, industrial robot, Internet of things, invention of writing, Jacques de Vaucanson, job automation, John von Neumann, Kevin Kelly, Law of Accelerating Returns, Loebner Prize, Menlo Park, meta-analysis, Metcalfe’s law, mirror neurons, Neil Armstrong, neurotypical, Nick Bostrom, Oculus Rift, old age dependency ratio, pattern recognition, planned obsolescence, pneumatic tube, RAND corporation, Ray Kurzweil, Rodney Brooks, self-driving car, Skype, social intelligence, SoftBank, software as a service, SQL injection, Stephen Hawking, Steven Pinker, superintelligent machines, technological singularity, TED Talk, telepresence, telepresence robot, The future is already here, The Future of Employment, the scientific method, theory of mind, Turing test, twin studies, Two Sigma, undersea cable, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Review, working-age population, zero day

The increased trend toward integration with computer technology will likely alter this to some degree. 7. The damsel in distress is also a feature of sadomasochistic fetishes, an aspect the AIs may have been manipulating in Nathan from before the beginning of this story. 8. The term “singularity” was originally used in this sense by Stanislaw Ulam in his obituary of computing giant John von Neumann. Chapter 17 1. The first two terms refer to the apocalyptic dystopia of the Terminator franchise, created by James Cameron and Gale Anne Hurd. The technological singularity is a hypothetical moment in our future when a machine intelligence rapidly self-improves, surpassing all human intelligence and severely disrupts all of society.


Language and Mind by Noam Chomsky

Alfred Russel Wallace, classic study, finite state, Great Leap Forward, John von Neumann, language acquisition, lateral thinking, machine translation, pattern recognition, phenotype, tacit knowledge, theory of mind

For those who sought a more mathematical formulation of the basic processes, there was the newly developed mathematical theory of communication, which, it was widely believed in the early 1950s, had provided a fundamental concept – the concept of “information” – that would unify the social and behavioral sciences and permit the development of a solid and satisfactory mathematical theory of human behavior on a probabilistic base. At about the same time, the theory of automata developed as an independent study, making use of closely related mathematical notions. And it was linked at once, and quite properly, to earlier explorations of the theory of neural nets. There were those – John von Neumann, for example – who felt that the entire development was dubious and shaky at best, and probably quite misconceived, but such qualms did not go far to dispel the feeling that mathematics, technology, and behavioristic linguistics and psychology were converging on a point of view that was very simple, very clear, and fully adequate to provide a basic understanding of what tradition had left shrouded in mystery.


Powers and Prospects by Noam Chomsky

anti-communist, Berlin Wall, Bretton Woods, colonial rule, declining real wages, deindustrialization, deskilling, Fall of the Berlin Wall, invisible hand, Jacques de Vaucanson, John von Neumann, language acquisition, liberation theology, Monroe Doctrine, Nixon triggered the end of the Bretton Woods system, old-boy network, RAND corporation, Ronald Reagan, South China Sea, theory of mind, Tobin tax, Turing test

The distinguished biologist François Jacob observes that ‘for the biologist, the living begins only with what was able to constitute a genetic program’, while ‘for the chemist, in contrast, it is somewhat arbitrary to make a demarcation where there can only be continuity’. Others might want to add crystals to the mix, or self-replicating automata of the kind pioneered by John von Neumann. There is no ‘right answer’, no reason to seek sharper boundaries to distinguish among physical, biological, chemical, and other aspects of the world. No discipline has any prior claim to particular objects in the world, whether they are complex molecules, stars, or human language. I should make it clear that these remarks are not uncontentious.


pages: 350 words: 103,988

Reinventing the Bazaar: A Natural History of Markets by John McMillan

accounting loophole / creative accounting, Albert Einstein, Alvin Roth, Andrei Shleifer, Anton Chekhov, Asian financial crisis, classic study, congestion charging, corporate governance, corporate raider, crony capitalism, Dava Sobel, decentralized internet, Deng Xiaoping, Dutch auction, electricity market, experimental economics, experimental subject, fear of failure, first-price auction, frictionless, frictionless market, George Akerlof, George Gilder, global village, Great Leap Forward, Hacker News, Hernando de Soto, I think there is a world market for maybe five computers, income inequality, income per capita, independent contractor, informal economy, information asymmetry, invisible hand, Isaac Newton, job-hopping, John Harrison: Longitude, John Perry Barlow, John von Neumann, Kenneth Arrow, land reform, lone genius, manufacturing employment, market clearing, market design, market friction, market microstructure, means of production, Network effects, new economy, offshore financial centre, ought to be enough for anybody, pez dispenser, pre–internet, price mechanism, profit maximization, profit motive, proxy bid, purchasing power parity, Robert Solow, Ronald Coase, Ronald Reagan, sealed-bid auction, search costs, second-price auction, Silicon Valley, spectrum auction, Stewart Brand, The Market for Lemons, The Nature of the Firm, The Wealth of Nations by Adam Smith, trade liberalization, transaction costs, War on Poverty, world market for maybe five computers, Xiaogang Anhui farmers, yield management

What is sometimes called the wisdom of the market results from the dispersion of decision-making. Markets make fewer big mistakes than planners. This is not because businesspeople are necessarily smarter than bureaucrats. The folklore of the computer industry, for example, relates a host of wrong predictions from those best placed to know. In 1954, John von Neumann, the mathematical genius who helped invent the computer, said, “I think there is a world market for maybe five computers.” In 1977, Ken Olson, president of Digital Equipment Corp., said, “There is no reason anyone would want a computer in their home.” In 1981, Bill Gates, founder of Microsoft, is reported to have said, “640K ought to be enough for anybody.”


pages: 309 words: 101,190

Climbing Mount Improbable by Richard Dawkins, Lalla Ward

Boeing 747, Buckminster Fuller, computer age, Drosophila, Fellow of the Royal Society, industrial robot, invention of radio, John von Neumann, Menlo Park, phenotype, Robert X Cringely, stem cell, the long tail, trade route

Make a new robot, then feed the same TRIP program into its on-board computer and turn it loose on the world to do the same thing.’ The hypothetical robot that we have now worked towards can be called a TRIP robot. A TRIP robot such as we are now imagining is a machine of great technical ingenuity and complexity. The principle was discussed by the celebrated Hungarian-American mathematician John von Neumann (one of two candidates for the honoured title of the father of the modern computer—the other was Alan Turing, the young British mathematician who, through his codebreaking genius, may have done more than any other individual on the Allied side to win the Second World War, but who was driven to suicide after the war by judicial persecution, including enforced hormone injections, for his homosexuality).


pages: 313 words: 101,403

My Life as a Quant: Reflections on Physics and Finance by Emanuel Derman

Bear Stearns, Berlin Wall, bioinformatics, Black-Scholes formula, book value, Brownian motion, buy and hold, capital asset pricing model, Claude Shannon: information theory, Dennis Ritchie, Donald Knuth, Emanuel Derman, financial engineering, fixed income, Gödel, Escher, Bach, haute couture, hiring and firing, implied volatility, interest rate derivative, Jeff Bezos, John Meriwether, John von Neumann, Ken Thompson, law of one price, linked data, Long Term Capital Management, moral hazard, Murray Gell-Mann, Myron Scholes, PalmPilot, Paul Samuelson, pre–internet, proprietary trading, publish or perish, quantitative trading / quantitative finance, Sharpe ratio, statistical arbitrage, statistical model, Stephen Hawking, Steve Jobs, stochastic volatility, technology bubble, the new new thing, transaction costs, volatility smile, Y2K, yield curve, zero-coupon bond, zero-sum game

It looked very unprofessorally businesslike, an early precursor of soon-to-arrive European Filofaxes and, a decade later, American Palm Pilots. David clearly thought big. In those days he was planning what he called "NonVon," a parallel-processing computer comprised of many small processors and memory units. It was to be the antithesis of the standard computer with one large central processor, a design that had prevailed since John von Neumann and the ENIAC computer of the 1940s. David's confidence inspired fear and envy. John Kender complained half-jokingly to me that while he and the other assistant professors in the tenure race at Columbia were trying to get modest government grants to do their work, David was always talking about ambitious proposals on a much larger scale, with plans for NonVon eventually to require a staff of tens to hundreds.


pages: 268 words: 109,447

The Cultural Logic of Computation by David Golumbia

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, American ideology, Benoit Mandelbrot, Bletchley Park, borderless world, business process, cellular automata, citizen journalism, Claude Shannon: information theory, computer age, Computing Machinery and Intelligence, corporate governance, creative destruction, digital capitalism, digital divide, en.wikipedia.org, finite state, folksonomy, future of work, Google Earth, Howard Zinn, IBM and the Holocaust, iterative process, Jaron Lanier, jimmy wales, John von Neumann, Joseph Schumpeter, late capitalism, Lewis Mumford, machine readable, machine translation, means of production, natural language processing, Norbert Wiener, One Laptop per Child (OLPC), packet switching, RAND corporation, Ray Kurzweil, RFID, Richard Stallman, semantic web, Shoshana Zuboff, Slavoj Žižek, social web, stem cell, Stephen Hawking, Steve Ballmer, Stewart Brand, strong AI, supply-chain management, supply-chain management software, technological determinism, Ted Nelson, telemarketer, The Wisdom of Crowds, theory of mind, Turing machine, Turing test, Vannevar Bush, web application, Yochai Benkler

As Amadae puts it, “the mathematical formalism structuring rational choice theory is impelled by the same academy-wide momentum propelling an increased emphasis on formal models as an indication of scientific standing” (158), also pointing to the influence of one of the founders of modern computing, John von Neumann, on rational choice doctrine (via his writings on game theory, von Neumann and Morgenstern 1944). Because cognition itself is formal, syntactic, and thereby instrumental, we are extending the human cognitive apparatus by building out our scientific and technological instruments; because this is the only sort of knowledge worth the name, and knowledge solves social problems, we need only build out our technology sufficiently to address any problems that emerge.


pages: 299 words: 19,560

Utopias: A Brief History From Ancient Writings to Virtual Communities by Howard P. Segal

1960s counterculture, Alvin Toffler, Apollo 11, biodiversity loss, British Empire, Buckminster Fuller, complexity theory, David Brooks, death of newspapers, dematerialisation, deskilling, energy security, European colonialism, Evgeny Morozov, Ford Model T, Francis Fukuyama: the end of history, full employment, future of journalism, Future Shock, G4S, garden city movement, germ theory of disease, Golden Gate Park, Herbert Marcuse, Herman Kahn, intentional community, invention of the printing press, Isaac Newton, Jeff Bezos, John Markoff, John von Neumann, Kim Stanley Robinson, knowledge economy, Lewis Mumford, liberation theology, Louis Pasteur, Mark Zuckerberg, mass immigration, means of production, megaproject, Nelson Mandela, Nicholas Carr, Nikolai Kondratiev, One Laptop per Child (OLPC), out of africa, pneumatic tube, post-war consensus, public intellectual, Ralph Waldo Emerson, Ray Kurzweil, Ronald Reagan, Silicon Valley, Skype, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Stewart Brand, Strategic Defense Initiative, technological determinism, technoutopianism, Thomas Malthus, Thorstein Veblen, transcontinental railway, traveling salesman, union organizing, urban planning, W. E. B. Du Bois, War on Poverty, warehouse robotics, Whole Earth Catalog

So, too, do the failures of other experts in such realms as environmental protection and nuclear power to achieve promised goals safely and efficiently.57 For that matter, predictions of an ever growing population in the developing world are now recognized as outdated, in favor of a far more complex picture.58 These dismal records have in turn led to a declining faith in forecasting as a serious intellectual and moral enterprise—just as, paradoxically, forecasting has become a highly profitable industry. A revealing footnote here is the failure of the otherwise brilliant scientists and engineers who invented computers during and after World War II to anticipate the evolution of the computers of their day. Interviews, memoirs, and other accounts from pioneers such as John Mauchly and John Von Neumann reveal no expectations of significant changes from the handful of room-sized behemoths—operated by skilled programmers and dependent on vacuum tubes that constantly needed to be replaced— that were to be used only by the largest national and international institutions to solve the most complex quantitative problems.


pages: 417 words: 97,577

The Myth of Capitalism: Monopolies and the Death of Competition by Jonathan Tepper

"Friedman doctrine" OR "shareholder theory", Affordable Care Act / Obamacare, air freight, Airbnb, airline deregulation, Alan Greenspan, bank run, barriers to entry, Berlin Wall, Bernie Sanders, Big Tech, big-box store, Bob Noyce, Boston Dynamics, business cycle, Capital in the Twenty-First Century by Thomas Piketty, citizen journalism, Clayton Christensen, collapse of Lehman Brothers, collective bargaining, compensation consultant, computer age, Cornelius Vanderbilt, corporate raider, creative destruction, Credit Default Swap, crony capitalism, diversification, don't be evil, Donald Trump, Double Irish / Dutch Sandwich, Dunbar number, Edward Snowden, Elon Musk, en.wikipedia.org, eurozone crisis, Fairchild Semiconductor, Fall of the Berlin Wall, family office, financial innovation, full employment, gentrification, German hyperinflation, gig economy, Gini coefficient, Goldman Sachs: Vampire Squid, Google bus, Google Chrome, Gordon Gekko, Herbert Marcuse, income inequality, independent contractor, index fund, Innovator's Dilemma, intangible asset, invisible hand, Jeff Bezos, Jeremy Corbyn, Jevons paradox, John Nash: game theory, John von Neumann, Joseph Schumpeter, junk bonds, Kenneth Rogoff, late capitalism, London Interbank Offered Rate, low skilled workers, Mark Zuckerberg, Martin Wolf, Maslow's hierarchy, means of production, merger arbitrage, Metcalfe's law, multi-sided market, mutually assured destruction, Nash equilibrium, Network effects, new economy, Northern Rock, offshore financial centre, opioid epidemic / opioid crisis, passive investing, patent troll, Peter Thiel, plutocrats, prediction markets, prisoner's dilemma, proprietary trading, race to the bottom, rent-seeking, road to serfdom, Robert Bork, Ronald Reagan, Sam Peltzman, secular stagnation, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley billionaire, Skype, Snapchat, Social Responsibility of Business Is to Increase Its Profits, SoftBank, Steve Jobs, stock buybacks, tech billionaire, The Chicago School, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, too big to fail, undersea cable, Vanguard fund, vertical integration, very high income, wikimedia commons, William Shockley: the traitorous eight, you are the product, zero-sum game

The optimal strategy is for the group to cooperate—no one talks to the blonde and they all talk to the less attractive friends. Nash's key idea was that among different players, they might all choose tacit cooperation rather than face competition. The solution to the problem of competition is called “Nash Equilibrium.” Nash didn't create game theory, but he developed it. His idea was a direct descendant of John von Neumann's Minimax theory. The idea is that players of a game won't seek to achieve the highest payout but will try to minimize their maximum loss. The easiest way to understand this is the example of a mother who allows her two children to divide a cake. The most equal division will happen if one cuts the cake and the other chooses the first piece.


pages: 350 words: 98,077

Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell

Ada Lovelace, AI winter, Alignment Problem, AlphaGo, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, artificial general intelligence, autonomous vehicles, backpropagation, Bernie Sanders, Big Tech, Boston Dynamics, Cambridge Analytica, Charles Babbage, Claude Shannon: information theory, cognitive dissonance, computer age, computer vision, Computing Machinery and Intelligence, dark matter, deep learning, DeepMind, Demis Hassabis, Douglas Hofstadter, driverless car, Elon Musk, en.wikipedia.org, folksonomy, Geoffrey Hinton, Gödel, Escher, Bach, I think there is a world market for maybe five computers, ImageNet competition, Jaron Lanier, job automation, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, license plate recognition, machine translation, Mark Zuckerberg, natural language processing, Nick Bostrom, Norbert Wiener, ought to be enough for anybody, paperclip maximiser, pattern recognition, performance metric, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rodney Brooks, self-driving car, sentiment analysis, Silicon Valley, Singularitarianism, Skype, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, tacit knowledge, tail risk, TED Talk, the long tail, theory of mind, There's no reason for any individual to have a computer in his home - Ken Olsen, trolley problem, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, world market for maybe five computers

In fact, the ideas that led to the first programmable computers came out of mathematicians’ attempts to understand human thought—particularly logic—as a mechanical process of “symbol manipulation.” Digital computers are essentially symbol manipulators, pushing around combinations of the symbols 0 and 1. To pioneers of computing like Alan Turing and John von Neumann, there were strong analogies between computers and the human brain, and it seemed obvious to them that human intelligence could be replicated in computer programs. Most people in artificial intelligence trace the field’s official founding to a small workshop in 1956 at Dartmouth College organized by a young mathematician named John McCarthy.


pages: 362 words: 97,288

Ghost Road: Beyond the Driverless Car by Anthony M. Townsend

A Pattern Language, active measures, AI winter, algorithmic trading, Alvin Toffler, Amazon Robotics, asset-backed security, augmented reality, autonomous vehicles, backpropagation, big-box store, bike sharing, Blitzscaling, Boston Dynamics, business process, Captain Sullenberger Hudson, car-free, carbon footprint, carbon tax, circular economy, company town, computer vision, conceptual framework, congestion charging, congestion pricing, connected car, creative destruction, crew resource management, crowdsourcing, DARPA: Urban Challenge, data is the new oil, Dean Kamen, deep learning, deepfake, deindustrialization, delayed gratification, deliberate practice, dematerialisation, deskilling, Didi Chuxing, drive until you qualify, driverless car, drop ship, Edward Glaeser, Elaine Herzberg, Elon Musk, en.wikipedia.org, extreme commuting, financial engineering, financial innovation, Flash crash, food desert, Ford Model T, fulfillment center, Future Shock, General Motors Futurama, gig economy, Google bus, Greyball, haute couture, helicopter parent, independent contractor, inventory management, invisible hand, Jane Jacobs, Jeff Bezos, Jevons paradox, jitney, job automation, John Markoff, John von Neumann, Joseph Schumpeter, Kickstarter, Kiva Systems, Lewis Mumford, loss aversion, Lyft, Masayoshi Son, megacity, microapartment, minimum viable product, mortgage debt, New Urbanism, Nick Bostrom, North Sea oil, Ocado, openstreetmap, pattern recognition, Peter Calthorpe, random walk, Ray Kurzweil, Ray Oldenburg, rent-seeking, ride hailing / ride sharing, Rodney Brooks, self-driving car, sharing economy, Shoshana Zuboff, Sidewalk Labs, Silicon Valley, Silicon Valley startup, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, SoftBank, software as a service, sovereign wealth fund, Stephen Hawking, Steve Jobs, surveillance capitalism, technological singularity, TED Talk, Tesla Model S, The Coming Technological Singularity, The Death and Life of Great American Cities, The future is already here, The Future of Employment, The Great Good Place, too big to fail, traffic fines, transit-oriented development, Travis Kalanick, Uber and Lyft, uber lyft, urban planning, urban sprawl, US Airways Flight 1549, Vernor Vinge, vertical integration, Vision Fund, warehouse automation, warehouse robotics

Such a device would be able to continually improve its own design, kicking off a chain reaction of accelerated learning. The Singularity, as Vinge dubbed such an event, would be “an exponential runaway beyond any hope of control,” a technological revolution “comparable to the rise of human life on Earth.” This wasn’t the first airing for this radical prediction. The mathematician John von Neumann had raised the possibility in the early 1950s. But Vinge’s message was timely, concise, and eminently meme-worthy. And while his assertion sounded like the plot for a dystopian novel, many geeks and gurus welcomed the possibility of machines with superhuman intelligence. In the age of the Human Genome Project and climate modeling, the great challenges facing humanity were better seen as informational problems, they argued.


pages: 289 words: 95,046

Chaos Kings: How Wall Street Traders Make Billions in the New Age of Crisis by Scott Patterson

"World Economic Forum" Davos, 2021 United States Capitol attack, 4chan, Alan Greenspan, Albert Einstein, asset allocation, backtesting, Bear Stearns, beat the dealer, behavioural economics, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, bitcoin, Bitcoin "FTX", Black Lives Matter, Black Monday: stock market crash in 1987, Black Swan, Black Swan Protection Protocol, Black-Scholes formula, blockchain, Bob Litterman, Boris Johnson, Brownian motion, butterfly effect, carbon footprint, carbon tax, Carl Icahn, centre right, clean tech, clean water, collapse of Lehman Brothers, Colonization of Mars, commodity super cycle, complexity theory, contact tracing, coronavirus, correlation does not imply causation, COVID-19, Credit Default Swap, cryptocurrency, Daniel Kahneman / Amos Tversky, decarbonisation, disinformation, diversification, Donald Trump, Doomsday Clock, Edward Lloyd's coffeehouse, effective altruism, Elliott wave, Elon Musk, energy transition, Eugene Fama: efficient market hypothesis, Extinction Rebellion, fear index, financial engineering, fixed income, Flash crash, Gail Bradbrook, George Floyd, global pandemic, global supply chain, Gordon Gekko, Greenspan put, Greta Thunberg, hindsight bias, index fund, interest rate derivative, Intergovernmental Panel on Climate Change (IPCC), Jeff Bezos, Jeffrey Epstein, Joan Didion, John von Neumann, junk bonds, Just-in-time delivery, lockdown, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, Mark Spitznagel, Mark Zuckerberg, market fundamentalism, mass immigration, megacity, Mikhail Gorbachev, Mohammed Bouazizi, money market fund, moral hazard, Murray Gell-Mann, Nick Bostrom, off-the-grid, panic early, Pershing Square Capital Management, Peter Singer: altruism, Ponzi scheme, power law, precautionary principle, prediction markets, proprietary trading, public intellectual, QAnon, quantitative easing, quantitative hedge fund, quantitative trading / quantitative finance, Ralph Nader, Ralph Nelson Elliott, random walk, Renaissance Technologies, rewilding, Richard Thaler, risk/return, road to serfdom, Ronald Reagan, Ronald Reagan: Tear down this wall, Rory Sutherland, Rupert Read, Sam Bankman-Fried, Silicon Valley, six sigma, smart contracts, social distancing, sovereign wealth fund, statistical arbitrage, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, systematic trading, tail risk, technoutopianism, The Chicago School, The Great Moderation, the scientific method, too big to fail, transaction costs, University of East Anglia, value at risk, Vanguard fund, We are as Gods, Whole Earth Catalog

More often than not, rather than discussing the nature of uncertainty and Black Swans, their conversations revolved around literature, history, art, and the vast array of fascinating people Mandelbrot had encountered during his long career (Margaret Mead, Noam Chomsky, Robert Oppenheimer, Stephen Jay Gould, and John von Neumann, to name a few). Mandelbrot, who died in 2010, would have an outsize influence on The Black Swan. In fact, the book is dedicated to him. But Taleb’s new insights into fractal forces at work in market crashes didn’t help him where it really counted at the time—at Empirica. * * * Empirica was bleeding.


pages: 1,396 words: 245,647

The Strangest Man: The Hidden Life of Paul Dirac, Mystic of the Atom by Graham Farmelo

Albert Einstein, anti-communist, Arthur Eddington, Berlin Wall, Bletchley Park, cuban missile crisis, double helix, Dr. Strangelove, Eddington experiment, Ernest Rutherford, Fall of the Berlin Wall, Fellow of the Royal Society, financial independence, gravity well, Henri Poincaré, invention of radio, invisible hand, Isaac Newton, John von Neumann, Kevin Kelly, Large Hadron Collider, Murray Gell-Mann, Neil Armstrong, period drama, Richard Feynman, Simon Singh, Stephen Hawking, strikebreaker, Suez canal 1869, Suez crisis 1956, University of East Anglia

Wigner was fearful of the future of the country, then under Admiral Horthy’s authoritarian regime. Despite all the political upheavals, Wigner had an exceptionally fine school education in mathematics and science, even more thorough than Dirac’s. Historians still debate why Budapest in the early twentieth century produced so many intellectual innovators, including John von Neumann, whom Dirac would later rate as the world’s finest mathematician, and Wigner’s friends Leó Szilárd and Edward Teller, both to do important research into the first nuclear weapons.17 The success of this cohort of Hungarians is partly due to their education, shortly after the war, in Budapest’s excellent high schools and partly to the vibrancy and ambition of the city’s Western-focused culture.18 Wigner was one of the shyest and most uncommunicative of the quantum physicists but, compared with Dirac, he was gregariousness itself, so conversation during their evening meals together was probably strained.

