Large Hadron Collider

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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

With no prospect of retraining the magnets any time soon, CERN scientists had to accept that when the Large Hadron Collider was ready to switch on a second time, it could not run safely at full power. The setbacks at CERN were a serious blow for particle physicists. In its history, the Large Hadron Collider endured delays lasting years along with cost overruns and catastrophic accidents. Talking through the events a month before the repairs were finished, Evans was circumspect. “We were all really down, but you cannot dwell on it,” he said. “You have to remember. Nobody had ever built anything like the Large Hadron Collider before.” The year 2009 marked the forty-fifth anniversary of the Higgs particle’s birth, at least in the theoretical equations written down in Peter Higgs’s notebook.

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Tevatron scientists would pour all their efforts into finding the particle before the Large Hadron Collider was up and running, he said. “CERN will look ridiculous at having missed the opportunity, and the future of the CERN will be very dark,” he told the British journal Physics World. Back in Michigan, Gordy Kane wrote out a letter and put it in the post. It was addressed to Stephen Hawking at Cambridge University and enclosed a check for $100. In an exchange of emails a few years later, Professor Hawking said the bet that the Higgs particle would never be found didn’t end with LEP. It carries on to Fermilab’s Tevatron and CERN’s Large Hadron Collider. “I think there’s a good chance that virtual black holes will make it impossible to observe the Higgs, but, of course, if it is found, I will pay,” he wrote.22 On hearing this, Kane said he was confident he would one day get his money back.

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Maiani apologized for taking so long to come clean about the problem, but said he was distracted by the excitement over the Higgs at CERN.23 “Had we run LEP for longer and not come up with anything and then discovered a bloody hole in the finances of the Large Hadron Collider, it could have been ...” Cashmore stops and draws a finger across his throat. “It could have been the end of the subject. It was that dramatic. It was that heavy-duty. The Large Hadron Collider was not a given. People could have pulled the plug. They could have said we were irresponsible, spending money we didn’t have, on an off chance. And it was an off chance. We could have ended up with nothing.”

Collider by Paul Halpern

Albert Einstein, Albert Michelson, anthropic principle, cosmic microwave background, cosmological constant, dark matter, Dr. Strangelove, Ernest Rutherford, Gary Taubes, gravity well, Herman Kahn, Higgs boson, horn antenna, index card, Isaac Newton, Large Hadron Collider, Magellanic Cloud, pattern recognition, Plato's cave, Richard Feynman, Ronald Reagan, statistical model, Stephen Hawking, Strategic Defense Initiative, time dilation

Lemaitre, Georges length contraction lepton colliders leptons Leucippus LHC. See Large Hadron Collider LHCb (Large Hadron Collider beauty) particle detector LHCf (Large Hadron Collider forward) detector light Einstein’s research on electric charges and invisible region of rainbow of colors of speed of wavelength measurement of lightning strikes, as accelerators Linde, Andrei lithium Liu, Jun Livingston, M. (Milton) Stanley lodestone Lofgren, Edward London, Jack MACHO Project MACHOs (Massive Compact Halo Objects) magnetic fields magnetic monopoles magnetism magnets at Fermilab hadrons as at Large Hadron Collider (LHC) in Superconducting Super Collider (SSC) in synchrotrons Manhattan Project Mann, Alfred K.

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Comparing it to Waxahachie, he wrote, “Geneva . . . has fewer good rib restaurants but more fondue and is easier to spell and pronounce.”23 Humanity’s best chance of finding the Higgs boson and possibly identifying some of the lightest supersymmetric companion particles now rests with the Large Hadron Collider. Though it will crash particles together at lower energies than the SSC was supposed to—14 TeV in total instead of 20 TeV—most theoretical estimates indicate that if the Higgs is out there the LHC will find it. If all goes well, modern physics will soon have cause for celebration. 8 Crashing by Design Building the Large Hadron Collider The age in which we live is the age in which we are discovering the fundamental laws of Nature, and that day will never come again —RICHARD FEYNMAN (THE CHARACTER OF PHYSICAL LAW, 1965) Compared to the wild flume ride of American high-energy physics, CERN has paddled steadily ahead like a steam-boat down the Rhone River.

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Unlike, for instance, Rubbia and Van der Meer’s winning science’s highest honor for the weak boson discoveries, there probably wouldn’t be obvious hands (aside from those of its namesake theorist) to confer the award. Completing the quartet at the LHC’s interaction points are two sizable specialized detectors: the LHCb (Large Hadron Collider beauty) experiment and ALICE (A Large Ion Collider Experiment). Two other petite detectors will operate near the ATLAS and CMS caverns, respectively: the LHCf (Large Hadron Collider forward) and TOTEM (TOTal Elastic and diffractive cross-section Measurement) experiments. The focus of the LHCb experiment is to produce B-particles (particles containing the bottom quark) and to examine their modes of decay.

Neutrino Hunters: The Thrilling Chase for a Ghostly Particle to Unlock the Secrets of the Universe by Ray Jayawardhana

Albert Einstein, Alfred Russel Wallace, anti-communist, Arthur Eddington, cosmic microwave background, dark matter, Eddington experiment, Ernest Rutherford, Higgs boson, invention of the telescope, Isaac Newton, it's over 9,000, Johannes Kepler, Large Hadron Collider, Magellanic Cloud, New Journalism, race to the bottom, random walk, Richard Feynman, Schrödinger's Cat, seminal paper, Skype, South China Sea, Stephen Hawking, time dilation, undersea cable, uranium enrichment

Formulated in the early 1970s, the standard model incorporates two dozen elementary particles of matter and their antimatter twins, three types of interactions among them, and the symmetries that govern those interactions. It is the best description of the subatomic world that we have, and countless experiments over three decades have verified its predictions with exquisite precision. The fabled Large Hadron Collider at CERN, the most powerful and expensive atom smasher ever, was constructed at a jaw-dropping price tag of roughly $9 billion in large part to nail down the final missing piece of the theory. The LHC confirmed the existence of the Higgs boson, a particle hypothesized to be responsible for endowing other elementary particles with mass.

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By recording billions of such decays over nearly a decade of operations, physicists have measured a larger-than-expected asymmetry in the decay rates of B-mesons compared to those of anti-B-mesons. This is the most severe case of CP violation yet seen, but it is still far from sufficient to account for the matter-antimatter asymmetry in the universe, and so the search continues for a more effective mechanism. Starting in 2011, one of the five major experiments at CERN’s Large Hadron Collider, the world’s most powerful particle accelerator, occupying a circular tunnel some 27 kilometers (16.8 miles) long near the Swiss-French border, is looking for other instances of CP violation. Meanwhile, theorists have dreamed up a number of other ways to generate a stronger asymmetry. Some of these are rather complicated, if not contrived.