In the summer of 1939, Wigner, Szilárd and Teller persuaded Einstein to write to President Roosevelt, drawing his attention to the possibility of nuclear weapons and the danger that the Germans might produce one first.17 After a long delay, Roosevelt invited Einstein to join a committee of government advisers but he brusquely declined and sat out the war at the Institute for Advanced Study in Princeton, where word spread that the Nazis were indeed working on a bomb. In the spring of 1940, Dirac’s friends Oswald Veblen and John von Neumann wrote to the director Frank Aydelotte, urgently seeking his assistance to fund investigations into the chain reaction. In their letter, they mentioned a recent conversation with the Dutch physical chemist Peter Debye, who had led one of Berlin’s largest research institutes until the German authorities sent him abroad in order to free his laboratories for secret war work.


pages: 385 words: 111,113

Augmented: Life in the Smart Lane by Brett King

23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, agricultural Revolution, Airbnb, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apollo 11, Apollo Guidance Computer, Apple II, artificial general intelligence, asset allocation, augmented reality, autonomous vehicles, barriers to entry, bitcoin, Bletchley Park, blockchain, Boston Dynamics, business intelligence, business process, call centre, chief data officer, Chris Urmson, Clayton Christensen, clean water, Computing Machinery and Intelligence, congestion charging, CRISPR, crowdsourcing, cryptocurrency, data science, deep learning, DeepMind, deskilling, different worldview, disruptive innovation, distributed generation, distributed ledger, double helix, drone strike, electricity market, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, fiat currency, financial exclusion, Flash crash, Flynn Effect, Ford Model T, future of work, gamification, Geoffrey Hinton, gig economy, gigafactory, Google Glasses, Google X / Alphabet X, Hans Lippershey, high-speed rail, Hyperloop, income inequality, industrial robot, information asymmetry, Internet of things, invention of movable type, invention of the printing press, invention of the telephone, invention of the wheel, James Dyson, Jeff Bezos, job automation, job-hopping, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, Kim Stanley Robinson, Kiva Systems, Kodak vs Instagram, Leonard Kleinrock, lifelogging, low earth orbit, low skilled workers, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, megacity, Metcalfe’s law, Minecraft, mobile money, money market fund, more computing power than Apollo, Neal Stephenson, Neil Armstrong, Network effects, new economy, Nick Bostrom, obamacare, Occupy movement, Oculus Rift, off grid, off-the-grid, packet switching, pattern recognition, peer-to-peer, Ray Kurzweil, retail therapy, RFID, ride hailing / ride sharing, Robert Metcalfe, Salesforce, Satoshi Nakamoto, Second Machine Age, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart transportation, Snapchat, Snow Crash, social graph, software as a service, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, synthetic biology, systems thinking, TaskRabbit, technological singularity, TED Talk, telemarketer, telepresence, telepresence robot, Tesla Model S, The future is already here, The Future of Employment, Tim Cook: Apple, trade route, Travis Kalanick, TSMC, Turing complete, Turing test, Twitter Arab Spring, uber lyft, undersea cable, urban sprawl, V2 rocket, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, white picket fence, WikiLeaks, yottabyte

It’s why, as consumers, we have come to expect major new features to be incorporated into every new iPhone.3 The graph on the following page shows what accelerated technology growth has looked like over the last 600 years. Statisticians call this sort of graph a “hockey stick curve” as it indicates evidence of an exponential growth scenario. In the 20th century, graphs like this appeared with increasing regularity, especially where technology was involved. This led to the hypothesis of what mathematician John von Neumann and futurist Ray Kurzweil dubbed the singularity (sometimes called the technological singularity)—a time when technological advancement reaches escape velocity. In theory, the singularity means that we could solve any problem mankind faces through the application of increasingly powerful computing.


pages: 354 words: 105,322

The Road to Ruin: The Global Elites' Secret Plan for the Next Financial Crisis by James Rickards

"World Economic Forum" Davos, Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, asset allocation, asset-backed security, bank run, banking crisis, barriers to entry, Bayesian statistics, Bear Stearns, behavioural economics, Ben Bernanke: helicopter money, Benoit Mandelbrot, Berlin Wall, Bernie Sanders, Big bang: deregulation of the City of London, bitcoin, Black Monday: stock market crash in 1987, Black Swan, blockchain, Boeing 747, Bonfire of the Vanities, Bretton Woods, Brexit referendum, British Empire, business cycle, butterfly effect, buy and hold, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, cellular automata, cognitive bias, cognitive dissonance, complexity theory, Corn Laws, corporate governance, creative destruction, Credit Default Swap, cuban missile crisis, currency manipulation / currency intervention, currency peg, currency risk, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, debt deflation, Deng Xiaoping, disintermediation, distributed ledger, diversification, diversified portfolio, driverless car, Edward Lorenz: Chaos theory, Eugene Fama: efficient market hypothesis, failed state, Fall of the Berlin Wall, fiat currency, financial repression, fixed income, Flash crash, floating exchange rates, forward guidance, Fractional reserve banking, G4S, George Akerlof, Glass-Steagall Act, global macro, global reserve currency, high net worth, Hyman Minsky, income inequality, information asymmetry, interest rate swap, Isaac Newton, jitney, John Meriwether, John von Neumann, Joseph Schumpeter, junk bonds, Kenneth Rogoff, labor-force participation, large denomination, liquidity trap, Long Term Capital Management, low interest rates, machine readable, mandelbrot fractal, margin call, market bubble, Mexican peso crisis / tequila crisis, Minsky moment, Money creation, money market fund, mutually assured destruction, Myron Scholes, Naomi Klein, nuclear winter, obamacare, offshore financial centre, operational security, Paul Samuelson, Peace of Westphalia, Phillips curve, Pierre-Simon Laplace, plutocrats, prediction markets, price anchoring, price stability, proprietary trading, public intellectual, quantitative easing, RAND corporation, random walk, reserve currency, RFID, risk free rate, risk-adjusted returns, Robert Solow, Ronald Reagan, Savings and loan crisis, Silicon Valley, sovereign wealth fund, special drawing rights, stock buybacks, stocks for the long run, tech billionaire, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, too big to fail, transfer pricing, value at risk, Washington Consensus, We are all Keynesians now, Westphalian system

Complexity and the related field of chaos theory are two branches of the broader sciences of nonlinear mathematics and critical state systems analysis. Los Alamos has been on the cutting edge of these fields from its start. Significant breakthroughs in the 1970s were computational and built on earlier theoretical work from the 1940s and 1950s by iconic figures such as John von Neumann and Stanislaw Ulam. Theoretical constructs were harnessed to massive computing power to simulate phenomena such as hydrodynamic turbulence. Seeing a fast-flowing stream at sunset is an aesthetic experience; poets try to capture its noetic beauty. Still, an effort to write equations that precisely model the ebb and flow, twist and turn, of every molecule of H2O in the stream, not just at a point in time, but dynamically through time, presents a challenge.


pages: 343 words: 102,846

Trees on Mars: Our Obsession With the Future by Hal Niedzviecki

"World Economic Forum" Davos, Ada Lovelace, agricultural Revolution, Airbnb, Albert Einstein, Alvin Toffler, Amazon Robotics, anti-communist, big data - Walmart - Pop Tarts, big-box store, business intelligence, Charles Babbage, Colonization of Mars, computer age, crowdsourcing, data science, David Brooks, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, Flynn Effect, Ford Model T, Future Shock, Google Glasses, hive mind, Howard Zinn, if you build it, they will come, income inequality, independent contractor, Internet of things, invention of movable type, Jaron Lanier, Jeff Bezos, job automation, John von Neumann, knowledge economy, Kodak vs Instagram, life extension, Lyft, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Marshall McLuhan, Neil Armstrong, One Laptop per Child (OLPC), Peter H. Diamandis: Planetary Resources, Peter Thiel, Pierre-Simon Laplace, Ponzi scheme, precariat, prediction markets, Ralph Nader, randomized controlled trial, Ray Kurzweil, ride hailing / ride sharing, rising living standards, Robert Solow, Ronald Reagan, Salesforce, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, TaskRabbit, tech worker, technological singularity, technological solutionism, technoutopianism, Ted Kaczynski, TED Talk, Thomas L Friedman, Tyler Cowen, Uber and Lyft, uber lyft, Virgin Galactic, warehouse robotics, working poor

This was technological development of astonishing speed prompted, quite literally, by our embodied will to survive—embedded in us, as Richard Dawkins theorizes, on the molecular level. The loser is wiped out, after all; a poor result from a genetic perspective. At any rate, in the lead-up to America’s entering World War II and throughout that epic conflict, a ragtag group led by Jewish Hungarian John von Neumann worked feverishly to build the bomb and, at the same time, build one of the world’s first multiuse electronic calculating machines, the ENIAC machine housed at the Princeton University based Institute for Advanced Study. The military provided substantial funding for ENIAC, having already seen what these fellows could do when unleashed on a problem.


Capital Ideas Evolving by Peter L. Bernstein

Albert Einstein, algorithmic trading, Andrei Shleifer, asset allocation, behavioural economics, Black Monday: stock market crash in 1987, Bob Litterman, book value, business cycle, buy and hold, buy low sell high, capital asset pricing model, commodity trading advisor, computerized trading, creative destruction, currency risk, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, diversification, diversified portfolio, endowment effect, equity premium, equity risk premium, Eugene Fama: efficient market hypothesis, financial engineering, financial innovation, fixed income, high net worth, hiring and firing, index fund, invisible hand, Isaac Newton, John Meriwether, John von Neumann, Joseph Schumpeter, Kenneth Arrow, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, market bubble, mental accounting, money market fund, Myron Scholes, paper trading, passive investing, Paul Samuelson, Performance of Mutual Funds in the Period, price anchoring, price stability, random walk, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, seminal paper, Sharpe ratio, short selling, short squeeze, Silicon Valley, South Sea Bubble, statistical model, survivorship bias, systematic trading, tail risk, technology bubble, The Wealth of Nations by Adam Smith, transaction costs, yield curve, Yogi Berra, zero-sum game

Consequently, people depended on prayer and incantation, in one form or another, as the only available form of risk management. What other approach could you take when everything seemed to be God’s will or the will of the Fates? As we move toward modern times, nature has declining importance. What takes its place? I would seek the answer to that question in the words of the mathematician John von Neumann, who developed the theory of games of strategy (as opposed to games of chance) during the 1920s and 1930s. The most significant insight in game theory was to recognize that men and women are not Robinson Crusoes—each individual isolated from all other individuals. Failure to keep this distinction in mind is the primary reason the techniques and concepts of the natural sciences so often lead the social scientists astray.


pages: 416 words: 106,582

This Will Make You Smarter: 150 New Scientific Concepts to Improve Your Thinking by John Brockman

23andMe, adjacent possible, Albert Einstein, Alfred Russel Wallace, Anthropocene, banking crisis, Barry Marshall: ulcers, behavioural economics, Benoit Mandelbrot, Berlin Wall, biofilm, Black Swan, Bletchley Park, butterfly effect, Cass Sunstein, cloud computing, cognitive load, congestion charging, correlation does not imply causation, Daniel Kahneman / Amos Tversky, dark matter, data acquisition, David Brooks, delayed gratification, Emanuel Derman, epigenetics, Evgeny Morozov, Exxon Valdez, Flash crash, Flynn Effect, Garrett Hardin, Higgs boson, hive mind, impulse control, information retrieval, information security, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, Jaron Lanier, Johannes Kepler, John von Neumann, Kevin Kelly, Large Hadron Collider, lifelogging, machine translation, mandelbrot fractal, market design, Mars Rover, Marshall McLuhan, microbiome, Murray Gell-Mann, Nicholas Carr, Nick Bostrom, ocean acidification, open economy, Pierre-Simon Laplace, place-making, placebo effect, power law, pre–internet, QWERTY keyboard, random walk, randomized controlled trial, rent control, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, Satyajit Das, Schrödinger's Cat, scientific management, security theater, selection bias, Silicon Valley, Stanford marshmallow experiment, stem cell, Steve Jobs, Steven Pinker, Stewart Brand, Stuart Kauffman, sugar pill, synthetic biology, the scientific method, Thorstein Veblen, Turing complete, Turing machine, twin studies, Vilfredo Pareto, Walter Mischel, Whole Earth Catalog, WikiLeaks, zero-sum game

In a positive-sum game, a rational, self-interested actor may benefit the other actor with the same choice that benefits himself or herself. More colloquially, positive-sum games are called win-win situations and are captured in the cliché “Everybody wins.” This family of concepts—zero-sum, nonzero-sum, positive-sum, negative-sum, constant-sum, and variable-sum games—was introduced by John von Neumann and Oskar Morgenstern when they invented the mathematical theory of games in 1944. The Google Books Ngram tool shows that the terms saw a steady increase in popularity beginning in the 1950s, and their colloquial relative “win-win” began a similar ascent in the 1970s. Once people are thrown together in an interaction, their choices don’t determine whether they are in a zero- or nonzero-sum game; the game is a part of the world they live in.


pages: 394 words: 108,215

What the Dormouse Said: How the Sixties Counterculture Shaped the Personal Computer Industry by John Markoff

Any sufficiently advanced technology is indistinguishable from magic, Apple II, back-to-the-land, beat the dealer, Bill Duvall, Bill Gates: Altair 8800, Buckminster Fuller, California gold rush, card file, computer age, Computer Lib, computer vision, conceptual framework, cuban missile crisis, different worldview, digital divide, Donald Knuth, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Thorp, El Camino Real, Electric Kool-Aid Acid Test, Fairchild Semiconductor, General Magic , general-purpose programming language, Golden Gate Park, Hacker Ethic, Hans Moravec, hypertext link, informal economy, information retrieval, invention of the printing press, Ivan Sutherland, Jeff Rulifson, John Markoff, John Nash: game theory, John von Neumann, Kevin Kelly, knowledge worker, Lewis Mumford, Mahatma Gandhi, Menlo Park, military-industrial complex, Mother of all demos, Norbert Wiener, packet switching, Paul Terrell, popular electronics, punch-card reader, QWERTY keyboard, RAND corporation, RFC: Request For Comment, Richard Stallman, Robert X Cringely, Sand Hill Road, Silicon Valley, Silicon Valley startup, South of Market, San Francisco, speech recognition, Steve Crocker, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, technological determinism, Ted Nelson, The Hackers Conference, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Turing test, union organizing, Vannevar Bush, We are as Gods, Whole Earth Catalog, William Shockley: the traitorous eight

Composed of thirteen thousand mechanical relays, the SSEC, which could perform a lumbering twenty-five instructions per second (today an Intel Pentium microprocessor will easily surpass three billion instructions in the same second), was a computing machine that straddled the divide between calculators and modern computers. It didn’t have a memory in the modern sense, and programs were entered via punched paper tape. The skills Crane developed on the SSEC later proved useful when he was hired to work on a new computer being built by the legendary mathematician John Von Neumann at the Institute for Advanced Study in Princeton. Frustrated with the slow speed of getting data into and out of his machine, Von Neumann had persuaded IBM’s founder, Tom Watson Sr., to donate a punch-card reader to help speed up the process. Since he was one of the few people who knew how card readers worked, Crane was enlisted in the project.


pages: 383 words: 105,021

Dark Territory: The Secret History of Cyber War by Fred Kaplan

air gap, Big Tech, Cass Sunstein, Charles Babbage, computer age, data acquisition, drone strike, dumpster diving, Edward Snowden, game design, hiring and firing, index card, information security, Internet of things, Jacob Appelbaum, John Markoff, John von Neumann, kremlinology, Laura Poitras, Mikhail Gorbachev, millennium bug, Morris worm, national security letter, Oklahoma City bombing, operational security, packet switching, pre–internet, RAND corporation, Ronald Reagan, seminal paper, Seymour Hersh, Silicon Valley, Skype, Stuxnet, tech worker, Timothy McVeigh, unit 8200, uranium enrichment, Wargames Reagan, Y2K, zero day

In April 1967, shortly before ARPANET’s rollout, an engineer named Willis Ware wrote a paper called “Security and Privacy in Computer Systems” and delivered it at the semiannual Joint Computer Conference in New York City. Ware was a pioneer in the field of computers, dating back to the late 1940s, when there barely was such a field. At Princeton’s Institute for Advanced Studies, he’d been a protégé of John von Neumann, helping design one of the first electrical computers. For years now, he headed the computer science department at the RAND Corporation, an Air Force–funded think tank in Santa Monica, California. He well understood the point of ARPANET, lauded its goals, admired its ambition; but he was worried about some implications that its managers had overlooked.


pages: 335 words: 107,779

Some Remarks by Neal Stephenson

airport security, augmented reality, barriers to entry, Bletchley Park, British Empire, cable laying ship, call centre, cellular automata, edge city, Eratosthenes, Fellow of the Royal Society, Hacker Ethic, high-speed rail, impulse control, Iridium satellite, Isaac Newton, Jaron Lanier, John von Neumann, Just-in-time delivery, Kevin Kelly, Kim Stanley Robinson, megaproject, music of the spheres, Neal Stephenson, Neil Armstrong, Norbert Wiener, offshore financial centre, oil shock, packet switching, pirate software, Richard Feynman, Saturday Night Live, shareholder value, Shenzhen special economic zone , Silicon Valley, Skype, slashdot, Snow Crash, social web, Socratic dialogue, South China Sea, SpaceShipOne, special economic zone, Stephen Hawking, the scientific method, trade route, Turing machine, undersea cable, uranium enrichment, Vernor Vinge, X Prize

The present thought occurring at t1, together with the Production Rule, will determine what F will think at t2.” Combined with the monadic property of being able to perceive the states of all other monads, this comes close to being a mathematically formal definition of cellular automata, a branch of mathematics generally agreed to have been invented by Stanislaw Ulam and John von Neumann during the 1940s as an outgrowth of work at Los Alamos. The impressive capabilities of such systems have, in subsequent decades, drawn the attention of many luminaries from the worlds of mathematics and physics, some of whom have proposed that the physical universe might, in fact, consist of cellular automata carrying out a calculation—a hypothesis known as Digital Physics, or It from Bit. 4.


pages: 374 words: 111,284

The AI Economy: Work, Wealth and Welfare in the Robot Age by Roger Bootle

"World Economic Forum" Davos, 3D printing, agricultural Revolution, AI winter, Albert Einstein, AlphaGo, Alvin Toffler, anti-work, antiwork, autonomous vehicles, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Bletchley Park, blockchain, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Carl Icahn, Chris Urmson, computer age, Computing Machinery and Intelligence, conceptual framework, corporate governance, correlation does not imply causation, creative destruction, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, Dr. Strangelove, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, facts on the ground, fake news, financial intermediation, full employment, future of work, Future Shock, general purpose technology, Great Leap Forward, Hans Moravec, income inequality, income per capita, industrial robot, Internet of things, invention of the wheel, Isaac Newton, James Watt: steam engine, Jeff Bezos, Jeremy Corbyn, job automation, job satisfaction, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, license plate recognition, low interest rates, machine translation, Marc Andreessen, Mark Zuckerberg, market bubble, mega-rich, natural language processing, Network effects, new economy, Nicholas Carr, Ocado, Paul Samuelson, Peter Thiel, Phillips curve, positional goods, quantitative easing, RAND corporation, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, rising living standards, road to serfdom, Robert Gordon, Robert Shiller, Robert Solow, Rutger Bregman, Second Machine Age, secular stagnation, self-driving car, seminal paper, Silicon Valley, Silicon Valley billionaire, Simon Kuznets, Skype, social intelligence, spinning jenny, Stanislav Petrov, Stephen Hawking, Steven Pinker, synthetic biology, technological singularity, The Future of Employment, The Wealth of Nations by Adam Smith, Thomas Malthus, trade route, universal basic income, US Airways Flight 1549, Vernor Vinge, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, wealth creators, winner-take-all economy, world market for maybe five computers, Y2K, Yogi Berra

Well, it is here in this book anyway. Whether and when it will ever be there, in the outside world, and with what consequences, is what we must now consider. The first use of the term “singularity” to refer to a future technology driven event seems to have been by the legendary computer pioneer John von Neumann, in the 1950s. But it doesn’t seem to have caught on until, in 1983, the mathematician Vernor Vinge wrote about an approaching “technological singularity.”3 More recently, the “Singularity,” notably now sporting a capital “S,” has become closely associated with the name of Ray Kurzweil, who published his book The Singularity is Near: When Humans Transcend Biology in 2005.


pages: 407 words: 104,622

The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution by Gregory Zuckerman

affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, Andrew Wiles, automated trading system, backtesting, Bayesian statistics, Bear Stearns, beat the dealer, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Black Monday: stock market crash in 1987, blockchain, book value, Brownian motion, butter production in bangladesh, buy and hold, buy low sell high, Cambridge Analytica, Carl Icahn, Claude Shannon: information theory, computer age, computerized trading, Credit Default Swap, Daniel Kahneman / Amos Tversky, data science, diversified portfolio, Donald Trump, Edward Thorp, Elon Musk, Emanuel Derman, endowment effect, financial engineering, Flash crash, George Gilder, Gordon Gekko, illegal immigration, index card, index fund, Isaac Newton, Jim Simons, John Meriwether, John Nash: game theory, John von Neumann, junk bonds, Loma Prieta earthquake, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, Mark Zuckerberg, Michael Milken, Monty Hall problem, More Guns, Less Crime, Myron Scholes, Naomi Klein, natural language processing, Neil Armstrong, obamacare, off-the-grid, p-value, pattern recognition, Peter Thiel, Ponzi scheme, prediction markets, proprietary trading, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, Robert Mercer, Ronald Reagan, self-driving car, Sharpe ratio, Silicon Valley, sovereign wealth fund, speech recognition, statistical arbitrage, statistical model, Steve Bannon, Steve Jobs, stochastic process, the scientific method, Thomas Bayes, transaction costs, Turing machine, Two Sigma

Most showed faith, hoping Simons could figure out a way to improve the results, but Simons himself was racked with self-doubt. The setback was “stomach-wrenching,” he told a friend. “There’s no rhyme or reason.” Simons had to find a different approach. CHAPTER FOUR Truth . . . is much too complicated to allow for anything but approximations. John von Neumann Jim Simons was miserable. He hadn’t abandoned a flourishing academic career to deal with sudden losses and grumpy investors. Simons had to find a different method to speculate on financial markets; Lenny Baum’s approach, reliant on intellect and instinct, just didn’t seem to work. It also left Simons deeply unsettled.


pages: 419 words: 109,241

A World Without Work: Technology, Automation, and How We Should Respond by Daniel Susskind

"World Economic Forum" Davos, 3D printing, agricultural Revolution, AI winter, Airbnb, Albert Einstein, algorithmic trading, AlphaGo, artificial general intelligence, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, Big Tech, blue-collar work, Boston Dynamics, British Empire, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, computer age, computer vision, computerized trading, creative destruction, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, Demis Hassabis, demographic transition, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, driverless car, drone strike, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, fake news, financial innovation, flying shuttle, Ford Model T, fulfillment center, future of work, gig economy, Gini coefficient, Google Glasses, Gödel, Escher, Bach, Hans Moravec, income inequality, income per capita, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Hargreaves, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kenneth Arrow, Kevin Roose, Khan Academy, Kickstarter, Larry Ellison, low skilled workers, lump of labour, machine translation, Marc Andreessen, Mark Zuckerberg, means of production, Metcalfe’s law, natural language processing, Neil Armstrong, Network effects, Nick Bostrom, Occupy movement, offshore financial centre, Paul Samuelson, Peter Thiel, pink-collar, precariat, purchasing power parity, Ray Kurzweil, ride hailing / ride sharing, road to serfdom, Robert Gordon, Sam Altman, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, social intelligence, software is eating the world, sovereign wealth fund, spinning jenny, Stephen Hawking, Steve Jobs, strong AI, tacit knowledge, technological solutionism, TED Talk, telemarketer, The Future of Employment, The Rise and Fall of American Growth, the scientific method, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, Travis Kalanick, Turing test, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, upwardly mobile, warehouse robotics, Watson beat the top human players on Jeopardy!, We are the 99%, wealth creators, working poor, working-age population, Y Combinator

Given nothing more than those, it played itself for three days to generate its own data—and it returned to thrash its older cousin, AlphaGo.31 Other systems are using similar techniques to engage in pursuits that more closely resemble the messiness of real life. Chess and go, for instance, are games of “perfect information”: both players see the entire board and all the pieces. But as the legendary mathematician John von Neumann put it, “real life is not like that. Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do.” That is why poker has fascinated researchers—and proven so hard to automate. Yet DeepStack, developed by a team in Canada and the Czech Republic in 2017, managed to defeat professional poker players in a series of more than forty-four thousand heads-up games (that is, games involving two players).


pages: 432 words: 106,612

Trillions: How a Band of Wall Street Renegades Invented the Index Fund and Changed Finance Forever by Robin Wigglesworth

Albert Einstein, algorithmic trading, asset allocation, Bear Stearns, behavioural economics, Benoit Mandelbrot, Big Tech, Black Monday: stock market crash in 1987, Blitzscaling, Brownian motion, buy and hold, California gold rush, capital asset pricing model, Carl Icahn, cloud computing, commoditize, coronavirus, corporate governance, corporate raider, COVID-19, data science, diversification, diversified portfolio, Donald Trump, Elon Musk, Eugene Fama: efficient market hypothesis, fear index, financial engineering, fixed income, Glass-Steagall Act, Henri Poincaré, index fund, industrial robot, invention of the wheel, Japanese asset price bubble, Jeff Bezos, Johannes Kepler, John Bogle, John von Neumann, Kenneth Arrow, lockdown, Louis Bachelier, machine readable, money market fund, Myron Scholes, New Journalism, passive investing, Paul Samuelson, Paul Volcker talking about ATMs, Performance of Mutual Funds in the Period, Peter Thiel, pre–internet, RAND corporation, random walk, risk-adjusted returns, road to serfdom, Robert Shiller, rolodex, seminal paper, Sharpe ratio, short selling, Silicon Valley, sovereign wealth fund, subprime mortgage crisis, the scientific method, transaction costs, uptick rule, Upton Sinclair, Vanguard fund

The eclecticism of RAND’s research community is reflected in his first published works, which were a proposal for a smog tax and a review of aircraft compartment design criteria for Army deployments. The nascent field of computing also rubbed off on Sharpe. He learned to program on a hulking RAND computer designed by John von Neumann—one of the greatest American mathematicians of the twentieth century—which staff had nicknamed “Johnniac,” as well as a state-of-the-art IBM machine. This then-novel skill, honed through countless brutal nighttime keypunch sessions, would prove invaluable for the young economist. Aside from helping Sharpe counter his weakness at pure mathematics, becoming one of the first-ever economist-programmers ultimately helped him secure a doctorate.


pages: 405 words: 105,395

Empire of the Sum: The Rise and Reign of the Pocket Calculator by Keith Houston

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Andy Kessler, Apollo 11, Apollo 13, Apple II, Bletchley Park, Boris Johnson, Charles Babbage, classic study, clockwork universe, computer age, Computing Machinery and Intelligence, double entry bookkeeping, Edmond Halley, Fairchild Semiconductor, Fellow of the Royal Society, Grace Hopper, human-factors engineering, invention of movable type, invention of the telephone, Isaac Newton, Johann Wolfgang von Goethe, Johannes Kepler, John Markoff, John von Neumann, Jony Ive, Kickstarter, machine readable, Masayoshi Son, Menlo Park, meta-analysis, military-industrial complex, Mitch Kapor, Neil Armstrong, off-by-one error, On the Revolutions of the Heavenly Spheres, orbital mechanics / astrodynamics, pattern recognition, popular electronics, QWERTY keyboard, Ralph Waldo Emerson, Robert X Cringely, side project, Silicon Valley, skunkworks, SoftBank, Steve Jobs, Steve Wozniak, The Home Computer Revolution, the payments system, Turing machine, Turing test, V2 rocket, William Shockley: the traitorous eight, Works Progress Administration, Yom Kippur War

After all, the electronic computer had shown that there was a new way to build calculating machines—one that did away with gears to be oiled and handles to be cranked, that worked near silently and with astounding speed. Back in 1949, the Mathematical Tables Project had inadvertently accelerated the transition to this brave new world. John von Neumann, a Hungarian American scientist of prodigious intellect and an alumnus of the Manhattan Project to build the first atomic bomb, had approached the MTP with a classic problem of economics: how to feed a given number of people as cheaply as possible with a fixed set of different ingredients.57 Twenty-five MTP computers toiled over the problem for twenty-one days, but von Neumann did not really care about their solution; instead, he wanted to confirm his suspicion that electronic computers were superior to the human variety.


pages: 913 words: 265,787

How the Mind Works by Steven Pinker

affirmative action, agricultural Revolution, Alfred Russel Wallace, Apple Newton, backpropagation, Buckminster Fuller, cognitive dissonance, Columbine, combinatorial explosion, complexity theory, computer age, computer vision, Computing Machinery and Intelligence, Daniel Kahneman / Amos Tversky, delayed gratification, disinformation, double helix, Dr. Strangelove, experimental subject, feminist movement, four colour theorem, Geoffrey Hinton, Gordon Gekko, Great Leap Forward, greed is good, Gregor Mendel, hedonic treadmill, Henri Poincaré, Herman Kahn, income per capita, information retrieval, invention of agriculture, invention of the wheel, Johannes Kepler, John von Neumann, lake wobegon effect, language acquisition, lateral thinking, Linda problem, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Mikhail Gorbachev, Murray Gell-Mann, mutually assured destruction, Necker cube, out of africa, Parents Music Resource Center, pattern recognition, phenotype, Plato's cave, plutocrats, random walk, Richard Feynman, Ronald Reagan, Rubik’s Cube, Saturday Night Live, scientific worldview, Search for Extraterrestrial Intelligence, sexual politics, social intelligence, Steven Pinker, Stuart Kauffman, tacit knowledge, theory of mind, Thorstein Veblen, Tipper Gore, Turing machine, urban decay, Yogi Berra

Strangelove, with his disconcerting tic of giving the Nazi salute, is one of cinema’s all-time eeriest characters. He was meant to symbolize a kind of intellectual who until recently was prominent in the public’s imagination: the nuclear strategist, paid to think the unthinkable. These men, who included Henry Kissinger (on whom Sellers based his portrayal), Herman Kahn, John von Neumann, and Edward Teller, were stereotyped as amoral nerds who cheerfully filled blackboards with equations about megadeaths and mutual assured destruction. Perhaps the scariest thing about them was their paradoxical conclusions—for example, that safety in the nuclear age comes from exposing one’s cities and protecting one’s missiles.

The thirty-six dramatic situations. Boston: The Writer, Inc. Posner, M. I. 1978. Chronometric explorations of mind. Hillsdale, N.J.: Erlbaum. Poundstone, W. 1988. Labyrinths of reason: Paradox, puzzles, and the frailty of knowledge. New York: Anchor. Poundstone, W. 1992. Prisoner’s dilemma: John von Neumann, game theory, and the puzzle of the bomb. New York: Anchor. Prasada, S., & Pinker, S. 1993. Generalizations of regular and irregular morphological patterns. Language and Cognitive Processes, 8, 1–56. Premack, D. 1976. Intelligence in ape and man. Hillsdale, N.J.: Erlbaum. Premack, D. 1990.


pages: 336 words: 113,519

The Undoing Project: A Friendship That Changed Our Minds by Michael Lewis

Albert Einstein, availability heuristic, behavioural economics, Cass Sunstein, choice architecture, complexity theory, Daniel Kahneman / Amos Tversky, Donald Trump, Douglas Hofstadter, endowment effect, feminist movement, framing effect, hindsight bias, John von Neumann, Kenneth Arrow, Linda problem, loss aversion, medical residency, Menlo Park, Murray Gell-Mann, Nate Silver, New Journalism, Paul Samuelson, peak-end rule, Richard Thaler, Saturday Night Live, Skinner box, Stanford marshmallow experiment, statistical model, systematic bias, the new new thing, Thomas Bayes, Walter Mischel, Yom Kippur War

It effectively turned a blind eye to gambling. Odd this, as the search for a theory about how people made risky decisions had started as an attempt to make Frenchmen shrewder gamblers. Amos’s text skipped over the long, tortured history of utility theory after Bernoulli all the way to 1944. A Hungarian Jew named John von Neumann and an Austrian anti-Semite named Oskar Morgenstern, both of whom fled Europe for America, somehow came together that year to publish what might be called the rules of rationality. A rational person making a decision between risky propositions, for instance, shouldn’t violate the von Neumann and Morgenstern transitivity axiom: If he preferred A to B and B to C, then he should prefer A to C.


A People’s History of Computing in the United States by Joy Lisi Rankin

activist fund / activist shareholder / activist investor, Albert Einstein, Apple II, Bill Gates: Altair 8800, Charles Babbage, Compatible Time-Sharing System, computer age, Computer Lib, corporate social responsibility, digital divide, Douglas Engelbart, Douglas Engelbart, Grace Hopper, Hacker Ethic, Howard Rheingold, Howard Zinn, it's over 9,000, Jeff Bezos, John Markoff, John von Neumann, language acquisition, Mark Zuckerberg, Menlo Park, military-industrial complex, Mother of all demos, Multics, Network effects, Norbert Wiener, pink-collar, profit motive, public intellectual, punch-card reader, RAND corporation, Silicon Valley, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Ted Nelson, the market place, urban planning, Whole Earth Catalog, wikimedia commons

University of Illinois Archives (2013). http://­archives​.­library​.­illinois​.­edu​/ ­blog​/ ­birth​-­of​ -­t he​-­computer​-­age. Archived at perma.cc/RJ57–9NV8. Anderson, Terry H. The Movement and the Sixties: Protest in Amer­i­ca from Greensboro to Wounded Knee. New York: Oxford University Press, 1995. Aspray, William. Computing before Computers. Ames: Iowa State University Press, 1990. —­—­—. John von Neumann and the Origins of Modern Computing. Cambridge, MA: MIT Press, 1991. Aspray, William, and Paul E. Ceruzzi, eds. The Internet and American Business. Cambridge, MA: MIT Press, 2008. Aspray, William, and Jeffrey Yost. “New Voices, New Topics.” IEEE Annals of the History of Computing 33, no. 2 (2011): 4–8.


pages: 443 words: 116,832

The Hacker and the State: Cyber Attacks and the New Normal of Geopolitics by Ben Buchanan

active measures, air gap, Bernie Sanders, bitcoin, blockchain, borderless world, Brian Krebs, British Empire, Cass Sunstein, citizen journalism, Citizen Lab, credit crunch, cryptocurrency, cuban missile crisis, data acquisition, disinformation, Donald Trump, drone strike, Edward Snowden, fake news, family office, Hacker News, hive mind, information security, Internet Archive, Jacob Appelbaum, John Markoff, John von Neumann, Julian Assange, Kevin Roose, Kickstarter, kremlinology, Laura Poitras, MITM: man-in-the-middle, Nate Silver, operational security, post-truth, profit motive, RAND corporation, ransomware, risk tolerance, Robert Hanssen: Double agent, rolodex, Ronald Reagan, Russian election interference, seminal paper, Silicon Valley, South China Sea, Steve Jobs, Stuxnet, subscription business, technoutopianism, undersea cable, uranium enrichment, Vladimir Vetrov: Farewell Dossier, Wargames Reagan, WikiLeaks, zero day

David Sanger and Michael Schmidt, “More Sanctions on North Korea After Sony Case,” New York Times, January 2, 2015. 21. Symantec Security Response, “WannaCry: Ransomware Attacks Show Strong Links to Lazarus Group,” Symantec blog, May 22, 2017. 22. At some level, the idea of the worm dated back to a famous work in computer science written in 1966. John Von Neumann and Arthur W. Burks, “Theory of Self-Reproducing Automata,” IEEE Transactions on Neural Networks 5, no. 1 (1966): 3–14. 23. Details are not abundant about the initial infection vector for WannaCry. For one view, see thegrugq, “The Triple A Threat: Aggressive Autonomous Agents,” presentation deck, Comae Technologies, 2017, 22. 24.


Human Frontiers: The Future of Big Ideas in an Age of Small Thinking by Michael Bhaskar

"Margaret Hamilton" Apollo, 3D printing, additive manufacturing, AI winter, Albert Einstein, algorithmic trading, AlphaGo, Anthropocene, artificial general intelligence, augmented reality, autonomous vehicles, backpropagation, barriers to entry, basic income, behavioural economics, Benoit Mandelbrot, Berlin Wall, Big bang: deregulation of the City of London, Big Tech, Bletchley Park, blockchain, Boeing 747, brain emulation, Brexit referendum, call centre, carbon tax, charter city, citizen journalism, Claude Shannon: information theory, Clayton Christensen, clean tech, clean water, cognitive load, Columbian Exchange, coronavirus, cosmic microwave background, COVID-19, creative destruction, CRISPR, crony capitalism, cyber-physical system, dark matter, David Graeber, deep learning, DeepMind, deindustrialization, dematerialisation, Demis Hassabis, demographic dividend, Deng Xiaoping, deplatforming, discovery of penicillin, disruptive innovation, Donald Trump, double entry bookkeeping, Easter island, Edward Jenner, Edward Lorenz: Chaos theory, Elon Musk, en.wikipedia.org, endogenous growth, energy security, energy transition, epigenetics, Eratosthenes, Ernest Rutherford, Eroom's law, fail fast, false flag, Fellow of the Royal Society, flying shuttle, Ford Model T, Francis Fukuyama: the end of history, general purpose technology, germ theory of disease, glass ceiling, global pandemic, Goodhart's law, Google Glasses, Google X / Alphabet X, GPT-3, Haber-Bosch Process, hedonic treadmill, Herman Kahn, Higgs boson, hive mind, hype cycle, Hyperloop, Ignaz Semmelweis: hand washing, Innovator's Dilemma, intangible asset, interchangeable parts, Internet of things, invention of agriculture, invention of the printing press, invention of the steam engine, invention of the telegraph, invisible hand, Isaac Newton, ITER tokamak, James Watt: steam engine, James Webb Space Telescope, Jeff Bezos, jimmy wales, job automation, Johannes Kepler, John von Neumann, Joseph Schumpeter, Kenneth Arrow, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, Large Hadron Collider, liberation theology, lockdown, lone genius, loss aversion, Louis Pasteur, Mark Zuckerberg, Martin Wolf, megacity, megastructure, Menlo Park, Minecraft, minimum viable product, mittelstand, Modern Monetary Theory, Mont Pelerin Society, Murray Gell-Mann, Mustafa Suleyman, natural language processing, Neal Stephenson, nuclear winter, nudge unit, oil shale / tar sands, open economy, OpenAI, opioid epidemic / opioid crisis, PageRank, patent troll, Peter Thiel, plutocrats, post scarcity, post-truth, precautionary principle, public intellectual, publish or perish, purchasing power parity, quantum entanglement, Ray Kurzweil, remote working, rent-seeking, Republic of Letters, Richard Feynman, Robert Gordon, Robert Solow, secular stagnation, shareholder value, Silicon Valley, Silicon Valley ideology, Simon Kuznets, skunkworks, Slavoj Žižek, sovereign wealth fund, spinning jenny, statistical model, stem cell, Steve Jobs, Stuart Kauffman, synthetic biology, techlash, TED Talk, The Rise and Fall of American Growth, the scientific method, The Wealth of Nations by Adam Smith, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, TikTok, total factor productivity, transcontinental railway, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, uranium enrichment, We wanted flying cars, instead we got 140 characters, When a measure becomes a target, X Prize, Y Combinator

Thanks to the program, previously unthinkable moves are now part of the tactical lexicon. AlphaGo, like AlphaFold, jolted the game out of a local maximum. DeepMind is at the forefront of a well-publicised renaissance in AI. (AI itself is a big idea that goes back to Alan Turing and pioneers like John von Neumann and Marvin Minsky and, in the form of dreams of automata, much earlier still.) Over recent decades, computer scientists have brought together a new generation of techniques: evolutionary algorithms, reinforcement learning, deep neural networks and backpropagation, adversarial networks, logistic regression, decision trees and Bayesian networks, among others.