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Fourth, it would help cosmologists understand how matter came to predominate over antimatter seconds after the big bang. Given all these exciting prospects, it is no wonder that neutrino hunters are looking forward to the coming decade with great anticipation. EIGHT SEEDS OF A REVOLUTION The summer of 2012 marked a triumphant capstone for physics. Two separate experiments at the gigantic Large Hadron Collider (LHC) at the CERN laboratory revealed compelling evidence of the Higgs boson, one of the most elusive subatomic particles that theorists had ever concocted. With this discovery, the crucial final piece of the grand edifice known as the standard model of particle physics fell into place. But the curious antics of neutrinos threaten to bring down the physicists’ elaborate creation, or at least show that it is incomplete.

Wonders of the Universe by Brian Cox, Andrew Cohen

a long time ago in a galaxy far, far away, Albert Einstein, Albert Michelson, Apollo 11, Arthur Eddington, California gold rush, Cepheid variable, cosmic microwave background, dark matter, Dmitri Mendeleev, Eddington experiment, Eyjafjallajökull, Ford Model T, heat death of the universe, Higgs boson, Isaac Newton, James Watt: steam engine, Johannes Kepler, Karl Jansky, Large Hadron Collider, Magellanic Cloud, Mars Rover, Neil Armstrong, Stephen Hawking, the scientific method, time dilation, trade route

The next great symmetry-breaking event, however, which occurred 10–11 seconds after the Big Bang, is absolutely within our reach because this is the era we are recreating and observing at CERN’s Large Hadron Collider. It is called electroweak symmetry breaking; at this point the final two forces of nature – electromagnetism and the weak nuclear force – are separated. During this process the sub-atomic building blocks of everything we see today (the quarks and electrons) acquired mass. The most popular theory for this process is known as the Higgs mechanism, and the search for the associated Higgs Particle is one of the key goals of the Large Hadron Collider project. We are now on very firm experimental and theoretical ground.

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Our description of last of the four, the Weak Nuclear Force, resides in the Standard Model of particle physics. This theory, a product of the 1970s, unifies the description of the Weak Nuclear Force with Quantum Electrodynamics, although there is a missing piece of the theory known as the Higgs Boson that is currently being searched for at the Large Hadron Collider at CERN in Geneva. Until the Higgs Boson, or whatever does its job, is found, we cannot claim to have a working description of the Weak Nuclear Force and its relationship with electromagnetism. However despite the long pedigree and beautiful accuracy and elegance of Einstein’s theory of gravity, it is known to be incomplete.

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Such is the power, excitement and rate of progress of modern science. This chapter is the story of how those building blocks were created in the very early Universe, fused into more complex structures over billions of years in the furnaces of space, and delicately assembled by the forces of nature into planets, mountains, rivers and human beings. The Large Hadron Collider (LHC) is the highest energy particle accelerator at CERN (the European particle physics laboratory near Geneva, Switzerland). In this huge machine, 27km (17 miles) in circumference, proton beams are accelerated so that they collide head-on. The resultant particles can be detected and recorded so that scientists can then try to understand how they fit together.

The Fear Index by Robert Harris

algorithmic trading, backtesting, banking crisis, dark matter, family office, fear index, Fellow of the Royal Society, fixed income, Flash crash, God and Mammon, high net worth, implied volatility, Jim Simons, Large Hadron Collider, mutually assured destruction, National best bid and offer, Neil Kinnock, Renaissance Technologies, speech recognition, two and twenty

The Making of Neil Kinnock Selling Hitler Good and Faithful Servant To my family Gill, Holly, Charlie, Matilda, Sam Acknowledgements I WISH TO thank all those whose expertise, generously given, has made this book possible: first and foremost Neville Quie of Citi, who made many helpful suggestions and introductions and who, along with Cameron Small, patiently helped me through the labyrinth of shorts and out-of-the-money puts; Charles Scott, formerly of Morgan Stanley, who discussed the concept, read the manuscript and introduced me to Andre Stern of Oxford Asset Management, Eli Lederman, former CEO of Turquoise, and David Keetly and John Mansell of Polar Capital Alva Fund, all of whom provided useful insights; Leda Braga, Mike Platt, Pawel Lewicki and the algorithmic team at BlueCrest for their hospitality and for letting me spend a day watching them in action; Christian Holzer for his advice on the VIX; Lucie Chaumeton for fact-checking; Philippe Jabre of Jabre Capital Partners SA for sharing his knowledge of the financial markets; Dr Ian Bird, head of the Large Hadron Collider Computing Grid Project, for two conducted tours and insights into CERN in the 1990s; Ariane Koek, James Gillies, Christine Sutton and Barbara Warmbein of the CERN Press Office; Dr Bryan Lynn, an academic physicist who worked at both Merrill Lynch and CERN and who kindly described his experiences of moving between these different worlds; Jean-Philippe Brandt of the Geneva Police Department for giving me a tour of the city and answering my queries about police procedure; Dr Stephen Golding, Consultant Radiologist at the John Radcliffe Hospital in Oxford, for advising me on brain scans and putting me in touch with Professor Christoph Becker and Dr Minerva Becker who in turn helpfully arranged a tour of the Radiological Department of the University Hospital in Geneva.

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Your family name … I only ask in case there may be a racist motive.’ ‘No, not Jewish.’ ‘And Madame Hoffmann?’ ‘I’m English.’ ‘And you’ve lived in Switzerland for how long, Dr Hoffmann?’ ‘Fourteen years.’ Weariness once again almost overtook him. ‘I came out here in the nineties to work for CERN, on the Large Hadron Collider. I was there for about six years.’ ‘And now?’ ‘I run a company.’ ‘Called?’ ‘Hoffmann Investment Technologies.’ ‘And what does it make?’ ‘What does it make? It makes money. It’s a hedge fund.’ ‘Very good. “It makes money.” How long have you been here?’ ‘Like I said – fourteen years.’

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He was conscious of being pale and unshaven and he tried to avoid meeting anyone’s gaze, which was easy enough as few bothered to look up as he passed. Hoffmann’s force of quants was nine-tenths male, for reasons he did not entirely understand. It was not deliberate policy; it simply seemed to be only men who applied, usually refugees from the twin miseries of academia: low salaries and high tables. Half a dozen had come from the Large Hadron Collider. Hoffmann would not even consider hiring anyone without a PhD in maths or the physical sciences; all doctoral theses were expected to have been peer-reviewed in the top fifteen per cent. Nationality did not matter and nor did social skills, with the result that Hoffmann’s payroll occasionally resembled a United Nations conference on Asperger’s syndrome.