Visual Thinking: The Hidden Gifts of People Who Think in Pictures, Patterns, and Abstractions by Temple Grandin, Ph.D.

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, a long time ago in a galaxy far, far away, air gap, Albert Einstein, American Society of Civil Engineers: Report Card, Apollo 11, Apple II, ASML, Asperger Syndrome, autism spectrum disorder, autonomous vehicles, Black Lives Matter, Boeing 737 MAX, Captain Sullenberger Hudson, clean water, cloud computing, computer vision, Computing Machinery and Intelligence, coronavirus, cotton gin, COVID-19, defense in depth, Drosophila, Elon Musk, en.wikipedia.org, GPT-3, Gregor Mendel, Greta Thunberg, hallucination problem, helicopter parent, income inequality, industrial robot, invention of movable type, Isaac Newton, James Webb Space Telescope, John Nash: game theory, John von Neumann, Jony Ive, language acquisition, longitudinal study, Mark Zuckerberg, Mars Rover, meta-analysis, Neil Armstrong, neurotypical, pattern recognition, Peter Thiel, phenotype, ransomware, replication crisis, Report Card for America’s Infrastructure, Robert X Cringely, Saturday Night Live, self-driving car, seminal paper, Silicon Valley, Skinner box, space junk, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Tacoma Narrows Bridge, TaskRabbit, theory of mind, TikTok, twin studies, unpaid internship, upwardly mobile, US Airways Flight 1549, warehouse automation, warehouse robotics, web application, William Langewiesche, Y Combinator

It’s possible that his mathematical mind may have been stimulated by Einstein’s book on the theory of relativity, a gift from Turing’s grandfather. At King’s College in Cambridge, England, along with advanced math, Turing studied cryptology. He read several influential books, including Bertrand Russell’s Introduction to Mathematical Philosophy and John von Neumann’s text on quantum mechanics. In a course called “Foundations of Mathematics” with British mathematician and codebreaker M. H. A. Newman, Turing first encountered David Hilbert’s Entscheidungsproblem, or “decision problem”: Is it possible to use an algorithm to determine whether an inference made during an operation of formal logic is valid?


pages: 480 words: 123,979

Dawn of the New Everything: Encounters With Reality and Virtual Reality by Jaron Lanier

4chan, air gap, augmented reality, back-to-the-land, Big Tech, Bill Atkinson, Buckminster Fuller, Burning Man, carbon footprint, cloud computing, collaborative editing, commoditize, Computer Lib, cosmological constant, creative destruction, crowdsourcing, deep learning, Donald Trump, Douglas Engelbart, Douglas Hofstadter, El Camino Real, Elon Musk, fake news, Firefox, game design, general-purpose programming language, gig economy, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Hacker Ethic, Hans Moravec, Howard Rheingold, hype cycle, impulse control, information asymmetry, intentional community, invisible hand, Ivan Sutherland, Jaron Lanier, John Gilmore, John Perry Barlow, John von Neumann, Kevin Kelly, Kickstarter, Kuiper Belt, lifelogging, mandelbrot fractal, Mark Zuckerberg, Marshall McLuhan, Menlo Park, military-industrial complex, Minecraft, Mitch Kapor, Mondo 2000, Mother of all demos, Murray Gell-Mann, Neal Stephenson, Netflix Prize, Network effects, new economy, Nick Bostrom, Norbert Wiener, Oculus Rift, pattern recognition, Paul Erdős, peak TV, Plato's cave, profit motive, Project Xanadu, quantum cryptography, Ray Kurzweil, reality distortion field, recommendation engine, Richard Feynman, Richard Stallman, Ronald Reagan, self-driving car, Silicon Valley, Silicon Valley startup, Skinner box, Skype, Snapchat, stem cell, Stephen Hawking, Steve Bannon, Steve Jobs, Steven Levy, Stewart Brand, systems thinking, technoutopianism, Ted Nelson, telemarketer, telepresence, telepresence robot, Thorstein Veblen, Turing test, Vernor Vinge, Whole Earth Catalog, Whole Earth Review, WikiLeaks, wikimedia commons

Hopper’s team was spectacular, even creating an optimizing compiler, way ahead of when that would become a hot topic in computer science. Text-based code demands that one particular abstraction become dominant, for it will provide the vocabulary. Therefore Hopper’s approach had the effect of making abstractions seem fundamental and unavoidable. Picture This Most of the earliest computers, such as one churning in John von Neumann’s basement lab at the Institute for Advanced Study at Princeton, included a rudimentary visual display: a light for each bit so you could watch it flipping moment to moment.3 You could watch a program running.4 That’s how I like to think about computation, as a concrete process involving materials changing states; the flipping bits.


pages: 485 words: 126,597

Paper: A World History by Mark Kurlansky

Ada Lovelace, Charles Babbage, circular economy, clean water, computer age, Edward Snowden, Great Leap Forward, invention of the telephone, invention of writing, Isaac Newton, James Watt: steam engine, John von Neumann, Joseph-Marie Jacquard, lone genius, Marshall McLuhan, means of production, moveable type in China, paper trading, planned obsolescence, trade route, Vannevar Bush

Hoe invents the steam-powered rotary printing press. 1863 American papermakers start using wood pulp. 1867 English wood pulp grinder exhibited in Paris. 1867 Wood pulp for paper first ground in the United States in Stockbridge, Massachusetts. 1867 Typewriter invented. 1872 United States surpasses Britain and Germany to become the largest paper producer in the world. 1874 Yukosha Company begins making machine-made paper in Tokyo, and six other companies follow in Osaka, Kyoto, and Kobe. 1890 US census tabulated by punch-card machines. 1899 Swedish explorer Sven Hedin, while excavating the ruins of the vanished city of Lu Lan, finds paper from 252 BCE, completely upsetting the history of paper. 1931 Vannevar Bush builds an analog electromechanical computer. 1945 John von Neumann publishes a paper on using binary numbers to program electronic memory. 1947 Transistor invented at Bell Labs. 1951 Remington Rand produces forty-six UNIVAC I computers with memory storage and output on magnetic tape. 1958 Microchip invented. ACKNOWLEDGMENTS MY FIRST THANK-YOU IS TO KERMIT HUMMEL, WHO CAME TO ME out of the blue and convinced me that paper was the subject on which I ought to be writing.


Stock Market Wizards: Interviews With America's Top Stock Traders by Jack D. Schwager

Asian financial crisis, banking crisis, barriers to entry, Bear Stearns, beat the dealer, Black-Scholes formula, book value, commodity trading advisor, computer vision, East Village, Edward Thorp, financial engineering, financial independence, fixed income, implied volatility, index fund, Jeff Bezos, John Meriwether, John von Neumann, junk bonds, locking in a profit, Long Term Capital Management, managed futures, margin call, Market Wizards by Jack D. Schwager, money market fund, Myron Scholes, paper trading, passive investing, pattern recognition, proprietary trading, random walk, risk free rate, risk tolerance, risk-adjusted returns, short selling, short squeeze, Silicon Valley, statistical arbitrage, Teledyne, the scientific method, transaction costs, Y2K

A large, irregular-polygon-shaped, brushed aluminum table, which served as a desk on one end and a conference area on the other, dominated the center of the room. We sat directly across from each other at the conference end. THE Q U A N T I T A T I V E EDGE traditional von Neumann machine, named after John von Neumann, has a single central processing unit (CPU) connected to a single memory unit. Originally, the two were well matched in speed and size. Over time, however, as processors became faster and memories got larger, the connection between the two—the time it takes for the CPU to get things out of memory, perform the computations, and place the results back into memory—became more and more of a bottleneck.


When Computers Can Think: The Artificial Intelligence Singularity by Anthony Berglas, William Black, Samantha Thalind, Max Scratchmann, Michelle Estes

3D printing, Abraham Maslow, AI winter, air gap, anthropic principle, artificial general intelligence, Asilomar, augmented reality, Automated Insights, autonomous vehicles, availability heuristic, backpropagation, blue-collar work, Boston Dynamics, brain emulation, call centre, cognitive bias, combinatorial explosion, computer vision, Computing Machinery and Intelligence, create, read, update, delete, cuban missile crisis, David Attenborough, DeepMind, disinformation, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Ernest Rutherford, factory automation, feminist movement, finite state, Flynn Effect, friendly AI, general-purpose programming language, Google Glasses, Google X / Alphabet X, Gödel, Escher, Bach, Hans Moravec, industrial robot, Isaac Newton, job automation, John von Neumann, Law of Accelerating Returns, license plate recognition, Mahatma Gandhi, mandelbrot fractal, natural language processing, Nick Bostrom, Parkinson's law, patent troll, patient HM, pattern recognition, phenotype, ransomware, Ray Kurzweil, Recombinant DNA, self-driving car, semantic web, Silicon Valley, Singularitarianism, Skype, sorting algorithm, speech recognition, statistical model, stem cell, Stephen Hawking, Stuxnet, superintelligent machines, technological singularity, Thomas Malthus, Turing machine, Turing test, uranium enrichment, Von Neumann architecture, Watson beat the top human players on Jeopardy!, wikimedia commons, zero day

Like perceptrons, it is possible to feed some of the outputs of a PLA back into some of the inputs buffered by flip-flops that store state. If that is done then they can in principle implement any general purpose computer program. Von Neumann Architecture Owned Modern computers use an architecture that was first proposed by John von Neumann in 1945, which is illustrated above. It has a memory that is organized as a series of words, each of which can contain a small number. Each word also has an address which can be used to access it. The memory provides random access, meaning that words can be efficiently accessed in a random order so there is no need to access them sequentially.


pages: 481 words: 125,946

What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence by John Brockman

Adam Curtis, agricultural Revolution, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Anthropocene, artificial general intelligence, augmented reality, autism spectrum disorder, autonomous vehicles, backpropagation, basic income, behavioural economics, bitcoin, blockchain, bread and circuses, Charles Babbage, clean water, cognitive dissonance, Colonization of Mars, complexity theory, computer age, computer vision, constrained optimization, corporate personhood, cosmological principle, cryptocurrency, cuban missile crisis, Danny Hillis, dark matter, data science, deep learning, DeepMind, Demis Hassabis, digital capitalism, digital divide, digital rights, discrete time, Douglas Engelbart, driverless car, Elon Musk, Emanuel Derman, endowment effect, epigenetics, Ernest Rutherford, experimental economics, financial engineering, Flash crash, friendly AI, functional fixedness, global pandemic, Google Glasses, Great Leap Forward, Hans Moravec, hive mind, Ian Bogost, income inequality, information trail, Internet of things, invention of writing, iterative process, James Webb Space Telescope, Jaron Lanier, job automation, Johannes Kepler, John Markoff, John von Neumann, Kevin Kelly, knowledge worker, Large Hadron Collider, lolcat, loose coupling, machine translation, microbiome, mirror neurons, Moneyball by Michael Lewis explains big data, Mustafa Suleyman, natural language processing, Network effects, Nick Bostrom, Norbert Wiener, paperclip maximiser, pattern recognition, Peter Singer: altruism, phenotype, planetary scale, Ray Kurzweil, Recombinant DNA, recommendation engine, Republic of Letters, RFID, Richard Thaler, Rory Sutherland, Satyajit Das, Search for Extraterrestrial Intelligence, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, social intelligence, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, superintelligent machines, supervolcano, synthetic biology, systems thinking, tacit knowledge, TED Talk, the scientific method, The Wisdom of Crowds, theory of mind, Thorstein Veblen, too big to fail, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!, We are as Gods, Y2K

McKinsey predicts that these technologies will create more than $50 trillion of economic value by 2025. If this is accurate, we should expect dramatically increased investment soon. The recent successes are being driven by cheap computer power and plentiful training data. Modern AI is based on the theory of “rational agents,” arising from work on microeconomics in the 1940s by John von Neumann and others. AI systems can be thought of as trying to approximate rational behavior using limited resources. There’s an algorithm for computing the optimal action for achieving a desired outcome, but it’s computationally expensive. Experiments have found that simple learning algorithms with lots of training data often outperform complex hand-crafted models.


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Capital Ideas: The Improbable Origins of Modern Wall Street by Peter L. Bernstein

Albert Einstein, asset allocation, backtesting, Benoit Mandelbrot, Black Monday: stock market crash in 1987, Black-Scholes formula, Bonfire of the Vanities, Brownian motion, business cycle, buy and hold, buy low sell high, capital asset pricing model, corporate raider, debt deflation, diversified portfolio, Eugene Fama: efficient market hypothesis, financial innovation, financial intermediation, fixed income, full employment, Glass-Steagall Act, Great Leap Forward, guns versus butter model, implied volatility, index arbitrage, index fund, interest rate swap, invisible hand, John von Neumann, Joseph Schumpeter, junk bonds, Kenneth Arrow, law of one price, linear programming, Louis Bachelier, mandelbrot fractal, martingale, means of production, Michael Milken, money market fund, Myron Scholes, new economy, New Journalism, Paul Samuelson, Performance of Mutual Funds in the Period, profit maximization, Ralph Nader, RAND corporation, random walk, Richard Thaler, risk free rate, risk/return, Robert Shiller, Robert Solow, Ronald Reagan, stochastic process, Thales and the olive presses, the market place, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, transfer pricing, zero-coupon bond, zero-sum game

As Roy put it, “A man who seeks advice about his actions will not be grateful for the suggestion that he maximize his expected utility.”19 The complexity of the subject has attracted the attention of some of the best thinkers of our time, including Kenneth Arrow, a Nobel Prize-winner, and Oskar Morgenstern and John von Neumann, famous for having invented game theory. But this is not the only feature of the Markowitz paradigm with controversial implications. The calculation of the Efficient Frontier is a task that would defy the abilities and capabilities of many investors, and even the capacities of many computers. so it is fair to ask whether the relationship between risk and return is as neat as Markowitz postulates.


pages: 394 words: 118,929

Dreaming in Code: Two Dozen Programmers, Three Years, 4,732 Bugs, and One Quest for Transcendent Software by Scott Rosenberg

A Pattern Language, AOL-Time Warner, Benevolent Dictator For Life (BDFL), Berlin Wall, Bill Atkinson, c2.com, call centre, collaborative editing, Computer Lib, conceptual framework, continuous integration, Do you want to sell sugared water for the rest of your life?, Donald Knuth, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dynabook, en.wikipedia.org, Firefox, Ford Model T, Ford paid five dollars a day, Francis Fukuyama: the end of history, Free Software Foundation, functional programming, General Magic , George Santayana, Grace Hopper, Guido van Rossum, Gödel, Escher, Bach, Howard Rheingold, HyperCard, index card, intentional community, Internet Archive, inventory management, Ivan Sutherland, Jaron Lanier, John Markoff, John Perry Barlow, John von Neumann, knowledge worker, L Peter Deutsch, Larry Wall, life extension, Loma Prieta earthquake, machine readable, Menlo Park, Merlin Mann, Mitch Kapor, Neal Stephenson, new economy, Nicholas Carr, no silver bullet, Norbert Wiener, pattern recognition, Paul Graham, Potemkin village, RAND corporation, Ray Kurzweil, Richard Stallman, Ronald Reagan, Ruby on Rails, scientific management, semantic web, side project, Silicon Valley, Singularitarianism, slashdot, software studies, source of truth, South of Market, San Francisco, speech recognition, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Stewart Brand, Strategic Defense Initiative, Ted Nelson, the Cathedral and the Bazaar, Therac-25, thinkpad, Turing test, VA Linux, Vannevar Bush, Vernor Vinge, Wayback Machine, web application, Whole Earth Catalog, Y2K

Yet other central figures in the development of modern software share his complaint that the software profession has taken a fundamental wrong turn. As early as 1978, John Backus, the father of Fortran, was expressing parallel views. Programming, Backus argued, had grown out of the ideas of John von Neumann, the mathematician who, at the dawn of computing in the 1940s, devised the basic structure of the “stored program” of sequentially executed instructions. But those ideas had become a straitjacket. “Von Neumann languages constantly keep our noses pressed in the dirt of address computation and the separate computation of single words,” he wrote.


pages: 452 words: 126,310

The Case for Space: How the Revolution in Spaceflight Opens Up a Future of Limitless Possibility by Robert Zubrin

Ada Lovelace, Albert Einstein, anthropic principle, Apollo 11, battle of ideas, Boeing 747, Charles Babbage, Charles Lindbergh, Colonization of Mars, complexity theory, cosmic microwave background, cosmological principle, Dennis Tito, discovery of DNA, double helix, Elon Musk, en.wikipedia.org, flex fuel, Francis Fukuyama: the end of history, gravity well, if you build it, they will come, Internet Archive, invisible hand, ITER tokamak, James Webb Space Telescope, Jeff Bezos, Johannes Kepler, John von Neumann, Kim Stanley Robinson, Kuiper Belt, low earth orbit, Mars Rover, Mars Society, Menlo Park, more computing power than Apollo, Naomi Klein, nuclear winter, ocean acidification, off grid, out of africa, Peter H. Diamandis: Planetary Resources, Peter Thiel, place-making, Pluto: dwarf planet, private spaceflight, Recombinant DNA, rising living standards, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, SoftBank, SpaceX Starlink, Strategic Defense Initiative, Stuart Kauffman, telerobotics, Thomas Malthus, three-masted sailing ship, time dilation, transcontinental railway, uranium enrichment, Virgin Galactic, Wayback Machine

This will make them expensive, as space labor will be dear and transportation from Earth will be costly. Expensive robots are acceptable for assisting in certain tasks, such as exploration, where large numbers are not required. But terraforming will need multitudes. The only solution would be robots that make themselves. Back in the 1940s, the mathematician John Von Neumann proved that self-replicating automatons are possible. That is, he proved that there is no mathematical contradiction that precludes the existence of such systems. But creating them is another issue altogether. No one today has a clue as to how to do it, but it would not be too big a leap of faith to believe that a machine could be built and programmed that, if let loose in a room filled with gears, wires, wheels, batteries, computer chips, and all its other component parts, could assemble a copy of itself.


pages: 401 words: 119,488

Smarter Faster Better: The Secrets of Being Productive in Life and Business by Charles Duhigg

Air France Flight 447, Asperger Syndrome, Atul Gawande, behavioural economics, Black Swan, cognitive dissonance, Daniel Kahneman / Amos Tversky, data science, David Brooks, digital map, epigenetics, Erik Brynjolfsson, framing effect, high-speed rail, hiring and firing, index card, John von Neumann, knowledge worker, Lean Startup, Malcom McLean invented shipping containers, meta-analysis, new economy, power law, Saturday Night Live, Silicon Valley, Silicon Valley startup, statistical model, Steve Jobs, the scientific method, the strength of weak ties, theory of mind, Toyota Production System, William Langewiesche, Yom Kippur War

., Numerical Methods in Finance: Bordeaux, June 2010, Springer Proceedings in Mathematics, vol. 12 (Berlin: Springer Berlin Heidelberg, 2012); René Carmona et al., “An Introduction to Particle Methods with Financial Application,” in Numerical Methods in Finance, 3–49; Pierre Del Moral, Mean Field Simulation for Monte Carlo Integration (Boca Raton, Fla.: CRC Press, 2013); Roger Eckhardt, “Stan Ulam, John von Neumann, and the Monte Carlo Method,” Los Alamos Science, special issue (1987): 131–37. in the shape of a hat Andrew Hargadon and Robert I. Sutton, “Technology Brokering and Innovation in a Product Development Firm,” Administrative Science Quarterly 42, no. 4 (1997): 716–49; Roger P. Brown, “Polymers in Sport and Leisure,” Rapra Review Reports 12, no. 3 (November 2, 2001); Melissa Larson, “From Bombers to Bikes,” Quality 37, no. 9 (1998): 30.