The Infinity Puzzle by Frank Close

Albert Einstein, Andrew Wiles, Arthur Eddington, dark matter, El Camino Real, en.wikipedia.org, Ernest Rutherford, Higgs boson, Isaac Newton, Large Hadron Collider, Murray Gell-Mann, Richard Feynman, Ronald Reagan, seminal paper, Simon Singh, Ted Sorensen

However, it would be three more years before this was finally understood, and a half century before the remarkable implications would be pursued at the Large Hadron Collider. Chapter 9 “the boson that has been named after me,” a.k.a. the hig gs boson How Peter Higgs—and many others—discover the “Higgs Mechanism” for creating mass. The Higgs Boson—why it is now so important for particle physicists, why it is named after him, and how to become famous in three weeks. “ G osh! Big’s no way to describe it, though it’s important in theory [5,5].” The Higgs Boson is so famous that its anagram appears in Nick Kemmer’s favorite crossword: the Guardian.1 Ask why CERN in Geneva is building the Large Hadron Collider (LHC), costing some $10 billion,2 and the stock answer will be “to discover the Higgs Boson.”

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In simplified accounts, Veltman’s role was much like that of John the Baptist, preparing the way with the tools, the blueprints, and the machinery to fit everything together; ’t Hooft was the true Messiah, the genius that physics had awaited for years who built the theory, and the structure, that would lead to a golden age. Forty years later, their legacy includes the largest and most ambitious experiments in physics that have ever been attempted: the simulation at the Large Hadron Collider (LHC) at CERN in Geneva of the first moments in the universe after the Big Bang. For more than two thousand years, until ’t Hooft, a central aim of philosophy and science had been to identify the fundamental pieces of matter, the “atoms,” and, latterly, the elementary particles. Following that breakthrough, the focus has changed: Our conceit today is that we may be able Prologue: Amsterdam, 1971 13 to reveal how matter itself was created and how our universe of shape and form came to be.

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The first half of this narrative describes how ’t Hooft, and others, made the crucial breakthroughs that culminated in the triumph of 1971. The remarkable developments that have come to pass since that seminal moment will be the theme of the later chapters. There I shall trace the path from a sideshow of a talk in Amsterdam to a multibillion-dollar worldwide scientific collaboration that hopes to answer such questions at the Large Hadron Collider. part  genesis Chapter 1 the point of infinity Abdus Salam arrives in Cambridge from India in 1946 and becomes a theoretical physicist by chance. Paul Matthews tells him that the textbooks on atomic physics are out-of-date. A beautiful theory of atoms and light—Quantum Electrodynamics—is in crisis, as its equations give nonsense, “infinity,” as the answer for quantities that are known to be finite.

The World According to Physics by Jim Al-Khalili

accounting loophole / creative accounting, Albert Einstein, butterfly effect, clockwork universe, cognitive dissonance, cosmic microwave background, cosmological constant, dark matter, double helix, Ernest Rutherford, fake news, Fellow of the Royal Society, germ theory of disease, gravity well, heat death of the universe, Higgs boson, information security, Internet of things, Isaac Newton, Large Hadron Collider, Murray Gell-Mann, post-truth, power law, publish or perish, quantum entanglement, Richard Feynman, Schrödinger's Cat, Stephen Hawking, supercomputer in your pocket, the scientific method, time dilation

Many physicists today feel that we might potentially be on the verge of another revolution in physics as big as that seen a century ago with the birth of relativity and quantum mechanics. I am not suggesting that we are about to discover some fundamental new phenomenon, like X-rays or radioactivity, but there may yet be a need for another Einstein to break the current deadlock. The Large Hadron Collider has not yet followed up on its 2012 success in detecting the Higgs boson, and thereby confirming the existence of the Higgs field (which I will discuss later); many physicists were hoping for the discovery of other new particles by now, which would help resolve long-standing mysteries. And we still don’t understand the nature of the dark matter holding galaxies together or the dark energy that is ripping the universe apart; nor do we have answers to fundamental questions like why there is more matter than antimatter; why the properties of the universe are so finely tuned to allow for stars and planets, and life, to exist; whether there is a multiverse; or whether there was anything before the Big Bang that created the universe we see.

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This is why Stephen Hawking never won a Nobel Prize for his work in the mid-1970s on the way black holes radiate energy, a phenomenon known as Hawking radiation: the Nobel is only awarded to theories or discoveries that have been confirmed experimentally. Likewise, Peter Higgs and others who made a similar prediction had to wait half a century for the existence of the Higgs boson to be confirmed at the Large Hadron Collider. It is also the reason why physics as a scientific discipline only began to make truly impressive advances once the tools and instruments necessary to test theories—through observation, experimentation, and quantitative measurement—had been invented. The ancient Greeks may have been brilliant at abstract thinking, developing subjects such as philosophy and geometry to a level of sophistication that is still valid today, but—Archimedes aside—they were not particularly famous for their experimental prowess.

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So, instead of patting ourselves on the back for how far we’ve come, should we consider the possibility that we might be straying too far from the path of physics? Many physicists will no doubt argue that these past few years have been tremendously exciting for fundamental physics, considering the widely reported discoveries of the Higgs boson at the Large Hadron Collider in 2012, followed by gravitational waves at the LIGO (Laser Interferometer Gravitational-Wave Observatory) facilities in the United States in 2016. But the truth is that both these observational discoveries, vital though they are, ‘merely’ confirm predictions made by theorists a long time ago—fifty years in the case of the Higgs, and a full century for gravitational waves.

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

Einstein found that unacceptable. His famous objection was echoed uncannily in 2009, at the inauguration of the Large Hadron Collider. Holger Bech Nielsen and Masao Ninomiya offered a modest proposal to save the world. We would play cards with God. Or the God particle. Conceptually, Nielsen and Ninomiya were suggesting something like this: Make up a deck with a million cards. All but one of the cards have blank faces. The other is the Joker, and it says, SHUT DOWN THE LARGE HADRON COLLIDER IMMEDIATELY. We shuffle the deck and draw one card. As long as the card is blank, the European science agency CERN continues with efforts to bring the LHC online and probe the secrets of the universe.

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For instance, Gott would want to know whether the ET’s language had a word for “war.” The ET would offer that elusive second data point, a second random draw from the urn of possibility. It would go a long way toward revealing whether the human condition is universal or unique. Pandora’s Box Buried in the mountainside near Geneva, CERN’s Large Hadron Collider (LHC) is the most powerful particle accelerator ever built. It is a circular vacuum tunnel in which magnets accelerate protons to nearly the speed of light. The protons smash into one another head-on, producing bursts of other particles. High among the LHC’s goals was to discover whether the Higgs boson exists.