Why Things Bite Back: Technology and the Revenge of Unintended Consequences by Edward Tenner

air freight, Alfred Russel Wallace, animal electricity, blue-collar work, Charles Babbage, clean water, collective bargaining, computer age, dematerialisation, Donald Knuth, Edward Jenner, Exxon Valdez, gentrification, germ theory of disease, Herman Kahn, informal economy, job automation, John Harrison: Longitude, John von Neumann, Lewis Mumford, Loma Prieta earthquake, loose coupling, Louis Pasteur, machine translation, mass immigration, Menlo Park, nuclear winter, oil shock, placebo effect, planned obsolescence, Productivity paradox, Ralph Waldo Emerson, rising living standards, Robert X Cringely, safety bicycle, scientific management, Shoshana Zuboff, Silicon Valley, sugar pill, systems thinking, technoutopianism, The Soul of a New Machine, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, Triangle Shirtwaist Factory

In the 195os, American notables helped celebrate the twenty-fifth anniversary of Fortune magazineby painting the year 198o in tones that rivaled the most radiant forecasts of the Soviet Politburo. David Sarnoff of RCA predicted: "Small atomic generators, installed in homes and industrial plants, will provide power for years and ultimately for a lifetime without recharging." John von Neumann of the Institute for Advanced Study and the Atomic Energy Commission speculated that energy might even "be free—just like the unmetered air." Henry R. Luce himself foresaw the global stewardship of consciousness by "High Organization" as represented by the multinational American corporation, bureaucracies, and labor unions.


pages: 453 words: 122,586

Samuelson Friedman: The Battle Over the Free Market by Nicholas Wapshott

2021 United States Capitol attack, Alan Greenspan, bank run, basic income, battle of ideas, Bear Stearns, Berlin Wall, Bretton Woods, business cycle, California gold rush, collective bargaining, coronavirus, corporate governance, COVID-19, creative destruction, David Ricardo: comparative advantage, Donald Trump, double helix, en.wikipedia.org, fiat currency, financial engineering, fixed income, floating exchange rates, full employment, God and Mammon, greed is good, Gunnar Myrdal, income inequality, indoor plumbing, invisible hand, John von Neumann, Joseph Schumpeter, Kenneth Arrow, laissez-faire capitalism, light touch regulation, liquidity trap, lockdown, low interest rates, Machinery of Freedom by David Friedman, market bubble, market clearing, mass immigration, military-industrial complex, Money creation, money market fund, Mont Pelerin Society, moral hazard, new economy, Nixon shock, Nixon triggered the end of the Bretton Woods system, paradox of thrift, Paul Samuelson, Philip Mirowski, Phillips curve, price mechanism, price stability, public intellectual, pushing on a string, quantitative easing, rent control, road to serfdom, Robert Bork, Robert Solow, Ronald Coase, Ronald Reagan, school vouchers, seminal paper, Simon Kuznets, social distancing, Tax Reform Act of 1986, The Chicago School, The Great Moderation, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Thorstein Veblen, too big to fail, trickle-down economics, universal basic income, upwardly mobile, urban renewal, War on Poverty, We are all Keynesians now, Works Progress Administration, zero-sum game

Silber, Volcker: The Triumph of Persistence (Bloomsbury Press, New York, 2012), pp. 145–46. 11.New York Times, July 29, 1979, p. F1. 12.Silber, Volcker, p. 148. 13.Personal Letters from 1979, Papers of Paul Volcker. Federal Reserve Bank of New York Archives, Box 95714. 14.Ibid. 15.Oskar Morgenstern (January 24, 1902–July 26, 1977), Princeton economist, who with mathematician John von Neumann founded the mathematical field of game theory and its application to economics. 16.Friedrich August Lutz (December 29, 1901–October 4, 1975), German-born Princeton economist who developed the expectations hypothesis. 17.Paul Volcker, “The Problems of Federal Reserve Policy since World War II,” Princeton, 1949. https://catalog.princeton.edu/catalog/dsp019019s3255. 18.Minutes of Federal Open Market Committee Meeting, August 14, 1979, p. 1. 19.Denis Winston Healey, Lord Healey (August 30, 1917–October 3, 2015), British Labour Party Secretary of State for Defence, 1964–1970; chancellor of the exchequer, 1974–1979; and deputy leader of the Labour Party, 1980–1983. 20.Healey, The Time of My Life, p. 432. 21.Ibid. 22.Presidential address to the American Economic Association and the American Finance Association, Atlantic City, N.J., September 16, 1976. https://www.newyorkfed.org/medialibrary/media/research/quarterly_review/75th/75article7.pdf. 23.Ibid. 24.Paul Volcker, “The Role of Monetary Targets in an Age of Inflation,” Journal of Monetary Economics 4, no. 2, April 1978. 25.Ibid., p. 331. 26.In particular the events in the spring and summer of 1977, when inflation leapt from 5 to 7 percent. 27.Paul Volcker and Toyoo Gyohten, Changing Fortunes: The World’s Money and the Threat to American Leadership (Times Books, New York, 1992), pp. 164–65. 28.New York Times, September 19, 1979, p. 1. 29.Volcker and Gyohten, Changing Fortunes, p. 165. 30.Paul A.


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The God Delusion by Richard Dawkins

Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, Ayatollah Khomeini, Bletchley Park, Boeing 747, Brownian motion, cosmological principle, David Attenborough, Desert Island Discs, double helix, en.wikipedia.org, experimental subject, Fellow of the Royal Society, gravity well, Gregor Mendel, invisible hand, John von Neumann, Jon Ronson, luminiferous ether, Menlo Park, meta-analysis, Murray Gell-Mann, Necker cube, Peter Singer: altruism, phenotype, placebo effect, planetary scale, Ralph Waldo Emerson, Richard Feynman, Schrödinger's Cat, scientific worldview, Search for Extraterrestrial Intelligence, stem cell, Stephen Hawking, Steven Pinker, the scientific method, theory of mind, Thorstein Veblen, trickle-down economics, unbiased observer

The ‘crime’ itself being a private act, performed by consenting adults who were doing nobody else any harm, we again have here the classic hallmark of religious absolutism. My own country has no right to be smug. Private homosexuality was a criminal offence in Britain up until – astonishingly – 1967. In 1954 the British mathematician Alan Turing, a candidate along with John von Neumann for the title of father of the computer, committed suicide after being convicted of the criminal offence of homosexual behaviour in private. Admittedly Turing was not buried alive under a wall pushed over by a tank. He was offered a choice between two years in prison (you can imagine how the other prisoners would have treated him) and a course of hormone injections which could be said to amount to chemical castration, and would have caused him to grow breasts.


pages: 474 words: 130,575

Surveillance Valley: The Rise of the Military-Digital Complex by Yasha Levine

23andMe, activist fund / activist shareholder / activist investor, Adam Curtis, Airbnb, AltaVista, Amazon Web Services, Anne Wojcicki, anti-communist, AOL-Time Warner, Apple's 1984 Super Bowl advert, bitcoin, Black Lives Matter, borderless world, Boston Dynamics, British Empire, Californian Ideology, call centre, Charles Babbage, Chelsea Manning, cloud computing, collaborative editing, colonial rule, company town, computer age, computerized markets, corporate governance, crowdsourcing, cryptocurrency, data science, digital map, disinformation, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dr. Strangelove, drone strike, dual-use technology, Edward Snowden, El Camino Real, Electric Kool-Aid Acid Test, Elon Musk, end-to-end encryption, fake news, fault tolerance, gentrification, George Gilder, ghettoisation, global village, Google Chrome, Google Earth, Google Hangouts, Greyball, Hacker Conference 1984, Howard Zinn, hypertext link, IBM and the Holocaust, index card, Jacob Appelbaum, Jeff Bezos, jimmy wales, John Gilmore, John Markoff, John Perry Barlow, John von Neumann, Julian Assange, Kevin Kelly, Kickstarter, Laura Poitras, life extension, Lyft, machine readable, Mark Zuckerberg, market bubble, Menlo Park, military-industrial complex, Mitch Kapor, natural language processing, Neal Stephenson, Network effects, new economy, Norbert Wiener, off-the-grid, One Laptop per Child (OLPC), packet switching, PageRank, Paul Buchheit, peer-to-peer, Peter Thiel, Philip Mirowski, plutocrats, private military company, RAND corporation, Ronald Reagan, Ross Ulbricht, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley startup, Skype, slashdot, Snapchat, Snow Crash, SoftBank, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Susan Wojcicki, Telecommunications Act of 1996, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Hackers Conference, Tony Fadell, uber lyft, vertical integration, Whole Earth Catalog, Whole Earth Review, WikiLeaks

The paper essentially described a modern multipurpose computer, complete with a display, keyboard, speech recognition software, networking capabilities, and applications that could be used in real time for a variety of tasks.27 It seems obvious to us now, but back then Lick’s ideas were visionary. His paper was widely circulated in defense circles and earned him an invitation by the Pentagon to do a series of lectures on the topic.28 “My first experience with computers had been listening to a talk by [mathematician John] von Neumann in Chicago back in nineteen forty-eight. It sounded like science fiction then: a machine that could carry out algorithms automatically,” recalled Charles Herzfeld, a physicist who would go on to serve as the director of ARPA in the mid-1960s.29 “But the next big shock was Lick: not only could we use these machines for massive calculations, but we could make them useful in our everyday lives.


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The Net Delusion: The Dark Side of Internet Freedom by Evgeny Morozov

"World Economic Forum" Davos, A Declaration of the Independence of Cyberspace, Alvin Toffler, Ayatollah Khomeini, Berlin Wall, borderless world, Buckminster Fuller, Californian Ideology, Cass Sunstein, citizen journalism, cloud computing, cognitive dissonance, Columbine, computer age, conceptual framework, crowdsourcing, digital divide, disinformation, Dissolution of the Soviet Union, don't be evil, Evgeny Morozov, failed state, Fall of the Berlin Wall, Francis Fukuyama: the end of history, global village, Google Earth, Herbert Marcuse, illegal immigration, invention of radio, invention of the printing press, invisible hand, John Markoff, John Perry Barlow, John von Neumann, lolcat, Marshall McLuhan, Mitch Kapor, Naomi Klein, Network effects, new economy, New Urbanism, off-the-grid, Panopticon Jeremy Bentham, peer-to-peer, pirate software, pre–internet, Productivity paradox, public intellectual, RAND corporation, Robert Solow, Ronald Reagan, Ronald Reagan: Tear down this wall, Silicon Valley, Silicon Valley startup, Sinatra Doctrine, Skype, Slavoj Žižek, social graph, Steve Jobs, Streisand effect, technological determinism, technoutopianism, TED Talk, The Wisdom of Crowds, urban planning, Washington Consensus, WikiLeaks, women in the workforce

Name a problem that has to deal with information, and Google is already on top of it. Why the Ultimate Technological Fix Is Online It’s not all Google’s fault. There is something about the Internet and its do-it-yourself ethos that invites an endless production of quick fixes, bringing to mind the mathematician John von Neumann’s insightful observation that “technological possibilities are irresistible to man. If man can go to the moon, he will. If he can control the climate, he will” (even though on that last point, von Neumann may have been a bit off ). With the Internet, it seems, everything is irresistible, if only because everything is within easy grasp.


How I Became a Quant: Insights From 25 of Wall Street's Elite by Richard R. Lindsey, Barry Schachter

Albert Einstein, algorithmic trading, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, asset allocation, asset-backed security, backtesting, bank run, banking crisis, Bear Stearns, Black-Scholes formula, Bob Litterman, Bonfire of the Vanities, book value, Bretton Woods, Brownian motion, business cycle, business process, butter production in bangladesh, buy and hold, buy low sell high, capital asset pricing model, centre right, collateralized debt obligation, commoditize, computerized markets, corporate governance, correlation coefficient, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency risk, discounted cash flows, disintermediation, diversification, Donald Knuth, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, financial engineering, financial innovation, fixed income, full employment, George Akerlof, global macro, Gordon Gekko, hiring and firing, implied volatility, index fund, interest rate derivative, interest rate swap, Ivan Sutherland, John Bogle, John von Neumann, junk bonds, linear programming, Loma Prieta earthquake, Long Term Capital Management, machine readable, margin call, market friction, market microstructure, martingale, merger arbitrage, Michael Milken, Myron Scholes, Nick Leeson, P = NP, pattern recognition, Paul Samuelson, pensions crisis, performance metric, prediction markets, profit maximization, proprietary trading, purchasing power parity, quantitative trading / quantitative finance, QWERTY keyboard, RAND corporation, random walk, Ray Kurzweil, Reminiscences of a Stock Operator, Richard Feynman, Richard Stallman, risk free rate, risk-adjusted returns, risk/return, seminal paper, shareholder value, Sharpe ratio, short selling, Silicon Valley, six sigma, sorting algorithm, statistical arbitrage, statistical model, stem cell, Steven Levy, stochastic process, subscription business, systematic trading, technology bubble, The Great Moderation, the scientific method, too big to fail, trade route, transaction costs, transfer pricing, value at risk, volatility smile, Wiener process, yield curve, young professional

As I said, the math core offerings were nothing new, so I looked around. Then came another fortuitous break: my discoveries of game theory and of my eventual thesis advisor, William F. Lucas. This guy is a math legend, though unlike most, as humble a man as you will ever meet. What made him a legend was an elegant counter example to John von Neumann’s and Oskar Morganstern’s conjecture that all cooperative N-person games have solutions according to their self-proclaimed definition of such. Until that time, cooperative game theory was thought uninteresting with no open issues. However, once Lucas proved the case was not closed, the whole subject blossomed with theories of solution concepts, some of which have proved extremely valuable in applications such as voting analysis and fair division.


pages: 436 words: 76

Culture and Prosperity: The Truth About Markets - Why Some Nations Are Rich but Most Remain Poor by John Kay

Alan Greenspan, Albert Einstein, Asian financial crisis, Barry Marshall: ulcers, behavioural economics, Berlin Wall, Big bang: deregulation of the City of London, Bletchley Park, business cycle, California gold rush, Charles Babbage, complexity theory, computer age, constrained optimization, corporate governance, corporate social responsibility, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, Donald Trump, double entry bookkeeping, double helix, Dr. Strangelove, Dutch auction, Edward Lloyd's coffeehouse, electricity market, equity premium, equity risk premium, Ernest Rutherford, European colonialism, experimental economics, Exxon Valdez, failed state, Fairchild Semiconductor, financial innovation, flying shuttle, Ford Model T, Francis Fukuyama: the end of history, George Akerlof, George Gilder, Goodhart's law, Great Leap Forward, greed is good, Gunnar Myrdal, haute couture, Helicobacter pylori, illegal immigration, income inequality, industrial cluster, information asymmetry, intangible asset, invention of the telephone, invention of the wheel, invisible hand, John Meriwether, John Nash: game theory, John von Neumann, junk bonds, Kenneth Arrow, Kevin Kelly, knowledge economy, Larry Ellison, light touch regulation, Long Term Capital Management, loss aversion, Mahatma Gandhi, market bubble, market clearing, market fundamentalism, means of production, Menlo Park, Michael Milken, Mikhail Gorbachev, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, Naomi Klein, Nash equilibrium, new economy, oil shale / tar sands, oil shock, Pareto efficiency, Paul Samuelson, pets.com, Phillips curve, popular electronics, price discrimination, price mechanism, prisoner's dilemma, profit maximization, proprietary trading, purchasing power parity, QWERTY keyboard, Ralph Nader, RAND corporation, random walk, rent-seeking, Right to Buy, risk tolerance, road to serfdom, Robert Solow, Ronald Coase, Ronald Reagan, Savings and loan crisis, second-price auction, shareholder value, Silicon Valley, Simon Kuznets, South Sea Bubble, Steve Jobs, Stuart Kauffman, telemarketer, The Chicago School, The Market for Lemons, The Nature of the Firm, the new new thing, The Predators' Ball, The Wealth of Nations by Adam Smith, Thorstein Veblen, total factor productivity, transaction costs, tulip mania, urban decay, Vilfredo Pareto, Washington Consensus, women in the workforce, work culture , yield curve, yield management

Behavioral economics contemplates alternative assumptions about motives and the nature of economic behavior. I will introduce game theory and institutional economics in the present chapter and take up behavioral economics in the chapter that follows. Economic Theory After Arrow and Debreu eeeeeeeee&ee&oeeeeeeoeeeoeeoeeooeeeoe In 1944,John von Neumann and Oskar Morgenstern published The Theory ofGames and Economic Behavior. This approach was, after an interval, to revolutionize economic theory. The analysis of competitive markets supposes anonymous interactions among many buyers and many sellers. The fragmentation and impersonality of these markets leads to incentive compatibility-there is no need to consider the behavior and responses of other market participants.


pages: 525 words: 131,496

Near and Distant Neighbors: A New History of Soviet Intelligence by Jonathan Haslam

active measures, Albert Einstein, Benoit Mandelbrot, Berlin Wall, Bletchley Park, Bolshevik threat, Bretton Woods, British Empire, cuban missile crisis, disinformation, falling living standards, false flag, John von Neumann, lateral thinking, military-industrial complex, Robert Hanssen: Double agent, Ronald Reagan, Strategic Defense Initiative, Valery Gerasimov, Vladimir Vetrov: Farewell Dossier, éminence grise

Finally, all Moscow’s communications with the outside world were suddenly severed. For Washington, this was Black Friday: October 29, 1948. When signals resumed on Monday, nothing could be deciphered. Computer Catch-Up At the Institute for Advanced Study the publication in 1946 by the Hungarian-born mathematician John von Neumann of a seminal article on the construction of the computer and the appearance of the first American civilian computer, ENIAC, that same year served to warn the Russians that the United States was moving into more innovative computation. This was despite the fact that it was a symbolic rather than a genuine threat, since the machine was digital with an outside program driven slowly, step by step, with only a single memory.


pages: 505 words: 138,917

Open: The Story of Human Progress by Johan Norberg

Abraham Maslow, additive manufacturing, affirmative action, Albert Einstein, anti-globalists, basic income, Berlin Wall, Bernie Sanders, Bletchley Park, Brexit referendum, British Empire, business cycle, business process, California gold rush, carbon tax, citizen journalism, classic study, Clayton Christensen, clean water, cognitive dissonance, collective bargaining, Corn Laws, coronavirus, COVID-19, creative destruction, crony capitalism, decarbonisation, deindustrialization, Deng Xiaoping, digital map, Donald Trump, Edward Jenner, fake news, Fall of the Berlin Wall, falling living standards, Filter Bubble, financial innovation, flying shuttle, Flynn Effect, Francis Fukuyama: the end of history, future of work, Galaxy Zoo, George Gilder, Gini coefficient, global pandemic, global supply chain, global village, green new deal, humanitarian revolution, illegal immigration, income per capita, Indoor air pollution, indoor plumbing, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Islamic Golden Age, James Watt: steam engine, Jane Jacobs, Jeff Bezos, job automation, John von Neumann, joint-stock company, Joseph Schumpeter, Kickstarter, knowledge economy, labour mobility, Lao Tzu, liberal capitalism, manufacturing employment, mass immigration, negative emissions, Network effects, open borders, open economy, Pax Mongolica, place-making, profit motive, RAND corporation, regulatory arbitrage, rent control, Republic of Letters, road to serfdom, Ronald Reagan, Schrödinger's Cat, sharing economy, side project, Silicon Valley, Solyndra, spice trade, stem cell, Steve Bannon, Steve Jobs, Steve Wozniak, Steven Pinker, tacit knowledge, The Death and Life of Great American Cities, The Wealth of Nations by Adam Smith, Thomas L Friedman, too big to fail, trade liberalization, trade route, transatlantic slave trade, Tyler Cowen, Uber for X, ultimatum game, universal basic income, World Values Survey, Xiaogang Anhui farmers, zero-sum game

One of Haber’s prominent colleagues pleaded to Hitler to spare Haber and told him that these purges would set Germany back a hundred years in physics and chemistry. Hitler retorted: ‘If Jews are so important to physics and chemistry, then we’ll just have to work one hundred years without physics and chemistry.’45 The list of thinkers who escaped Hitler reads like a Who’s Who of the scientific world: Fritz Haber, Albert Einstein, John von Neumann, Niels Bohr, Edward Teller, Erwin Schrödinger, and many more. Most of them escaped to the US, which was safe and far away. ‘It was the most significant influx of ability of which there is any record,’ wrote the novelist and chemist C. P. Snow. ‘The refugees made [the US], in a very short time, the world’s dominant force in pure science.’46 It was an incalculable loss to Germany, not least in terms of military capability.


pages: 530 words: 145,220

The Search for Life on Mars by Elizabeth Howell

affirmative action, Alfred Russel Wallace, Apollo 11, British Empire, dark matter, double helix, fake news, financial independence, follow your passion, Ford Model T, glass ceiling, Google Earth, independent contractor, invention of the telescope, James Webb Space Telescope, John von Neumann, Louis Pasteur, Mars Rover, Menlo Park, Neil Armstrong, New Journalism, Pluto: dwarf planet, Ronald Reagan, Skype

Chapter 4: The Road to Utopia 86 visitors from Mars: So claimed one who knew von Kármán and his fellow Hungarians, the German physicist Otto Frisch. They were a “galaxy of brilliant Hungarian expatriates,” as he termed them, whose number included Edward Teller, Leo Szilard, Eugene Wigner, and John von Neumann. All made fundamental contributions to modern science, not least in the years before and during World War II. 90 Deep Space Network: Originally, one of the “southern hemisphere” dishes was located in South Africa, but growing concerns over the apartheid regime in the 1960s meant that it was abandoned in favor of the Spanish station outside of Madrid. 91 exobiologists: The term exobiology was coined by Nobel laureate Joshua Lederberg, who was involved in the Viking missions.


pages: 570 words: 151,609

Into the Black: The Extraordinary Untold Story of the First Flight of the Space Shuttle Columbia and the Astronauts Who Flew Her by Rowland White, Richard Truly