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During the downtime, physicist Holger Bech Nielsen, one of the original doomsayers, and colleague Masao Ninomiya began posting yet more bizarre speculations about the LHC’s troubles to an internet site. These too were quickly picked up by the media, resulting in such headlines as GOD IS SABOTAGING THE LARGE HADRON COLLIDER and TIME-TRAVELING HIGGS SABOTAGES THE LHC. NO, REALLY. In effect the physicists were proposing an observation selection effect. Suppose that operation of the LHC would cause a catastrophe ending all earthly life. Then, given that we’re alive, we necessarily live in a quantum world in which all attempts to create fatally powerful colliders have been prevented by a series of “accidents.”

The Fabric of the Cosmos by Brian Greene

airport security, Albert Einstein, Albert Michelson, Arthur Eddington, Brownian motion, clockwork universe, conceptual framework, cosmic microwave background, cosmological constant, dark matter, dematerialisation, Eddington experiment, Hans Lippershey, Henri Poincaré, invisible hand, Isaac Newton, Large Hadron Collider, luminiferous ether, Murray Gell-Mann, power law, quantum entanglement, Richard Feynman, seminal paper, Stephen Hawking, time dilation, urban renewal

But if gravity’s intrinsic strength on small scales is far greater than previously thought, tiny black holes could be produced with significantly less compression force than previously believed. Calculations show that the Large Hadron Collider may have just enough squeezing power to create a cornucopia of microscopic black holes through high-energy collisions between protons.7 Think about how amazing that would be. The Large Hadron Collider might turn out to be a factory for producing microscopic black holes! These black holes would be so small and would last for such a short time that they wouldn’t pose us the slightest threat (years ago, Stephen Hawking showed that all black holes disintegrate via quantum processes—big ones very slowly, tiny ones very quickly), but their production would provide confirmation of some of the most exotic ideas ever contemplated.

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If the lower end of this range turns out to be right, Fermilab stands a reasonably good chance of discovering a Higgs particle in the near future. And certainly, if Fermilab fails and if the estimated mass range is nonetheless correct, the Large Hadron Collider should produce Higgs particles galore by the end of the decade. The detection of Higgs particles would be a major milestone, as it would confirm the existence of a species of field that theoretical particle physicists and cosmologists have invoked for decades, without any supporting experimental evidence. Another major goal of both Fermilab and the Large Hadron Collider is to detect evidence of supersymmetry. Recall from Chapter 12 that supersymmetry pairs particles whose spins differ by half a unit and is an idea that originally arose from studies of string theory in the early 1970s.

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As a primary example, just as electromagnetic fields are composed of photons, Higgs fields are composed of particles that, not surprisingly, are called Higgs particles. Theoretical calculations have shown that if there is a Higgs ocean permeating space, Higgs particles should be among the debris from the high-energy collisions that will take place at the Large Hadron Collider, a giant atom smasher now under construction at Centre Européène pour la Recherche Nuclaire (CERN) in Geneva, Switzerland, and slated to come online in 2007. Roughly speaking, enormously energetic head-on collisions between protons should be able to knock a Higgs particle out of the Higgs ocean somewhat as energetic underwater collisions can knock H2O molecules out of the Atlantic.

The Serious Guide to Joke Writing: How to Say Something Funny About Anything by Sally Holloway

Albert Einstein, Berlin Wall, Boris Johnson, congestion charging, Hugh Fearnley-Whittingstall, Kickstarter, Large Hadron Collider, lateral thinking

We get busy with the exercises, crank up our brains and then they really do appear... Summary • You don’t have to be a genius to write jokes, they exist in the ether! • You just need to spend time looking for them! Why not start now? Chapter Five (PRACTICAL): Double Joke-webs & The Hadron Joke Collider The Large Hadron Collider will accelerate bunches of protons... colliding them head-on..., with each collision spewing out thousands of particles at nearly the speed of light. Scientific American The Hadron Joke Collider will bash two opposing subjects together, colliding them head-on with the collision spewing out jokes at the speed of thought.

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Scientific American The Hadron Joke Collider will bash two opposing subjects together, colliding them head-on with the collision spewing out jokes at the speed of thought. Me It’s Week Three of the class and I get them playing some improv games as a bit of a warm upxii. They’ve enjoyed romping round the room but it’s time for something more cerebral. I sit them down and ask them if they’ve heard of the Large Hadron Collider. Most of them have, although they’ve no idea why I’m mentioning it. ‘We’re going to use a similar concept to write jokes,’ I tell them. Loads of jokes are links between two previously unrelated subjects. I tell them a joke... I love it that politicians are coming out as bisexual. On election night the swingometer will at last be able to swing both ways!

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But it would be a shame if that’s all you did a double joke-web for, when there’s so much more to find. The other thing is that the obvious links can lead to obvious jokes. When you collide subjects you will find the deeper less obvious ideas which lead to profound jokes, thoughts and musings - a truly wonderful thing. Don’t forget... The purpose of the Large Hadron Collider is to increase our knowledge about the universe. How Stuff Works The purpose of the Hadron Joke Collider is to increase the number of jokes in the world. Me Summary • Many jokes are links between two subjects. • You can push these links further by using the Hadron Joke Collider to bash subjects together

Lost in Math: How Beauty Leads Physics Astray by Sabine Hossenfelder

Adam Curtis, Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, Brownian motion, clockwork universe, cognitive bias, cosmic microwave background, cosmological constant, cosmological principle, crowdsourcing, dark matter, data science, deep learning, double helix, game design, Henri Poincaré, Higgs boson, income inequality, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, Johannes Kepler, Large Hadron Collider, Murray Gell-Mann, Nick Bostrom, random walk, Richard Feynman, Schrödinger's Cat, Skype, Stephen Hawking, sunk-cost fallacy, systematic bias, TED Talk, the scientific method

It’s the right combination between explaining empirical facts and using fundamental principles that makes a physical theory successful and beautiful.” Gian is head of the theory division at CERN, the Conseil Européen pour la Recherche Nucléaire. CERN operates what is currently the largest particle collider, the Large Hadron Collider (LHC), humankind’s closest look yet at the elementary building blocks of matter: a $6 billion, 16-mile underground ring to accelerate protons and smash them together at almost the speed of light. The LHC is a compilation of extremes: supercooled magnets, ultrahigh vacuum, computer clusters that, during the experiments, record about three gigabytes of data—comparable to several thousand ebooks—per second.