Albert Einstein, Apollo 11, Apollo 13, Apollo Guidance Computer, Ayatollah Khomeini, Berlin Wall, Boeing 747, Charles Lindbergh, cuban missile crisis, Easter island, Fall of the Berlin Wall, Gene Kranz, Isaac Newton, it's over 9,000, John von Neumann, low earth orbit, Maui Hawaii, Mercator projection, Neil Armstrong, orbital mechanics / astrodynamics, Ronald Reagan, Strategic Defense Initiative, William Langewiesche

As with Hans Mark, Morgenstern was resident in the United States as a consequence of Hitler’s annexation of Austria in 1938. A professor of economics at the University of Vienna, Morgenstern was visiting Princeton when the Nazis seized Vienna. He remained at the American university, where he met the Hungarian-born mathematical genius John von Neumann. A prodigy who as a child could memorize and recite the phone book, von Neumann had earned his PhD in mathematics at just twenty-two. Still in his twenties, he took up, alongside Albert Einstein, one of five professorships at Princeton’s Institute for Advanced Study. Von Neumann’s polymathic brilliance ranged from quantum mechanics to the hydrogen bomb.


pages: 497 words: 144,283

Connectography: Mapping the Future of Global Civilization by Parag Khanna

"World Economic Forum" Davos, 1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 9 dash line, additive manufacturing, Admiral Zheng, affirmative action, agricultural Revolution, Airbnb, Albert Einstein, amateurs talk tactics, professionals talk logistics, Amazon Mechanical Turk, Anthropocene, Asian financial crisis, asset allocation, autonomous vehicles, banking crisis, Basel III, Berlin Wall, bitcoin, Black Swan, blockchain, borderless world, Boycotts of Israel, Branko Milanovic, BRICs, British Empire, business intelligence, call centre, capital controls, Carl Icahn, charter city, circular economy, clean water, cloud computing, collateralized debt obligation, commoditize, complexity theory, continuation of politics by other means, corporate governance, corporate social responsibility, credit crunch, crony capitalism, crowdsourcing, cryptocurrency, cuban missile crisis, data is the new oil, David Ricardo: comparative advantage, deglobalization, deindustrialization, dematerialisation, Deng Xiaoping, Detroit bankruptcy, digital capitalism, digital divide, digital map, disruptive innovation, diversification, Doha Development Round, driverless car, Easter island, edge city, Edward Snowden, Elon Musk, energy security, Ethereum, ethereum blockchain, European colonialism, eurozone crisis, export processing zone, failed state, Fairphone, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, forward guidance, gentrification, geopolitical risk, global supply chain, global value chain, global village, Google Earth, Great Leap Forward, Hernando de Soto, high net worth, high-speed rail, Hyperloop, ice-free Arctic, if you build it, they will come, illegal immigration, income inequality, income per capita, industrial cluster, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, LNG terminal, low cost airline, low earth orbit, low interest rates, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, middle-income trap, mittelstand, Monroe Doctrine, Multics, mutually assured destruction, Neal Stephenson, New Economic Geography, new economy, New Urbanism, off grid, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Parag Khanna, Peace of Westphalia, peak oil, Pearl River Delta, Peter Thiel, Philip Mirowski, Planet Labs, plutocrats, post-oil, post-Panamax, precautionary principle, private military company, purchasing power parity, quantum entanglement, Quicken Loans, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Solow, rolling blackouts, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, six sigma, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, Stuxnet, supply-chain management, sustainable-tourism, systems thinking, TaskRabbit, tech worker, TED Talk, telepresence, the built environment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, Tim Cook: Apple, trade route, Tragedy of the Commons, transaction costs, Tyler Cowen, UNCLOS, uranium enrichment, urban planning, urban sprawl, vertical integration, WikiLeaks, Yochai Benkler, young professional, zero day

As Guangzhou has graduated from factory town to financial center, its glittering central business district features the aerodynamic 103-story-tall IFC tower, modern art museums one would expect to find in Zurich, and an opera house designed by Zaha Hadid. Just outside the city, the Singapore-run Knowledge City and Guangzhou Science City were built to resemble a low-rise version of Silicon Valley, with leafy boulevards that feature bronze statues of Albert Einstein and the mathematician John von Neumann. Singapore has opened a branch of its elite Chinese-language Hwa Chong Institution while also partnering with the local government to develop new curricula for the South China University of Technology, which already graduates some of the country’s top entrepreneurs establishing companies in digital industries such as cloud computing and GPS navigation, materials engineering, renewable energy, biotechnology, and pharmaceuticals.


pages: 497 words: 146,551

Lila: An Inquiry Into Morals by Robert M. Pirsig

Albert Einstein, Buckminster Fuller, feminist movement, gentrification, index card, John von Neumann, luminiferous ether, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, trade route

With more than ten-thousand trees that kept wanting to expand to one-hundred thousand, the PROGRAM slips were absolutely necessary to keep from getting lost. What made them so powerful was that they too were on slips, one slip for each instruction. This meant the PROGRAM slips were random access too and could be changed and resequenced as the need arose without any difficulty. He remembered reading that John Von Neumann, an inventor of the computer, had said the single thing that makes a computer so powerful is that the program is data and can be treated like any other data. That seemed a little obscure when Phædrus had read it but now it was making sense. The next slips were the GRIT slips. These were for days when he woke up in a foul mood and could find nothing but fault everywhere.


pages: 696 words: 143,736

The Age of Spiritual Machines: When Computers Exceed Human Intelligence by Ray Kurzweil

Ada Lovelace, Alan Greenspan, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Alvin Toffler, Any sufficiently advanced technology is indistinguishable from magic, backpropagation, Buckminster Fuller, call centre, cellular automata, Charles Babbage, classic study, combinatorial explosion, complexity theory, computer age, computer vision, Computing Machinery and Intelligence, cosmological constant, cosmological principle, Danny Hillis, double helix, Douglas Hofstadter, Everything should be made as simple as possible, financial engineering, first square of the chessboard / second half of the chessboard, flying shuttle, fudge factor, functional programming, George Gilder, Gödel, Escher, Bach, Hans Moravec, I think there is a world market for maybe five computers, information retrieval, invention of movable type, Isaac Newton, iterative process, Jacquard loom, John Gilmore, John Markoff, John von Neumann, Lao Tzu, Law of Accelerating Returns, mandelbrot fractal, Marshall McLuhan, Menlo Park, natural language processing, Norbert Wiener, optical character recognition, ought to be enough for anybody, pattern recognition, phenotype, punch-card reader, quantum entanglement, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Robert Metcalfe, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, social intelligence, speech recognition, Steven Pinker, Stewart Brand, stochastic process, Stuart Kauffman, technological singularity, Ted Kaczynski, telepresence, the medium is the message, The Soul of a New Machine, There's no reason for any individual to have a computer in his home - Ken Olsen, traveling salesman, Turing machine, Turing test, Whole Earth Review, world market for maybe five computers, Y2K

—IBM Chairman Thomas Watson, 1943 “Computers in the future may weigh no more than 1.5 tons.” —Popular Mechanics, 1949 “It would appear that we have reached the limits of what is possible to achieve with computer technology, although one should be careful with such statements, as they tend to sound pretty silly in five years.” —John von Neumann, 1949 “There’s no reason for individuals to have a computer in their home.” —Ken Olson, 1977 “640,000 bytes of memory ought to be enough for anybody.” —Bill Gates, 1981 “Long before the year 2000, the entire antiquated structure of college degrees, majors and credits will be a shambles.”


pages: 541 words: 146,445

Spin by Robert Charles Wilson

airport security, Colonization of Mars, Great Leap Forward, invention of writing, invisible hand, John von Neumann, lateral thinking, Mahatma Gandhi, megacity, oil shale / tar sands, rolodex, Stephen Hawking, synthetic biology

Given the inherent difficulty of sublight-speed travel as a way of exploring the galaxy, most technological cultures eventually settle for an expanding grid of von Neumann machines—which is what the replicators are—that costs nothing to maintain and generates a trickle of scientific information that expands exponentially over historical time." "Okay," I said, "I understand that. The Martian replicators aren't unique. They ran into what you call an ecology—" "A von Neumann ecology." (After the twentieth-century mathematician John von Neumann, who first suggested the possibility of self-reproducing machines.) "A von Neumann ecology, and they were absorbed by it. But that doesn't tell us anything about the Hypotheticals or the Spin." Jason pursed his lips impatiently. "Tyler, no. You don't understand. The Hypotheticals are the von Neumann ecology.


pages: 470 words: 144,455

Secrets and Lies: Digital Security in a Networked World by Bruce Schneier

Ayatollah Khomeini, barriers to entry, Bletchley Park, business process, butterfly effect, cashless society, Columbine, defense in depth, double entry bookkeeping, drop ship, fault tolerance, game design, IFF: identification friend or foe, information security, John Gilmore, John von Neumann, knapsack problem, macro virus, Mary Meeker, MITM: man-in-the-middle, moral panic, Morris worm, Multics, multilevel marketing, mutually assured destruction, PalmPilot, pez dispenser, pirate software, profit motive, Richard Feynman, risk tolerance, Russell Brand, Silicon Valley, Simon Singh, slashdot, statistical model, Steve Ballmer, Steven Levy, systems thinking, the payments system, Timothy McVeigh, Y2K, Yogi Berra

Almost every computer security system that uses cryptography needs random numbers—for keys, unique values in protocols, and so on—and the security of those systems is often dependent on the randomness of those random numbers. If the random number generator is insecure, the entire system breaks. Depending on who you talk to, generating random numbers from a computer is either trivial or impossible. Theoretically, it’s impossible. John von Neumann, the father of computers, said: “Anyone who considers arithmetic methods of producing random digits is, of course, in a state of sin.” What he means is that it is impossible to get something truly random out of a deterministic beast like a computer. This is true, but luckily we can get by anyway.


pages: 573 words: 157,767

From Bacteria to Bach and Back: The Evolution of Minds by Daniel C. Dennett

Ada Lovelace, adjacent possible, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, AlphaGo, Andrew Wiles, Bayesian statistics, bioinformatics, bitcoin, Bletchley Park, Build a better mousetrap, Claude Shannon: information theory, computer age, computer vision, Computing Machinery and Intelligence, CRISPR, deep learning, disinformation, double entry bookkeeping, double helix, Douglas Hofstadter, Elon Musk, epigenetics, experimental subject, Fermat's Last Theorem, Gödel, Escher, Bach, Higgs boson, information asymmetry, information retrieval, invention of writing, Isaac Newton, iterative process, John von Neumann, language acquisition, megaproject, Menlo Park, Murray Gell-Mann, Necker cube, Norbert Wiener, pattern recognition, phenotype, Richard Feynman, Rodney Brooks, self-driving car, social intelligence, sorting algorithm, speech recognition, Stephen Hawking, Steven Pinker, strong AI, Stuart Kauffman, TED Talk, The Wealth of Nations by Adam Smith, theory of mind, Thomas Bayes, trickle-down economics, Turing machine, Turing test, Watson beat the top human players on Jeopardy!, Y2K

Before turning to some of the specialized ways brains are designed to extract semantic information, it is time to address the issue of how dramatically brains differ from the computers that have flooded our world. Control tasks formerly performed by human brains have recently been usurped by computers, which have taken charge of many things, from elevators to airplanes to oil refineries. Turing’s theoretical idea, made operational by John von Neumann’s implementation, the serial stored program computer, has multiplied exponentially in the last sixty years and now occupies every environment on Earth and has sent thousands, perhaps millions, of descendants into space; the most traveled brainchildren in history. The brilliant idealizations of Shannon, Turing, von Neumann, McCulloch, and Pitts have led to such an explosion in information-handling competence that today it is commonly supposed not only that brains are just organic digital computers of one sort or another but that also silicon-based computers will soon embody Artificial Intelligence that will surpass human brains in “all the achievements of creative skill” (to echo Beverley’s outraged charge that Darwin thought that “Absolute Ignorance” could do the same trick).


pages: 492 words: 149,259

Big Bang by Simon Singh

Albert Einstein, Albert Michelson, All science is either physics or stamp collecting, Andrew Wiles, anthropic principle, Arthur Eddington, Astronomia nova, Bletchley Park, Boeing 747, Brownian motion, carbon-based life, Cepheid variable, Chance favours the prepared mind, Charles Babbage, Commentariolus, Copley Medal, cosmic abundance, cosmic microwave background, cosmological constant, cosmological principle, dark matter, Dava Sobel, Defenestration of Prague, discovery of penicillin, Dmitri Mendeleev, Eddington experiment, Edmond Halley, Edward Charles Pickering, Eratosthenes, Ernest Rutherford, Erwin Freundlich, Fellow of the Royal Society, Ford Model T, fudge factor, Hans Lippershey, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, heat death of the universe, Henri Poincaré, horn antenna, if you see hoof prints, think horses—not zebras, Index librorum prohibitorum, information security, invention of the telescope, Isaac Newton, Johannes Kepler, John von Neumann, Karl Jansky, Kickstarter, Louis Daguerre, Louis Pasteur, luminiferous ether, Magellanic Cloud, Murray Gell-Mann, music of the spheres, Olbers’ paradox, On the Revolutions of the Heavenly Spheres, Paul Erdős, retrograde motion, Richard Feynman, scientific mainstream, Simon Singh, Stephen Hawking, Strategic Defense Initiative, the scientific method, Thomas Kuhn: the structure of scientific revolutions, time dilation, unbiased observer, Wilhelm Olbers, William of Occam

THOMAS HENRY HUXLEY (1825-95), English biologist The sciences do not try to explain, they hardly even try to interpret, they mainly make models. By a model is meant a mathematical construct which, with the addition of certain verbal interpretations, describes observed phenomena. The justification of such a mathematical construct is solely and precisely that it is expected to work. JOHN VON NEUMANN (1903-57), Hungarian-born mathematician The science of today is the technology of tomorrow. EDWARD TELLER (1908-2003), American physicist Every great advance in science has issued from a new audacity of imagination. JOHN DEWEY (1859-1952), American philosopher Four stages of acceptance: i) this is worthless nonsense, ii) this is an interesting, but perverse, point of view, iii) this is true, but quite unimportant, iv) I always said so.


pages: 543 words: 153,550

Model Thinker: What You Need to Know to Make Data Work for You by Scott E. Page

Airbnb, Albert Einstein, Alfred Russel Wallace, algorithmic trading, Alvin Roth, assortative mating, behavioural economics, Bernie Madoff, bitcoin, Black Swan, blockchain, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Checklist Manifesto, computer age, corporate governance, correlation does not imply causation, cuban missile crisis, data science, deep learning, deliberate practice, discrete time, distributed ledger, Easter island, en.wikipedia.org, Estimating the Reproducibility of Psychological Science, Everything should be made as simple as possible, experimental economics, first-price auction, Flash crash, Ford Model T, Geoffrey West, Santa Fe Institute, germ theory of disease, Gini coefficient, Higgs boson, High speed trading, impulse control, income inequality, Isaac Newton, John von Neumann, Kenneth Rogoff, knowledge economy, knowledge worker, Long Term Capital Management, loss aversion, low skilled workers, Mark Zuckerberg, market design, meta-analysis, money market fund, multi-armed bandit, Nash equilibrium, natural language processing, Network effects, opioid epidemic / opioid crisis, p-value, Pareto efficiency, pattern recognition, Paul Erdős, Paul Samuelson, phenotype, Phillips curve, power law, pre–internet, prisoner's dilemma, race to the bottom, random walk, randomized controlled trial, Richard Feynman, Richard Thaler, Robert Solow, school choice, scientific management, sealed-bid auction, second-price auction, selection bias, six sigma, social graph, spectrum auction, statistical model, Stephen Hawking, Supply of New York City Cabdrivers, systems thinking, tacit knowledge, The Bell Curve by Richard Herrnstein and Charles Murray, The Great Moderation, the long tail, The Rise and Fall of American Growth, the rule of 72, the scientific method, The Spirit Level, the strength of weak ties, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, Tragedy of the Commons, urban sprawl, value at risk, web application, winner-take-all economy, zero-sum game

The figure shows three trees: Tree 1: If (age < 30) and (internet hours per week in [15, 25]) Tree 2: If (age in [20, 45]) and (internet hours per week > 30) Tree 3: If (age > 40) and (internet hours per week < 20) Figure M3: A Forest of Decision Trees Classifying Conference Attendees The collection of trees are called a forest. Machine learning algorithms create trees randomly on a training set and then keep those that classify accurately on the testing set and on a training set. 8. Concavity and Convexity To say nonlinear science is akin to saying non-elephant zoology. —John von Neumann We now introduce nonlinear models and nonlinear functions. Nonlinear functions can curve downward or upward, they can form S-shapes, they can kink, jump, and squiggle. In time, we cover all of these possibilities. We start here with models that rely on convexity and concavity. We show how growth and positive feedbacks produce convexity and how diminishing returns and negative feedbacks produce concavity.


The Art of Computer Programming: Sorting and Searching by Donald Ervin Knuth

card file, Charles Babbage, Claude Shannon: information theory, complexity theory, correlation coefficient, Donald Knuth, double entry bookkeeping, Eratosthenes, Fermat's Last Theorem, G4S, information retrieval, iterative process, John von Neumann, linked data, locality of reference, Menlo Park, Norbert Wiener, NP-complete, p-value, Paul Erdős, RAND corporation, refrigerator car, sorting algorithm, Vilfredo Pareto, Yogi Berra, Zipf's Law

If we want to speed up the insertion process we can consider inserting several elements at a time, "batching" them, and this leads naturally to the general idea of merge sorting. From a historical point of view, merge sorting was one of the very first methods proposed for computer sorting; it was suggested by John von Neumann as early as 1945 (see Section 5.5). We shall study merging in considerable detail in Section 5.4, with regard to external sorting algorithms; our main concern in the present section is the somewhat simpler question of merge sorting within a high-speed random-access memory. Table 1 shows a merge sort that "burns the candle at both ends" in a manner similar to the scanning procedure we have used in quicksort and radix exchange: We examine the input from the left and from the right, working towards the 160 SORTING 5.2.4 middle.

The designers of EDVAC were especially interested in sorting, because it epitomized the potential nonnumerical applications of computers; they realized that a satisfactory order code should not only be capable of expressing programs for the solution of differ- difference equations, it must also have enough flexibility to handle the combinatorial "decision-making" aspects of algorithms. John von Neumann therefore prepared programs for internal merge sorting in 1945, in order to test the adequacy of some instruction codes he was proposing for the EDVAC computer. The existence of efficient special-purpose sorting machines provided a natural standard by which the merits of his proposed computer organization could be evaluated.


pages: 551 words: 174,280

The Beginning of Infinity: Explanations That Transform the World by David Deutsch

agricultural Revolution, Albert Michelson, anthropic principle, Apollo 13, artificial general intelligence, Bonfire of the Vanities, Charles Babbage, Computing Machinery and Intelligence, conceptual framework, cosmological principle, dark matter, David Attenborough, discovery of DNA, Douglas Hofstadter, Easter island, Eratosthenes, Ernest Rutherford, first-past-the-post, Georg Cantor, global pandemic, Gödel, Escher, Bach, illegal immigration, invention of movable type, Isaac Newton, Islamic Golden Age, Jacquard loom, Johannes Kepler, John Conway, John von Neumann, Joseph-Marie Jacquard, Kenneth Arrow, Loebner Prize, Louis Pasteur, mirror neurons, Nick Bostrom, pattern recognition, Pierre-Simon Laplace, precautionary principle, Richard Feynman, Search for Extraterrestrial Intelligence, seminal paper, Stephen Hawking, supervolcano, technological singularity, Thales of Miletus, The Coming Technological Singularity, the scientific method, Thomas Malthus, Thorstein Veblen, Turing test, Vernor Vinge, Whole Earth Review, William of Occam, zero-sum game

As a matter of fact, there is no such thing as mathematical ‘inspiration’ (mathematical knowledge coming from an infallible source, traditionally God): as I explained in Chapter 8, our knowledge of mathematics is not infallible. But if Representative Mills meant that mathematicians are, or somehow ought to be, society’s best judges of fairness, then he was simply mistaken.* The National Academy of Sciences panel that reported to Congress in 1948 included the mathematician and physicist John von Neumann. It decided that a rule invented by the statistician Joseph Adna Hill (which is the one in use today) is the most impartial between states. But the mathematicians Michel Balinski and Peyton Young have since concluded that it favours smaller states. This illustrates again that different criteria of ‘impartiality’ favour different apportionment rules, and which of them is the right criterion cannot be determined by mathematics.


pages: 1,331 words: 163,200

Hands-On Machine Learning With Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron

AlphaGo, Amazon Mechanical Turk, Anton Chekhov, backpropagation, combinatorial explosion, computer vision, constrained optimization, correlation coefficient, crowdsourcing, data science, deep learning, DeepMind, don't repeat yourself, duck typing, Elon Musk, en.wikipedia.org, friendly AI, Geoffrey Hinton, ImageNet competition, information retrieval, iterative process, John von Neumann, Kickstarter, machine translation, natural language processing, Netflix Prize, NP-complete, OpenAI, optical character recognition, P = NP, p-value, pattern recognition, pull request, recommendation engine, self-driving car, sentiment analysis, SpamAssassin, speech recognition, stochastic process

Since AdaGrad, RMSProp, and Adam optimization automatically reduce the learning rate during training, it is not necessary to add an extra learning schedule. For other optimization algorithms, using exponential decay or performance scheduling can considerably speed up convergence. Avoiding Overfitting Through Regularization With four parameters I can fit an elephant and with five I can make him wiggle his trunk. John von Neumann, cited by Enrico Fermi in Nature 427 Deep neural networks typically have tens of thousands of parameters, sometimes even millions. With so many parameters, the network has an incredible amount of freedom and can fit a huge variety of complex datasets. But this great flexibility also means that it is prone to overfitting the training set.


pages: 522 words: 162,310

Fantasyland: How America Went Haywire: A 500-Year History by Kurt Andersen

affirmative action, Alan Greenspan, Albert Einstein, animal electricity, anti-communist, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, back-to-the-land, Bernie Sanders, British Empire, Burning Man, California gold rush, Celebration, Florida, centre right, cognitive dissonance, Columbine, corporate governance, cotton gin, Credit Default Swap, David Brooks, delayed gratification, dematerialisation, disinformation, disintermediation, disruptive innovation, Donald Trump, Donner party, Downton Abbey, Easter island, Edward Snowden, Electric Kool-Aid Acid Test, failed state, fake news, Ferguson, Missouri, God and Mammon, Gordon Gekko, greed is good, Herman Kahn, high net worth, illegal immigration, invisible hand, Isaac Newton, John von Neumann, Kickstarter, large denomination, Mark Zuckerberg, market fundamentalism, McMansion, Mikhail Gorbachev, military-industrial complex, Minecraft, moral panic, mutually assured destruction, new economy, New Urbanism, Norman Mailer, off-the-grid, Oklahoma City bombing, placebo effect, post-truth, pre–internet, prosperity theology / prosperity gospel / gospel of success, Ralph Waldo Emerson, RAND corporation, reality distortion field, Ronald Reagan, Silicon Valley, smart meter, Snapchat, South Sea Bubble, Steve Jobs, sugar pill, Ted Kaczynski, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Timothy McVeigh, trade route, transcontinental railway, urban renewal, We are all Keynesians now, Whole Earth Catalog, WikiLeaks, Y2K, young professional

In the early 1960s, a mania for a certain kind of hyperrationalist abstraction had U.S. leaders in its thrall. It came along at just the right moment, as the Cold War and then the Vietnam War reached their horrific peaks, to help give reason itself a permanent taint in the American mind. The mathematician John von Neumann, a father of both the digital and the nuclear ages, left Germany for the United States just before the Nazis took power. As a young man, he created game theory, the distillation of human decision making to its underlying, purely mathematical essentials. He helped to create the atomic bomb and to choose the Japanese cities to be incinerated, work about which he seemed blithe and unchastened.