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The mathematics of susy is very similar to that of already established theories, and the standard physics curriculum is good preparation for students to work on susy. “It’s a well-defined framework; it was easy,” says Michael. It was a good choice. Michael received tenure in 2004 and now heads the research group New Physics at the Large Hadron Collider, funded by the German Research Foundation. “I also like symmetries. That made it attractive for me.” AS I’VE noted, on our quest to understand what the world is made of, we have found twenty-five different elementary particles. Supersymmetry completes this collection with a set of still undiscovered partner particles, one for each of the known particles, and some additional ones.

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“SUSY searches at the Tevatron and the LHC.” Talk given at Physics in Collision, Vancouver, Canada, August/September 2011, slide 41. http://indico.cern.ch/event/117880/contributions/1330772/attachments/58548/84276/portell_SUSYsearches.pdf. 11. Allanach B. 2015. “Hint of new particle at CERN’s Large Hadron Collider?” Guardian, December 16, 2015. 12. Quoted in Cho A. 2007. “Physicists’ nightmare scenario: the Higgs and nothing else.” Science 315:1657–1658. 13. Gross D. 2013. “Closing remarks.” Presentation at Strings 2013, Sogang University, Seoul, South Korea, June 24–29, 2013. www.youtube.com /embed/vtXAwk1vkmk.

The Elements of Power: Gadgets, Guns, and the Struggle for a Sustainable Future in the Rare Metal Age by David S. Abraham

"World Economic Forum" Davos, 3D printing, Airbus A320, Boeing 747, carbon footprint, circular economy, Citizen Lab, clean tech, clean water, commoditize, Deng Xiaoping, Elon Musk, en.wikipedia.org, Fairphone, geopolitical risk, gigafactory, glass ceiling, global supply chain, information retrieval, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Large Hadron Collider, new economy, oil shale / tar sands, oil shock, planned obsolescence, reshoring, Robert Metcalfe, Ronald Reagan, Silicon Valley, Solyndra, South China Sea, Steve Ballmer, Steve Jobs, systems thinking, telemarketer, Tesla Model S, thinkpad, upwardly mobile, uranium enrichment, WikiLeaks, Y2K

Geological Survey figures, Metal-Pages prices, author’s estimates. 22. Lokanc, Eggert, and Redlinger, “The Availability of Indium,” 4. 23. Ibid., 3. 24. Tia Ghose, “New Atom-Smashing Magnet Passes First Tests,” Live Science, July 12, 2013, http://www.livescience.com/38129-large-hadron-collider-magnet-passes-tests.html; Lynn Yaris, “Successful Test of New U.S. Magnet Puts Large Hadron Collider on Track for Major Upgrade,” News Center, July 11, 2013, http://newscenter.lbl.gov/2013/07/11/new-magnet-for-lhc/. 25. “Molycorp-Silmet AS, David O’Brock’s interview,” Ruslan TV, April 16, 2011, http://www.youtube.com/watch?v=JMZMjiCWuJA; O’Brock, interview, January 22, 2013. 26.

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The Estonian refiner sells small amounts of specialized high-grade niobium metal to universities and small manufacturers, rather than to giant multinational companies. Silmet’s metal finds its way into magnetic resonance imaging machines, televisions, and even the electromagnets that steer streams of protons around CERN’s Large Hadron Collider, the world’s highest-powered particle accelerator, which is located in Switzerland.24 O’Brock doesn’t like to show the initial processing of niobium from the Brazilian supplies. He is proud of the safety of his facility but says the building is still dangerous, since the processing produces a lot of volatile dust.

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., 72 BHP Billiton, 58 Big Bertha gun, 160–61, 275n12 Big Data (Cukier and Mayer-Schönberger), 119 Bissel, Richard, 159 Bloomberg News: on CBMM, 42 on Colombian tungsten trade, 109 Boeing, 113, 128, 130–31 Boiridy, Mia, 85 Bombs, from airplanes, 279n33 Boogaart, Gerald van den, 33–35 Boron, 21, 26, 116, 121 Boston Consulting Group, 212 Boyle, Dominic, 163 Bre-X (exploration company), 59 Britain: export bans during WWI, 162–63 tungsten, actions on during WWII, 239n28 British Geological Survey, on Chinese production of critical materials, 236–37n18 Bronze, 157 Bronze Age, 12, 157, 274n7 Broxo company, 115 Bubar, Don, 55, 64 Bukit Merah, Malaysia, pollution in, 183 Burns, Stuart, 147 Business models, need for change in, 223–25 By-product production, 79–80 Cadmium, 3, 116, 148, 159, 167, 181, 258n3 Cadmium-tellurium thin films, 148–49 Calculators, 118–19 Canada: indium sales via telemarketing, 251n7 mining workforce, age of, 85 Carbon emissions, 152–53, 266n5, 281n2 Carnegie Mellon University, 211 Carneiro, Tadeu: on CBMM, 43, 46, 64–65 lack of investment worries, 54, 64 on niobium, 44 as spokesperson for CBMM, 41 on sustainability, 152, 153 Cars, 141–48 Cassiterites (tin ore), 105–6 Castilloux, Ryan, 116 Catalytic converters, 144–45 Caterpillar, 212, 223–24 CBMM (Companhia Brasileira de Metalurgia e Mineração), 39–46, 54, 62, 64–66, 152–53, 242n6 Central Intelligence Agency (CIA), 158 Centronics, 214 Ceramics, in wireless networks, 124 Cerium, 2, 35, 74, 75, 104, 140–41 CERN, Large Hadron Collider, 81 CFLs (compact fluorescent lightbulbs), 150 Characteristics of rare metals, 3–4 Chicago Board of Trade, 101 Chicago Mercantile Exchange, 101 Chile, ore grade of lithium mines, 285n33 China: antimony production in, 289n16 CBMM ownership in, 42 coal demand in, 208 critical material production, 236–37n18 defense expenditures, 278n31 environmental issues, 153–54, 173–77, 281n2 export ban on rare earth, x, 212 Hong Kong, relationship with, 102 Japan, conflict with, x, 15, 22–25, 165 Jiangxi, ore processing in, 77, 82–85 low-energy lighting production in, 152 material production costs, 240n33 rare earth elements supply chain, control of, 32–37 rare earth permanent magnets in, 137 rare metal exchanges, 96–98 rare metals industry in, 194–200 refining in, 75, 82–85 regulatory environment, 99–101, 103–5, 202, 240n34, 288n11 steel demand in, 11 technology use in, 218 tungsten production in, 289n16 WTO membership of, 200–203 China Securities Regulatory Commission, 99, 101 Chinese Society of Rare Earths, 176 CIA (Central Intelligence Agency), 158 Circular economies, 225 Cisco, 218 Clean energy technologies, 290n27 Cloud storage, 122 CO2 emissions, 152–53, 266n5, 281n2 Coal, 149–50, 178, 207, 208 Cobalt, 3, 18–21, 25, 28, 78, 101, 121, 128, 147, 219, 235nn5–6, 260n15 Cohen, Ronald R., 179–80, 184 Colombia: mineral trading as funding for conflicts in, 109 tungsten production in, 48 Colorado School of Mines, 79, 86–87, 296n23 Committee on Natural Resources (U.S.