After Apollo?: Richard Nixon and the American Space Program by John M. Logsdon

Apollo 11, Apollo 13, Boeing 747, general purpose technology, John von Neumann, low earth orbit, Neil Armstrong, RAND corporation, Ronald Reagan, Teledyne

It had little credibility when it was submitted to the new Office of Management and Budget (OMB) in August 1970. NASA selected Mathematica, Inc. of Princeton, NJ to lead an independent study of shuttle economics. Mathematica had been founded by prestigious economist Oskar Morgenstern of the Institute for Advanced Studies; there he had worked with mathematician John von Neumann to develop game theory, an approach to analyzing situations in which actors with conflicting interests pursue independent courses of action. Morgenstern had founded Mathematica to pursue practical applications of this approach. At 190 A f t e r A p o l l o? Mathematica, a young Austrian-born economist named Klaus Heiss was put in charge of the space shuttle study.


pages: 741 words: 164,057

Editing Humanity: The CRISPR Revolution and the New Era of Genome Editing by Kevin Davies

23andMe, Airbnb, Anne Wojcicki, Apple's 1984 Super Bowl advert, Asilomar, bioinformatics, California gold rush, clean water, coronavirus, COVID-19, CRISPR, crowdsourcing, discovery of DNA, disinformation, Doomsday Clock, double helix, Downton Abbey, Drosophila, Edward Jenner, Elon Musk, epigenetics, fake news, Gregor Mendel, Hacker News, high-speed rail, hype cycle, imposter syndrome, Isaac Newton, John von Neumann, Kickstarter, life extension, Mark Zuckerberg, microbiome, Mikhail Gorbachev, mouse model, Neil Armstrong, New Journalism, ocean acidification, off-the-grid, personalized medicine, Peter Thiel, phenotype, QWERTY keyboard, radical life extension, RAND corporation, Recombinant DNA, rolodex, scientific mainstream, Scientific racism, seminal paper, Shenzhen was a fishing village, side project, Silicon Valley, Silicon Valley billionaire, Skype, social distancing, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, synthetic biology, TED Talk, the long tail, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, traumatic brain injury, warehouse automation

He was formerly an advisor to BGI’s controversial Cognitive Genomics project, since aborted. Now he believes he can apply AI to the prediction of complex polygenic traits including cognitive ability. Once, when asked to give his view of a superior human intelligence, Hsu offered as an example John von Neumann, the 20th-century polymath, developer of game theory, and computer science, who was capable of total recall and a photographic memory. “In my opinion,” Hsu says, “genotypes exist that correspond to phenotypes as far beyond von Neumann as he was beyond a normal human.” Hsu cofounded a PGT clinic called Genomic Prediction, located in an unremarkable office park off the New Jersey Turnpike, a short drive from Manhattan.


pages: 602 words: 177,874

Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations by Thomas L. Friedman

3D printing, additive manufacturing, affirmative action, Airbnb, AltaVista, Amazon Web Services, Anthropocene, Apple Newton, autonomous vehicles, Ayatollah Khomeini, barriers to entry, Berlin Wall, Bernie Sanders, Big Tech, biodiversity loss, bitcoin, blockchain, Bob Noyce, business cycle, business process, call centre, carbon tax, centre right, Chris Wanstrath, Clayton Christensen, clean tech, clean water, cloud computing, cognitive load, corporate social responsibility, creative destruction, CRISPR, crowdsourcing, data science, David Brooks, deep learning, demand response, demographic dividend, demographic transition, Deng Xiaoping, digital divide, disinformation, Donald Trump, dual-use technology, end-to-end encryption, Erik Brynjolfsson, fail fast, failed state, Fairchild Semiconductor, Fall of the Berlin Wall, Ferguson, Missouri, first square of the chessboard / second half of the chessboard, Flash crash, fulfillment center, game design, gig economy, global pandemic, global supply chain, Great Leap Forward, illegal immigration, immigration reform, income inequality, indoor plumbing, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the steam engine, inventory management, Irwin Jacobs: Qualcomm, Jeff Bezos, job automation, John Markoff, John von Neumann, Khan Academy, Kickstarter, knowledge economy, knowledge worker, land tenure, linear programming, Live Aid, low interest rates, low skilled workers, Lyft, Marc Andreessen, Mark Zuckerberg, mass immigration, Maui Hawaii, Menlo Park, Mikhail Gorbachev, mutually assured destruction, Neil Armstrong, Nelson Mandela, ocean acidification, PalmPilot, pattern recognition, planetary scale, power law, pull request, Ralph Waldo Emerson, ransomware, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Reagan, Salesforce, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, Solyndra, South China Sea, Steve Jobs, subscription business, supercomputer in your pocket, synthetic biology, systems thinking, TaskRabbit, tech worker, TED Talk, The Rise and Fall of American Growth, Thomas L Friedman, Tony Fadell, transaction costs, Transnistria, uber lyft, undersea cable, urban decay, urban planning, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y2K, Yogi Berra, zero-sum game

Norm Ornstein Dear Tom, It is an oddity often remarked upon that at the turn of the century, one small, obscure provincial area of Hungary, then under the benign tutelage of Emperor Franz Josef, spawned several towering figures in the fields of physics and mathematics—among them Edward Teller, George de Hevesy, Eugene Wigner, Leo Szilard and John von Neumann. This group, many of them Nobel Prize winners, all of them products of the Jewish middle class, were referred to in their diaspora as the “Men from Mars” because of their obscure provenance and their thick Finno-Ugaric accents. What explosive tinder in this remote corner of the Carpathians had nourished such a forest fire of genius?


pages: 586 words: 186,548

Architects of Intelligence by Martin Ford

3D printing, agricultural Revolution, AI winter, algorithmic bias, Alignment Problem, AlphaGo, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, barriers to entry, basic income, Baxter: Rethink Robotics, Bayesian statistics, Big Tech, bitcoin, Boeing 747, Boston Dynamics, business intelligence, business process, call centre, Cambridge Analytica, cloud computing, cognitive bias, Colonization of Mars, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, CRISPR, crowdsourcing, DARPA: Urban Challenge, data science, deep learning, DeepMind, Demis Hassabis, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, driverless car, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, fake news, Fellow of the Royal Society, Flash crash, future of work, general purpose technology, Geoffrey Hinton, gig economy, Google X / Alphabet X, Gödel, Escher, Bach, Hans Moravec, Hans Rosling, hype cycle, ImageNet competition, income inequality, industrial research laboratory, industrial robot, information retrieval, job automation, John von Neumann, Large Hadron Collider, Law of Accelerating Returns, life extension, Loebner Prize, machine translation, Mark Zuckerberg, Mars Rover, means of production, Mitch Kapor, Mustafa Suleyman, natural language processing, new economy, Nick Bostrom, OpenAI, opioid epidemic / opioid crisis, optical character recognition, paperclip maximiser, pattern recognition, phenotype, Productivity paradox, radical life extension, Ray Kurzweil, recommendation engine, Robert Gordon, Rodney Brooks, Sam Altman, self-driving car, seminal paper, sensor fusion, sentiment analysis, Silicon Valley, smart cities, social intelligence, sparse data, speech recognition, statistical model, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, synthetic biology, systems thinking, Ted Kaczynski, TED Talk, The Rise and Fall of American Growth, theory of mind, Thomas Bayes, Travis Kalanick, Turing test, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, women in the workforce, working-age population, workplace surveillance , zero-sum game, Zipcar

These two paradigms were completely different, they aimed to try and solve different problems, and they used completely different methods and different kinds of mathematics. Back then, it wasn’t at all clear which was going to be the winning paradigm. It’s still not clear to some people today. What was interesting, was that some of the people most associated with logic actually believed in the neural net paradigm. The biggest examples are John von Neumann and Alan Turing, who both thought that big networks of simulated neurons were a good way to study intelligence and figure out how those things work. However, the dominant approach in AI was symbol processing inspired by logic. In logic, you take symbol strings and alter them to arrive at new symbol strings, and people thought that must be how reasoning works.


pages: 654 words: 191,864

Thinking, Fast and Slow by Daniel Kahneman

Albert Einstein, Atul Gawande, availability heuristic, Bayesian statistics, behavioural economics, Black Swan, book value, Cass Sunstein, Checklist Manifesto, choice architecture, classic study, cognitive bias, cognitive load, complexity theory, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, delayed gratification, demand response, endowment effect, experimental economics, experimental subject, Exxon Valdez, feminist movement, framing effect, hedonic treadmill, hindsight bias, index card, information asymmetry, job satisfaction, John Bogle, John von Neumann, Kenneth Arrow, libertarian paternalism, Linda problem, loss aversion, medical residency, mental accounting, meta-analysis, nudge unit, pattern recognition, Paul Samuelson, peak-end rule, precautionary principle, pre–internet, price anchoring, quantitative trading / quantitative finance, random walk, Richard Thaler, risk tolerance, Robert Metcalfe, Ronald Reagan, Shai Danziger, sunk-cost fallacy, Supply of New York City Cabdrivers, systematic bias, TED Talk, The Chicago School, The Wisdom of Crowds, Thomas Bayes, transaction costs, union organizing, Walter Mischel, Yom Kippur War

Consider this example: If you prefer an apple to a banana, then you also prefer a 10% chance to win an apple to a 10% chance to win a banana. The apple and the banana stand for any objects of choice (including gambles), and the 10% chance stands for any probability. The mathematician John von Neumann, one of the giant intellectual figures of the twentieth century, and the economist Oskar Morgenstern had derived their theory of rational choice between gambles from a few axioms. Economists adopted expected utility theory in a dual role: as a logic that prescribes how decisions should be made, and as a description of how Econs make choices.


pages: 894 words: 190,485

Write Great Code, Volume 1 by Randall Hyde

AltaVista, business process, Donald Knuth, John von Neumann, level 1 cache, locality of reference, machine readable, Von Neumann architecture, Y2K

Knowing about memory performance characteristics, data locality, and cache operation can help you design software that runs as fast as possible. Writing great code requires a strong knowledge of the computer’s architecture. 6.1 The Basic System Components The basic operational design of a computer system is called its architecture. John von Neumann, a pioneer in computer design, is given credit for the principal architecture in use today. For example, the 80x86 family uses the von Neumann architecture (VNA). A typical von Neumann system has three major components: the central processing unit (CPU), memory, and input/output (I/O), as shown in Figure 6-1.


pages: 562 words: 201,502

Elon Musk by Walter Isaacson

4chan, activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, AltaVista, Apollo 11, Apple II, Apple's 1984 Super Bowl advert, artificial general intelligence, autism spectrum disorder, autonomous vehicles, basic income, Big Tech, blockchain, Boston Dynamics, Burning Man, carbon footprint, ChatGPT, Chuck Templeton: OpenTable:, Clayton Christensen, clean tech, Colonization of Mars, computer vision, Computing Machinery and Intelligence, coronavirus, COVID-19, crowdsourcing, cryptocurrency, deep learning, DeepMind, Demis Hassabis, disinformation, Dogecoin, Donald Trump, Douglas Engelbart, drone strike, effective altruism, Elon Musk, estate planning, fail fast, fake news, game design, gigafactory, GPT-4, high-speed rail, hiring and firing, hive mind, Hyperloop, impulse control, industrial robot, information security, Jeff Bezos, Jeffrey Epstein, John Markoff, John von Neumann, Jony Ive, Kwajalein Atoll, lab leak, large language model, Larry Ellison, lockdown, low earth orbit, Marc Andreessen, Marc Benioff, Mars Society, Max Levchin, Michael Shellenberger, multiplanetary species, Neil Armstrong, Network effects, OpenAI, packet switching, Parler "social media", paypal mafia, peer-to-peer, Peter Thiel, QAnon, Ray Kurzweil, reality distortion field, remote working, rent control, risk tolerance, Rubik’s Cube, Salesforce, Sam Altman, Sam Bankman-Fried, San Francisco homelessness, Sand Hill Road, Saturday Night Live, self-driving car, seminal paper, short selling, Silicon Valley, Skype, SpaceX Starlink, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steve Wozniak, Steven Levy, Streisand effect, supply-chain management, tech bro, TED Talk, Tesla Model S, the payments system, Tim Cook: Apple, universal basic income, Vernor Vinge, vertical integration, Virgin Galactic, wikimedia commons, William MacAskill, work culture , Y Combinator

At some point, biological brainpower would be dwarfed by digital brainpower. In addition, new AI machine-learning systems could ingest information on their own and teach themselves how to generate outputs, even upgrade their own code and capabilities. The term “singularity” was used by the mathematician John von Neumann and the sci-fi writer Vernor Vinge to describe the moment when artificial intelligence could forge ahead on its own at an uncontrollable pace and leave us mere humans behind. “That could happen sooner than we expected,” Musk said in an ominous, flat tone. For a moment I was struck by the oddness of the scene.


pages: 767 words: 208,933

Liberalism at Large: The World According to the Economist by Alex Zevin

"there is no alternative" (TINA), activist fund / activist shareholder / activist investor, affirmative action, Alan Greenspan, anti-communist, Asian financial crisis, bank run, Berlin Wall, Big bang: deregulation of the City of London, Bretton Woods, British Empire, business climate, business cycle, capital controls, carbon tax, centre right, Chelsea Manning, collective bargaining, Columbine, Corn Laws, corporate governance, corporate social responsibility, creative destruction, credit crunch, David Ricardo: comparative advantage, debt deflation, desegregation, disinformation, disruptive innovation, do well by doing good, Donald Trump, driverless car, Edward Snowden, failed state, Fall of the Berlin Wall, financial deregulation, financial innovation, Francis Fukuyama: the end of history, full employment, Gini coefficient, Glass-Steagall Act, global supply chain, guns versus butter model, hiring and firing, imperial preference, income inequality, interest rate derivative, invisible hand, It's morning again in America, Jeremy Corbyn, John von Neumann, Joseph Schumpeter, Julian Assange, junk bonds, Khartoum Gordon, land reform, liberal capitalism, liberal world order, light touch regulation, Long Term Capital Management, low interest rates, market bubble, Martin Wolf, means of production, Michael Milken, Mikhail Gorbachev, Monroe Doctrine, Mont Pelerin Society, moral hazard, Naomi Klein, new economy, New Journalism, Nixon triggered the end of the Bretton Woods system, no-fly zone, Norman Macrae, Northern Rock, Occupy movement, Philip Mirowski, plutocrats, post-war consensus, price stability, quantitative easing, race to the bottom, railway mania, rent control, rent-seeking, road to serfdom, Ronald Reagan, Rosa Parks, Seymour Hersh, Snapchat, Socratic dialogue, Steve Bannon, subprime mortgage crisis, Suez canal 1869, Suez crisis 1956, The Wealth of Nations by Adam Smith, Thomas Malthus, too big to fail, trade liberalization, trade route, unbanked and underbanked, underbanked, unorthodox policies, upwardly mobile, War on Poverty, WikiLeaks, Winter of Discontent, Yom Kippur War, young professional

: A Study of the Expedient Pledge on Rents Included in the Conservative Election Manifesto in October, London 1959; Macrae, Sunshades in October: An Analysis of the Main Mistakes in British Economic Policy Since the Mid Nineteen-fifties, London 1963; Macrae, Homes for the People, London 1967; Macrae, The Neurotic Trillionaire; A Survey of Mr. Nixon’s America, New York 1970; Macrae, The 2025 Report: A Concise History of the Future, 1975–2025, New York 1984; Macrae, The Hobart Century, London 1984; Macrae, John von Neumann: The Scientific Genius Who Pioneered the Modern Computer, Game Theory, Nuclear Deterrence, and Much More, Providence, RI 1999. 45.‘The Unacknowledged Giant’, 17 June 2010. 46.‘The Risen Sun’, 27 May 1967; ‘Consider Japan’, 1 September 1962. 47.‘Consider Japan’, 1 September 1962. 48.‘The Risen Sun’, 27 May 1967. 49.


Engineering Security by Peter Gutmann

active measures, address space layout randomization, air gap, algorithmic trading, Amazon Web Services, Asperger Syndrome, bank run, barriers to entry, bitcoin, Brian Krebs, business process, call centre, card file, cloud computing, cognitive bias, cognitive dissonance, cognitive load, combinatorial explosion, Credit Default Swap, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Debian, domain-specific language, Donald Davies, Donald Knuth, double helix, Dr. Strangelove, Dunning–Kruger effect, en.wikipedia.org, endowment effect, false flag, fault tolerance, Firefox, fundamental attribution error, George Akerlof, glass ceiling, GnuPG, Google Chrome, Hacker News, information security, iterative process, Jacob Appelbaum, Jane Jacobs, Jeff Bezos, John Conway, John Gilmore, John Markoff, John von Neumann, Ken Thompson, Kickstarter, lake wobegon effect, Laplace demon, linear programming, litecoin, load shedding, MITM: man-in-the-middle, Multics, Network effects, nocebo, operational security, Paradox of Choice, Parkinson's law, pattern recognition, peer-to-peer, Pierre-Simon Laplace, place-making, post-materialism, QR code, quantum cryptography, race to the bottom, random walk, recommendation engine, RFID, risk tolerance, Robert Metcalfe, rolling blackouts, Ruby on Rails, Sapir-Whorf hypothesis, Satoshi Nakamoto, security theater, semantic web, seminal paper, Skype, slashdot, smart meter, social intelligence, speech recognition, SQL injection, statistical model, Steve Jobs, Steven Pinker, Stuxnet, sunk-cost fallacy, supply-chain attack, telemarketer, text mining, the built environment, The Death and Life of Great American Cities, The Market for Lemons, the payments system, Therac-25, too big to fail, Tragedy of the Commons, Turing complete, Turing machine, Turing test, Wayback Machine, web application, web of trust, x509 certificate, Y2K, zero day, Zimmermann PGP

The standard economic decisionmaking model, also known as the Bayesian decision-making model, assumes that someone making a decision will carefully take all relevant information into account in order to come up with an optimal decision [5]. As one observer put it, this model “took its marching orders from standard American economics, which assumes that people always know what they want and choose the optimal course of action for getting it” [6]. This model, called Utility Theory, goes back to at least 1944 and John von Neumann’s work on game theory [7], although some trace its origins (in somewhat distant forms) as far back as the early 1700s [8]. The formalisation of the economic decision-making model, Subjective Expected Utility Theory (SEU), makes the following assumptions about the decision-making process [9][10][11][12]: 1.