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

It is not clear if that formula will ever be repeated. For one thing, there has been an explosion of publications. Many theories vie for prominence—far more than in the days of Einstein and Schrödinger. Yet the energies required to test these approaches have required increasingly expensive and time-consuming projects, such as the Large Hadron Collider near Geneva, Switzerland. Unlike, for example, the eclipse measurements, experimental science has generally proceeded far more slowly and cautiously, requiring far greater quantities of data 224 Conclusion: Beyond Einstein and Schrödinger before announcing results. In high-energy physics, teams typically involve hundreds of researchers rather than lone pioneers.

…

Over the course of the 1970s and 1980s, particle accelerator experiments at CERN (European Organization for Nuclear Research), near Geneva, Switzerland, verified each of those predictions except for the last. Finally, the Higgs boson was confirmed through particle collision data collected at CERN’s Large Hadron Collider. 227 Einstein’s Dice and Schrödinger’s Cat Along with electroweak unification, the standard model also includes a theoretical description of the strong interaction that involves exchange particles called gluons. These form the “glue” that sticks quarks together and keeps them confined to groups of three (or quark-antiquark pairs in the case of mesons).

…

Exploring the full implications of string/M-theory and loop quantum gravity would require an excursion to the Planck scale, the minuscule domain in which quantum theory and gravity meet. Such tremendous energies are well beyond current reach. Fortunately, high-energy theories often have lower-energy implications. Thus the Large Hadron Collider could well detect particle states that offer a window into physics beyond the standard model. An example would be supersymmetric companion particles: mates of fermions with bosonic properties, or vice versa. The discovery of such would offer powerful evidence for supersymmetry and possible dark matter candidates.

The God Equation: The Quest for a Theory of Everything by Michio Kaku

Albert Einstein, anthropic principle, Arthur Eddington, cosmic microwave background, cosmological constant, dark matter, double helix, Eddington experiment, Edmond Halley, Ernest Rutherford, fudge factor, Higgs boson, Isaac Newton, Johannes Kepler, Large Hadron Collider, Murray Gell-Mann, Olbers’ paradox, place-making, Richard Feynman, Schrödinger's Cat, Stephen Hawking, Tacoma Narrows Bridge, uranium enrichment

For all the excitement generated by string theory, the critics have been keen to point out its defects. And after all the hype and frenzy, real progress has stalled. The most glaring problem is that, for all the flattering press extolling the beauty and complexity of the theory, we have no solid, testable evidence. Once, it was hoped that the Large Hadron Collider (LHC) outside Geneva, Switzerland, the biggest particle accelerator in history, would find concrete evidence for the final theory, but this has remained elusive. The LHC was able to find the Higgs boson (or the God particle), but this particle was only a tiny missing piece of the final theory.

…

Physicists found it difficult to believe that anything so clumsy and unwieldy could be the fundamental theory of the universe. LHC Because there is so much at stake, nations are willing to spend billions to create the next-generation particle accelerators. Currently, the headlines have been dominated by the Large Hadron Collider outside Geneva, Switzerland, the largest machine of science ever built, costing more than $12 billion and stretching almost seventeen miles in circumference. LHC looks like a huge doughnut that straddles the border between Switzerland and France. Inside the tube, protons are accelerated until they reach extremely high energy.

…

As far as a direct impact on our immediate lives, it probably will be minimal. Each solution of the theory of everything is an entire universe. Therefore, the energy at which the theory becomes relevant is the Planck energy, which is a quadrillion times greater than the energy produced by the Large Hadron Collider. The energy scale of the theory of everything concerns the creation of the universe and the mysteries of black holes, not the affairs of you and me. The real impact of the theory on our lives may be philosophical, because the theory may finally answer deep philosophical questions that have haunted great thinkers for generations, such as is time travel possible, what happened before creation, and where did the universe come from?

Reinventing Capitalism in the Age of Big Data by Viktor Mayer-Schönberger, Thomas Ramge

accounting loophole / creative accounting, Air France Flight 447, Airbnb, Alvin Roth, Apollo 11, Atul Gawande, augmented reality, banking crisis, basic income, Bayesian statistics, Bear Stearns, behavioural economics, bitcoin, blockchain, book value, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Cass Sunstein, centralized clearinghouse, Checklist Manifesto, cloud computing, cognitive bias, cognitive load, conceptual framework, creative destruction, Daniel Kahneman / Amos Tversky, data science, Didi Chuxing, disruptive innovation, Donald Trump, double entry bookkeeping, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, flying shuttle, Ford Model T, Ford paid five dollars a day, Frederick Winslow Taylor, fundamental attribution error, George Akerlof, gig economy, Google Glasses, Higgs boson, information asymmetry, interchangeable parts, invention of the telegraph, inventory management, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, job satisfaction, joint-stock company, Joseph Schumpeter, Kickstarter, knowledge worker, labor-force participation, land reform, Large Hadron Collider, lone genius, low cost airline, low interest rates, Marc Andreessen, market bubble, market design, market fundamentalism, means of production, meta-analysis, Moneyball by Michael Lewis explains big data, multi-sided market, natural language processing, Neil Armstrong, Network effects, Nick Bostrom, Norbert Wiener, offshore financial centre, Parag Khanna, payday loans, peer-to-peer lending, Peter Thiel, Ponzi scheme, prediction markets, price anchoring, price mechanism, purchasing power parity, radical decentralization, random walk, recommendation engine, Richard Thaler, ride hailing / ride sharing, Robinhood: mobile stock trading app, Sam Altman, scientific management, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, Snapchat, statistical model, Steve Jobs, subprime mortgage crisis, Suez canal 1869, tacit knowledge, technoutopianism, The Future of Employment, The Market for Lemons, The Nature of the Firm, transaction costs, universal basic income, vertical integration, William Langewiesche, Y Combinator

It also required more than 300,000 mathematicians, physicists, biologists, chemists, engineers, and mechanics spread across dozens of labs, each playing his or her own small part, from developing a menu of foods to sustain people in zero gravity to setting up a communications link between the lunar module, mission control, and the White House to crafting the parachute that safely brought the astronauts home to the blue marble of Earth. Similarly, the construction of the Large Hadron Collider, which in 2012 detected the Higgs boson and helped solidify the Standard Model of particle physics, involved more than 10,000 scientists from over one hundred countries. We do not unravel the mysteries of our universe and our existence through the work of a single lone genius but rather through collaboration among many other individuals.

…

These leaders, and those following in their footsteps, were far more concerned with effecting their visions than with the price tag for doing so. Likewise, a community may decide to harvest a crop from a plot of land, even if this wastes a great deal of water. An army may want to win a war, even at the expense of a great number of soldiers. It doesn’t matter if it cost $10 billion to build the Large Hadron Collider, the scientists suggest, because the knowledge gained from it is priceless—it will lead us to innumerable other discoveries (but policy makers still worried about the cost). The truth, of course, is that our resources aren’t unlimited. Only in paradise do milk and honey flow aplenty. Throughout the ages, resources have been scarce, and our means for utilizing them have been limited.

…

The moon landing required: “Apollo 11 Mission Report,” NASA, n.d., http://www.hq.nasa.gov/alsj/a11/A11_PAOMissionReport.html. 10,000 scientists from over one hundred countries: Roger Highfield, “LHC: Scientists Jockey for Position in Race to Find the Higgs Particle,” Telegraph, September 10, 2008, http://www.telegraph.co.uk/news/science/large-hadron-collider/3351478/LHC-Scientists-jockey-for-position-in-race-to-find-the-Higgs-particle.html. “looks with grace upon each link”: Quoted in Moberg, “The Development of Protoecology in Sweden.” “Coordination ranges from tyrannical to democratic”: Charles E. Lindblom, The Market System: What It Is, How It Works, and What to Make of It (New Haven: Yale University Press, 2002), 20.

On the Future: Prospects for Humanity by Martin J. Rees

23andMe, 3D printing, air freight, Alfred Russel Wallace, AlphaGo, Anthropocene, Asilomar, autonomous vehicles, Benoit Mandelbrot, biodiversity loss, blockchain, Boston Dynamics, carbon tax, circular economy, CRISPR, cryptocurrency, cuban missile crisis, dark matter, decarbonisation, DeepMind, Demis Hassabis, demographic transition, Dennis Tito, distributed ledger, double helix, driverless car, effective altruism, Elon Musk, en.wikipedia.org, Geoffrey Hinton, global village, Great Leap Forward, Higgs boson, Hyperloop, Intergovernmental Panel on Climate Change (IPCC), Internet of things, James Webb Space Telescope, Jeff Bezos, job automation, Johannes Kepler, John Conway, Large Hadron Collider, life extension, mandelbrot fractal, mass immigration, megacity, Neil Armstrong, Nick Bostrom, nuclear winter, ocean acidification, off-the-grid, pattern recognition, precautionary principle, quantitative hedge fund, Ray Kurzweil, Recombinant DNA, Rodney Brooks, Search for Extraterrestrial Intelligence, sharing economy, Silicon Valley, smart grid, speech recognition, Stanford marshmallow experiment, Stanislav Petrov, stem cell, Stephen Hawking, Steven Pinker, Stuxnet, supervolcano, technological singularity, the scientific method, Tunguska event, uranium enrichment, Walter Mischel, William MacAskill, Yogi Berra

And what most compels our interest is the fascination of the individual discovery or insight. The cumulative advance of science requires new technology and new instruments—in symbiosis, of course, with theory and insight. Some instruments are ‘tabletop’ in scale. At the other extreme, the Large Hadron Collider at CERN in Geneva, 9 kilometres in diameter, is currently the world’s most elaborate scientific instrument. Its completion in 2009 generated enthusiastic razzmatazz and wide public interest, but at the same time questions were understandably raised about why such a large investment was being made in the seemingly recondite science of subnuclear physics.

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., 17 Kepler, Johannes, 131 Kepler project, 131–32 Khrushchev, Nikita, 17 kidneys sold for transplant, 71 killer robots, 101–2 The Knowledge: How to Rebuild Our World from Scratch (Dartnell), 217 Kolmogorov, Andrey, 172 Kolmogorov complexity, 172, 174, 193 Kuhn, Thomas, 205 Kurzweil, Ray, 81, 108 Large Hadron Collider, 206–7 Lee Sedol, 88 Lehrer, Tom, 17 Leonov, Alexey, 138 life: Earth as only known home of, 121; habitable planets and, 125, 126–27, 133, 135–36; origin of, 128–29, 135–36; universe fine-tuned for, 186, 197–98. See also aliens, intelligent life-long learning, 98–99 lifespan: ethics of extreme measures at end of, 69; extended by downloading thoughts and memories, 105; improvements so far achieved, 6; research on extension of, 79–82 Linde, Andrei, 188 lithium-ion batteries, 49 Lomborg, Bjørn, 42 Long Now Foundation, 224–25 long-term thinking, 227.

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., 98 optimism: about life’s destiny, 227; about moral progress, 6; about technological fixes for climate change, 42; about technology, 5, 225–26; machines surpassing human capabilities and, 108; Wells’s mix of anxiety and, 14 organ transplants, 71–72 origin of life, 128–29, 135–36 Our Final Hour (Rees), 12–13 ozone depletion, 31–32 pale blue dot, 10, 120, 133, 164 Paley, William, 197–98 pandemics: advances in microbiology and, 72; air travel and, 109; as global threat, 216, 217; magnitude of fallout from, 76–77 paradigm shifts, 205 Parfit, Derek, 116–17 Paris climate conference of 2015: Mission Innovation of, 48; papal encyclical and, 35; protocols following on, 219; temperature goal of, 41; uncertain results of, 44, 57 particle accelerators: Large Hadron Collider, 206–7; speculation on risks of, 110–16, 118; teams working on big projects of, 205–6 Pauli, Wolfgang, 209 Peierls, Rudolf, 222 personal identity, 105 pessimism, 226–27 Petrov, Stanislav, 18 Pfizer, abandoning neurological drugs, 212 philosophers of science, 203–5 physical reality: aliens with different perception of, 160, 190; human-induced threats and, 118; limited power of human minds and, 9, 189–90, 194; observable universe and, 181; our constricted concept of, 184.