“Herding, social influence and economic decision-making: sociopsychological and neuroscientific analyses”, Michelle Baddeley, Philosophical Transactions of the Royal Society B (Biological Sciences), Vol.365, No.1538 (27 January 2010), p.281. “Decision making in complex systems”, Baruch Fischhoff, Proceedings of the NATO Advanced Study Institute on Intelligent Decision Support on Intelligent Decision Support in Process Environments, Springer-Verlag, 1986, p.61. “Theory of Games and Economic Behaviour”, John von Neumann and Oskar Morgenstern, Princeton University Press, 1944. “Emotion and Reason: The Cognitive Neuroscience of Decision Making”, Alain Berthoz, Oxford University Press, 2006. “Models of Man : Social and Rational”, Herbert Simon, John Wiley and Sons, 1957. “Reason in Human Affairs”, Herbert Simon, Stanford University Press, 1983.


pages: 1,737 words: 491,616

Rationality: From AI to Zombies by Eliezer Yudkowsky

Albert Einstein, Alfred Russel Wallace, anthropic principle, anti-pattern, anti-work, antiwork, Arthur Eddington, artificial general intelligence, availability heuristic, backpropagation, Bayesian statistics, behavioural economics, Berlin Wall, Boeing 747, Build a better mousetrap, Cass Sunstein, cellular automata, Charles Babbage, cognitive bias, cognitive dissonance, correlation does not imply causation, cosmological constant, creative destruction, Daniel Kahneman / Amos Tversky, dematerialisation, different worldview, discovery of DNA, disinformation, Douglas Hofstadter, Drosophila, Eddington experiment, effective altruism, experimental subject, Extropian, friendly AI, fundamental attribution error, Great Leap Forward, Gödel, Escher, Bach, Hacker News, hindsight bias, index card, index fund, Isaac Newton, John Conway, John von Neumann, Large Hadron Collider, Long Term Capital Management, Louis Pasteur, mental accounting, meta-analysis, mirror neurons, money market fund, Monty Hall problem, Nash equilibrium, Necker cube, Nick Bostrom, NP-complete, One Laptop per Child (OLPC), P = NP, paperclip maximiser, pattern recognition, Paul Graham, peak-end rule, Peter Thiel, Pierre-Simon Laplace, placebo effect, planetary scale, prediction markets, random walk, Ray Kurzweil, reversible computing, Richard Feynman, risk tolerance, Rubik’s Cube, Saturday Night Live, Schrödinger's Cat, scientific mainstream, scientific worldview, sensible shoes, Silicon Valley, Silicon Valley startup, Singularitarianism, SpaceShipOne, speech recognition, statistical model, Steve Jurvetson, Steven Pinker, strong AI, sunk-cost fallacy, technological singularity, The Bell Curve by Richard Herrnstein and Charles Murray, the map is not the territory, the scientific method, Turing complete, Turing machine, Tyler Cowen, ultimatum game, X Prize, Y Combinator, zero-sum game

Maybe before you pull the dualist fire alarm on human brains being physically special, you should provide experimental proof that a rock can’t play the same role in dispelling the Mysterious Phenomenon as a human researcher? But that’s hindsight, and it’s easy to call the shots in hindsight. Do you really think you could’ve done better than John von Neumann, if you’d been alive at the time? The point of this kind of retrospective analysis is to ask what kind of fully general clues you could have followed, and whether there are any similar clues you’re ignoring now on current mysteries. Though it is a little embarrassing that even after the theory of amplitudes and configurations had been worked out—with the theory now giving the definite prediction that any nudged particle would do the trick—early scientists still didn’t get it.

That’s like, like some kind of comedy routine where the guy opens a box, and it contains a spring-loaded pie, so the guy opens another box, and it contains another spring-loaded pie, and the guy just keeps doing this without even thinking of the possibility that the next box contains a pie too. You think John von Neumann, who may have been the highest-g human in history, wouldn’t think of it?” “That’s right,” Huve says, “He wouldn’t. Ponder that.” “This is the world where my good friend Ernest formulates his Schrödinger’s Cat thought experiment, and in this world, the thought experiment goes: ‘Hey, suppose we have a radioactive particle that enters a superposition of decaying and not decaying.


Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann

active measures, Amazon Web Services, billion-dollar mistake, bitcoin, blockchain, business intelligence, business logic, business process, c2.com, cloud computing, collaborative editing, commoditize, conceptual framework, cryptocurrency, data science, database schema, deep learning, DevOps, distributed ledger, Donald Knuth, Edward Snowden, end-to-end encryption, Ethereum, ethereum blockchain, exponential backoff, fake news, fault tolerance, finite state, Flash crash, Free Software Foundation, full text search, functional programming, general-purpose programming language, Hacker News, informal economy, information retrieval, Internet of things, iterative process, John von Neumann, Ken Thompson, Kubernetes, Large Hadron Collider, level 1 cache, loose coupling, machine readable, machine translation, Marc Andreessen, microservices, natural language processing, Network effects, no silver bullet, operational security, packet switching, peer-to-peer, performance metric, place-making, premature optimization, recommendation engine, Richard Feynman, self-driving car, semantic web, Shoshana Zuboff, social graph, social web, software as a service, software is eating the world, sorting algorithm, source of truth, SPARQL, speech recognition, SQL injection, statistical model, surveillance capitalism, systematic bias, systems thinking, Tragedy of the Commons, undersea cable, web application, WebSocket, wikimedia commons

.: “Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google’s Datacenter Network,” at Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM), August 2015. doi:10.1145/2785956.2787508 [10] Glenn K. Lockwood: “Hadoop’s Uncomfortable Fit in HPC,” glennklock‐ wood.blogspot.co.uk, May 16, 2014. 312 | Chapter 8: The Trouble with Distributed Systems [11] John von Neumann: “Probabilistic Logics and the Synthesis of Reliable Organ‐ isms from Unreliable Components,” in Automata Studies (AM-34), edited by Claude E. Shannon and John McCarthy, Princeton University Press, 1956. ISBN: 978-0-691-07916-5 [12] Richard W. Hamming: The Art of Doing Science and Engineering.


pages: 496 words: 174,084

Masterminds of Programming: Conversations With the Creators of Major Programming Languages by Federico Biancuzzi, Shane Warden

Benevolent Dictator For Life (BDFL), business intelligence, business logic, business process, cellular automata, cloud computing, cognitive load, commoditize, complexity theory, conceptual framework, continuous integration, data acquisition, Dennis Ritchie, domain-specific language, Douglas Hofstadter, Fellow of the Royal Society, finite state, Firefox, follow your passion, Frank Gehry, functional programming, general-purpose programming language, Guido van Rossum, higher-order functions, history of Unix, HyperCard, industrial research laboratory, information retrieval, information security, iterative process, Ivan Sutherland, John von Neumann, Ken Thompson, Larry Ellison, Larry Wall, linear programming, loose coupling, machine readable, machine translation, Mars Rover, millennium bug, Multics, NP-complete, Paul Graham, performance metric, Perl 6, QWERTY keyboard, RAND corporation, randomized controlled trial, Renaissance Technologies, Ruby on Rails, Sapir-Whorf hypothesis, seminal paper, Silicon Valley, slashdot, software as a service, software patent, sorting algorithm, SQL injection, Steve Jobs, traveling salesman, Turing complete, type inference, Valgrind, Von Neumann architecture, web application

He served as chair of the department from 1995 to 1997, and in the spring of 2003. Professor Aho has a B.A.Sc. in engineering physics from the University of Toronto and a Ph.D. in electrical engineering/computer science from Princeton University. Professor Aho won the Great Teacher Award for 2003 from the Society of Columbia Graduates. Professor Aho has won the IEEE John von Neumann Medal and is a Member of the U.S. National Academy of Engineering and the American Academy of Arts and Sciences. He received honorary doctorates from the Universities of Helsinki and Waterloo, and is a Fellow of the American Association for the Advancement of Science, the ACM, Bell Labs, and the IEEE.


pages: 1,237 words: 227,370

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann

active measures, Amazon Web Services, billion-dollar mistake, bitcoin, blockchain, business intelligence, business logic, business process, c2.com, cloud computing, collaborative editing, commoditize, conceptual framework, cryptocurrency, data science, database schema, deep learning, DevOps, distributed ledger, Donald Knuth, Edward Snowden, end-to-end encryption, Ethereum, ethereum blockchain, exponential backoff, fake news, fault tolerance, finite state, Flash crash, Free Software Foundation, full text search, functional programming, general-purpose programming language, Hacker News, informal economy, information retrieval, Infrastructure as a Service, Internet of things, iterative process, John von Neumann, Ken Thompson, Kubernetes, Large Hadron Collider, level 1 cache, loose coupling, machine readable, machine translation, Marc Andreessen, microservices, natural language processing, Network effects, no silver bullet, operational security, packet switching, peer-to-peer, performance metric, place-making, premature optimization, recommendation engine, Richard Feynman, self-driving car, semantic web, Shoshana Zuboff, social graph, social web, software as a service, software is eating the world, sorting algorithm, source of truth, SPARQL, speech recognition, SQL injection, statistical model, surveillance capitalism, systematic bias, systems thinking, Tragedy of the Commons, undersea cable, web application, WebSocket, wikimedia commons

.: “Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google’s Datacenter Network,” at Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM), August 2015. doi:10.1145/2785956.2787508 [10] Glenn K. Lockwood: “Hadoop’s Uncomfortable Fit in HPC,” glennklockwood.blogspot.co.uk, May 16, 2014. [11] John von Neumann: “Probabilistic Logics and the Synthesis of Reliable Organisms from Unreliable Components,” in Automata Studies (AM-34), edited by Claude E. Shannon and John McCarthy, Princeton University Press, 1956. ISBN: 978-0-691-07916-5 [12] Richard W. Hamming: The Art of Doing Science and Engineering.


God Created the Integers: The Mathematical Breakthroughs That Changed History by Stephen Hawking

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Antoine Gombaud: Chevalier de Méré, Augustin-Louis Cauchy, Bletchley Park, British Empire, Edmond Halley, Eratosthenes, Fellow of the Royal Society, G4S, Georg Cantor, Henri Poincaré, Isaac Newton, Johannes Kepler, John von Neumann, p-value, Pierre-Simon Laplace, Richard Feynman, seminal paper, Stephen Hawking, the long tail, three-masted sailing ship, tontine, Turing machine

It is hard to imagine the development of either electrodynamics or quantum theory without the methods of Jean Baptiste Joseph Fourier or the work on calculus and the theory of complex functions pioneered by Carl Friedrich Gauss and Augustin-Louis Cauchy—and it was Henri Lebesgue’s work on the theory of measure that enabled John von Neumann to formulate the rigorous understanding of quantum theory that we have today. Albert Einstein could not have completed his general theory of relativity had it not been for the geometric ideas of Bernhard Riemann. And practically all of modern science would be far less potent (if it existed at all) without the concepts of probability and statistics pioneered by Pierre Simon Laplace.

Students jokingly called it the “Ivory Tower,” not because of the often ethereal intellectual activity it over-looked, but because it overlooked “Procter Hall,” the graduate college’s chief public room, built with a donation from William Cooper Procter, a founder of the American company Procter & Gamble, the manufacturers of Ivory Soap! Within the confines of the mathematics department, Turing could pursue whatever he pleased. There was no need to conform. He felt at home in the department. Yet, in spite of John von Neumann’s offer to stay on at the Institute for Advanced Study as a research assistant, Turing decided to return to England after receiving his Ph.D. in 1938. He realized that America, in general, and Presbyterian Princeton, in particular, would not easily tolerate a nonconformist such as himself. In the summer of 1938, he returned to a Europe on the brink of war.


pages: 827 words: 239,762

The Golden Passport: Harvard Business School, the Limits of Capitalism, and the Moral Failure of the MBA Elite by Duff McDonald

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Albert Einstein, Apollo 13, barriers to entry, Bayesian statistics, Bear Stearns, Bernie Madoff, Bob Noyce, Bonfire of the Vanities, business cycle, business process, butterfly effect, capital asset pricing model, Capital in the Twenty-First Century by Thomas Piketty, Carl Icahn, Clayton Christensen, cloud computing, collateralized debt obligation, collective bargaining, commoditize, compensation consultant, corporate governance, corporate raider, corporate social responsibility, creative destruction, deskilling, discounted cash flows, disintermediation, disruptive innovation, Donald Trump, eat what you kill, Fairchild Semiconductor, family office, financial engineering, financial innovation, Frederick Winslow Taylor, full employment, George Gilder, glass ceiling, Glass-Steagall Act, global pandemic, Gordon Gekko, hiring and firing, Ida Tarbell, impact investing, income inequality, invisible hand, Jeff Bezos, job-hopping, John von Neumann, Joseph Schumpeter, junk bonds, Kenneth Arrow, Kickstarter, Kōnosuke Matsushita, London Whale, Long Term Capital Management, market fundamentalism, Menlo Park, Michael Milken, new economy, obamacare, oil shock, pattern recognition, performance metric, Pershing Square Capital Management, Peter Thiel, planned obsolescence, plutocrats, profit maximization, profit motive, pushing on a string, Ralph Nader, Ralph Waldo Emerson, RAND corporation, random walk, rent-seeking, Ronald Coase, Ronald Reagan, Sam Altman, Sand Hill Road, Saturday Night Live, scientific management, shareholder value, Sheryl Sandberg, Silicon Valley, Skype, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, Steve Jurvetson, survivorship bias, TED Talk, The Nature of the Firm, the scientific method, Thorstein Veblen, Tragedy of the Commons, union organizing, urban renewal, vertical integration, Vilfredo Pareto, War on Poverty, William Shockley: the traitorous eight, women in the workforce, Y Combinator

Born in Louisville, Kentucky, in 1866, Flexner had staked out permanent territory as an educational authority with the publication two decades earlier of the Flexner Report, which is credited with sparking the reform of medical education in the United States and Canada. He also cofounded (with Louis Bamberger) the Institute for Advanced Study at Princeton, with the immodest ambition of “[advancing] the frontiers of knowledge.”1 The institute, which later counted Albert Einstein and John Von Neumann among its faculty, has more than met that goal. Flexner was both a critic and an innovator—a man to be listened to, even if HBS didn’t like what he had to say. And they most certainly did not, starting with his conclusion that the rapid proliferation of professional schools within the university system—with the exception of medicine and law—was a threat to the university’s sacred purpose of the advancement of knowledge.2 And what society most certainly did not need, Flexner argued, was a graduate school of business at Harvard, which, ironically, the Rockefellers’ own GEB had helped bring into being.


pages: 1,117 words: 270,127

On Thermonuclear War by Herman Kahn

British Empire, business cycle, defense in depth, Ford Model T, Herman Kahn, John von Neumann, mutually assured destruction, New Journalism, oil shale / tar sands, Project Plowshare, RAND corporation, Suez crisis 1956, two and twenty, zero-sum game

This is an understatement of the things that are now technologically feasible but that "cost a little too much." I have not seen any figures, but I surmise that relatively thin margins of cost prevent us from doing such extraordinary projects as melting ice caps and diverting ocean currents. The coming crisis in technology was described by the late John von Neumann in an article entitled "Can We Survive Technology?" 8 To quote von Neumann: "'The great globe itself is in a rapidly maturing crisis—a crisis attributable to the fact that the environment in which technological progress must occur has become both undersized and underorganized. . . . "In the first half of this century the accelerating Industrial Revolution encountered an absolute limitation—not on technological progress as such, but on an essential safety factor.


pages: 1,261 words: 294,715

Behave: The Biology of Humans at Our Best and Worst by Robert M. Sapolsky

autism spectrum disorder, autonomous vehicles, behavioural economics, Bernie Madoff, biofilm, blood diamond, British Empire, Broken windows theory, Brownian motion, car-free, classic study, clean water, cognitive dissonance, cognitive load, corporate personhood, corporate social responsibility, Daniel Kahneman / Amos Tversky, delayed gratification, desegregation, different worldview, domesticated silver fox, double helix, Drosophila, Edward Snowden, en.wikipedia.org, epigenetics, Flynn Effect, framing effect, fudge factor, George Santayana, global pandemic, Golden arches theory, Great Leap Forward, hiring and firing, illegal immigration, impulse control, income inequality, intentional community, John von Neumann, Loma Prieta earthquake, long peace, longitudinal study, loss aversion, Mahatma Gandhi, meta-analysis, microaggression, mirror neurons, Mohammed Bouazizi, Monkeys Reject Unequal Pay, mouse model, mutually assured destruction, Nelson Mandela, Network effects, nocebo, out of africa, Peter Singer: altruism, phenotype, Philippa Foot, placebo effect, publication bias, RAND corporation, risk tolerance, Rosa Parks, selective serotonin reuptake inhibitor (SSRI), self-driving car, Silicon Valley, Skinner box, social contagion, social distancing, social intelligence, Stanford marshmallow experiment, Stanford prison experiment, stem cell, Steven Pinker, strikebreaker, theory of mind, Tragedy of the Commons, transatlantic slave trade, traveling salesman, trickle-down economics, trolley problem, twin studies, ultimatum game, Walter Mischel, wikimedia commons, zero-sum game, zoonotic diseases

In a world of noncooperators it’s disadvantageous to be the first altruist. How do systems of cooperation ever start?* Gigantic Question #1: What Strategy for Cooperating Is Optimal? While biologists were formulating these questions, other scientists were already starting to answer them. In the 1940s “game theory” was founded by the polymath John von Neumann, one of the fathers of computer science. Game theory is the study of strategic decision making. Framed slightly differently, it’s the mathematical study of when to cooperate and when to cheat. The topic was already being explored with respect to economics, diplomacy, and warfare. What was needed was for game theorists and biologists to start talking.


pages: 931 words: 79,142

Concepts, Techniques, and Models of Computer Programming by Peter Van-Roy, Seif Haridi

computer age, Debian, discrete time, Donald Knuth, Eratosthenes, fault tolerance, functional programming, G4S, general-purpose programming language, George Santayana, John von Neumann, Lao Tzu, Menlo Park, natural language processing, NP-complete, Paul Graham, premature optimization, sorting algorithm, the Cathedral and the Bazaar, Therac-25, Turing complete, Turing machine, type inference

Talk given at the Newcastle Seminar on the Teaching of Computing Science, Newcastle, UK. [232] Matthias Zenger and Martin Odersky. Implementing extensible compilers. In 1st International Workshop on Multiparadigm Programming with Object-Oriented Languages, pages 61–80, Budapest, Hungary, June 2001. John von Neumann Institute for Computing (NIC). Workshop held as part of ECOOP 2001. Foundations of Index ! (cut) operation (in Prolog), 662, 666, 669 ! (escaped variable marker), 500, 509 !! (read-only) operation, 206, 799 " (double quote), 53, 821 $ (nesting marker), 53, 83, 355, 365 ´ (single quote), 35, 52, 821, 824 ’ (single quote) operation (in Lisp), 39 * (multiplication) operation, 54, 821 */ (comment end), 841 + (addition) operation, 54, 821 - (subtraction) operation, 54, 821 .


Applied Cryptography: Protocols, Algorithms, and Source Code in C by Bruce Schneier

active measures, cellular automata, Claude Shannon: information theory, complexity theory, dark matter, Donald Davies, Donald Knuth, dumpster diving, Dutch auction, end-to-end encryption, Exxon Valdez, fault tolerance, finite state, heat death of the universe, information security, invisible hand, John von Neumann, knapsack problem, MITM: man-in-the-middle, Multics, NP-complete, OSI model, P = NP, packet switching, quantum cryptography, RAND corporation, RFC: Request For Comment, seminal paper, software patent, telemarketer, traveling salesman, Turing machine, web of trust, Zimmermann PGP

If you are depending on your random-number generator for security, weird correlations and strange results are the last things you want. The problem is that a random-number generator doesn’t produce a random sequence. It probably doesn’t produce anything that looks even remotely like a random sequence. Of course, it is impossible to produce something truly random on a computer. Donald Knuth quotes John von Neumann as saying: “Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin” [863]. Computers are deterministic beasts: Stuff goes in one end, completely predictable operations occur inside, and different stuff comes out the other end. Put the same stuff in on two separate occasions and the same stuff comes out both times.


pages: 1,799 words: 532,462

The Codebreakers: The Comprehensive History of Secret Communication From Ancient Times to the Internet by David Kahn

anti-communist, Bletchley Park, British Empire, Charles Babbage, classic study, Claude Shannon: information theory, computer age, cotton gin, cuban missile crisis, Easter island, end-to-end encryption, Fellow of the Royal Society, heat death of the universe, Honoré de Balzac, index card, interchangeable parts, invention of the telegraph, Isaac Newton, Johannes Kepler, John von Neumann, Louis Daguerre, machine translation, Maui Hawaii, Norbert Wiener, out of africa, pattern recognition, place-making, planned obsolescence, Plato's cave, pneumatic tube, popular electronics, positional goods, Republic of Letters, Searching for Interstellar Communications, stochastic process, Suez canal 1869, the scientific method, trade route, Turing machine, union organizing, yellow journalism, zero-sum game

The problem is then to discover the transformation rule, or the nature of the filter, when given the statistics of the input and output. It is like finding the structure of an electrical filter by passing random noise through it and measuring the statistical distributions of the input and output voltages.” Cryptology may also be regarded as a conflict in the sense employed in The Theory of Games and Economic Behavior by John Von Neumann and Oskar Morgenstern. As Shannon, who first made the allusion, puts it: “The situation between the cipher designer and cryptanalyst can be thought of as a ‘game’ of a very simple structure; a zero-sum two-person game with complete information, and just two ‘moves.’ [A zero-sum game is one in which one contestant’s advances are made at the expense of the other.]