Infinity in the Palm of Your Hand: Fifty Wonders That Reveal an Extraordinary Universe by Marcus Chown

Albert Einstein, Anton Chekhov, Apollo 11, Arthur Eddington, Carrington event, dark matter, Donald Trump, double helix, Eddington experiment, Edmond Halley, gravity well, horn antenna, Isaac Newton, Kickstarter, Large Hadron Collider, microbiome, Neil Armstrong, Richard Feynman, Search for Extraterrestrial Intelligence, space junk, Stephen Hawking, Turing machine

When the sponge is stretched upwards at high tide, it sucks water out of the well, lowering its level; and, when the sponge is scrunched back down at high tide, it squeezes water back into the well, raising its level. A more contemporary example of such rock tides comes from the 26.7-kilometer subatomic racetrack of the Large Hadron Collider (LHC) near Geneva. Around this ring, counter-rotating beams of protons are smashed together at 99.999999 percent of the speed of light. In July 2012, they created the fabled Higgs particle, the “quantum” of the Higgs field, which endows all other subatomic particles with mass. The LHC occupies the same tunnel as an earlier accelerator known as the Large Electron-Positron Collider (LEP).

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Speculations range from as-yet-undiscovered subatomic particles to fridge-sized black holes surviving from the earliest moments of the Big Bang to relics from the future in which time runs backwards (seriously!).2 If the dark matter is made of the former, it may at this moment literally be in the air all around you. There was a hope that a candidate subatomic particle might turn up at the Large Hadron Collider, the giant particle accelerator near Geneva in Switzerland. But so far, no joy. In idle moments, I daydream about whether there might not be dark stars, dark planets, and dark life, and that the real reason a fifty-year search for extraterrestrial intelligence has drawn a blank is that the dark stuff is where all the action is, with the chaos of galactic commerce going on all around us.

…

In the 1950s, radio astronomers, using equipment adapted from wartime radar, discovered that the radio emission observed from some galaxies came not from the central knot of stars, as expected, but, mysteriously, from giant, radio-emitting lobes on either side of the galaxy. In the early 1980s, the thread-thin jets that are feeding the lobes were imaged for the first time by the Very Large Array of radio dishes in New Mexico. They mock our puny attempts at accelerating matter. Whereas the multi-billion-euro Large Hadron Collider can whip a nanogram or so of matter to within a whisker of the speed of light, nature’s cosmic jets can accelerate to similar speeds many times the mass of the sun each year. The jets help to control the structure of their parent galaxies because, in the inner regions, where they are still fast and powerful, they drive out all the gaseous raw material of stars, snuffing out star formation.

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

The Hubble’s planned successor, the James Webb space telescope, basically a large parabolic mirror, will transmit to Earth up to 3.5 million bytes per second. The Large Hadron Collider lies along the French-Swiss border and is the world’s largest particle accelerator. On average it generates half a billion bytes of data every second. That’s every second of every year, and there are 31 million seconds every year. CERN, the European Organization for Nuclear Research that built and maintains the Large Hadron Collider, created a LHC Computing Grid, distributing its massive data to servers in thirty-four countries and allowing scientists worldwide to access and analyze that data.

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, 156–57 job scheduling problem, 56–57, 87 Johnson, Pete, 24 Journal of the Association of Computing Machinery, 118–19 Karmarkar, Narendra, 70 Karp, Richard, 6–7, 55–58, 77–78 Kasner, Edward, 34 Katrina (hurricane), 161 Kempe, Alfred, 42 Kepler, Johannes, 20 Khachiyan, Leonid, 69–70 Khot, Subhash, 104 al-Khwārizmī, Muhammad ibn Mūsā, 32 kidney exchange problem, 64–65 Kiev University, 84 Kleene, Stephen, 75 Knuth, Donald, 58 Kolmogorov, Andrey, 79, 80–83, 84, 167 Kolmogorov complexity, 83 Komsomol, 85 language, sentences in, 75, 75–76 language translation, 18, 23 Large Hadron Collider, 158 law enforcement, and P = NP, 25–26 laws of motion, 20–21 Levin, Leonid, 6, 79, 83–85 LHC Computing Grid, 158 Liapunov, Alexy, 79 liar’s paradox, 110–13 linear programming, 69–70, 70 linguistics, context-free grammar in, 75, 75–76 logical functions: circuit complexity of, 79–80; for cliques, 53–54; as friendship diagram, 55; satisfiable, 54, 79 Loren, Sophia, and Kevin Bacon, 31–32 Los Alamos National Lab, 149 machine learning, 22, 22–23, 159 Major League Baseball, 16–19 map coloring: explanation of problem, 42–43, 43; heuristic for, 92–96, 93, 94, 95, 96; as NP, 46 market equilibrium, 49 marketing, P = NP and, 27 Martian rule, 86–87 Marxism, and probability theory, 81 Massachusetts Institute of Technology, 85 matchmaking, 33–36, 34, 35, 117–18 mathematics, NP problems in, 49–50 math puzzles, usefulness of, 4–5 Matsuoka, Yoky, 5–6, 165 max-cut problem, 45, 46 McCulloch, Warren, 75 McLean, Malcolm, 160 medicine, and P = NP, 14–15 Merkle, Roger, 127 messenger RNA (mRNA), 47–48 Meyer, Albert, 85 microprocessors: capabilities of, 90–92; parallel, 155, 156–57; speed of, 156 microwave attack, 107 Milgram, Stanley, 30–31 Millennium Problems, 7, 14 min-cut problem, 44, 44–45 Minesweeper, 61–62, 62 minimum energy states, 48 MMORPG (massively multiplayer online role-playing game), 66, 66–67 Moore, Gordon, 156 Moore’s law, 91, 92, 156 Moscow State University, 80, 84 Mulmuley, Ketan, 121 music, automated creation of, 24–25 Nash, John, 49 National Center for Supercomputing Applications (NCSA), 13–14 natural proofs, 118 NC (Nick’s Class) problems, 157–58 Neumann, John von, 6, 85–86 neural nets, creation of, 75 Nevada, neighbors of, 42–43, 43 Newton, Isaac, 20–21 New York to Chicago, possible routes, 7–8 Nobel Prize, for Nash, 49 NOT gates, 79, 114, 114, 116–17 Novikov, Pyotr, 79 Novosibirsk State University, 83–84 NP (nondeterministic polynomial time): in biology, 47–48; circuit size in, 116; in economics, 49; examples of, 46; in mathematics, 49–50; meaning of, ix, 4; in physics, 48, 48; reduction to satisfiability, 54–55 NP-complete problems: accepting unsolvability of, 107–8; approximation for, 99–104, 100, 101, 102, 103; brute force approach to, 90–92, 91; categorizing, 59; changing the problem, 105–7; commonality of, 162; examples of, 59–65; and factoring, 140–41; heuristics for, 92–97; Levin’s work with, 84–85; naming of, 58; problems of unknown status, 65–70; quantum algorithms for, 146–47; small solutions for, 97, 97–99, 98; Sudoku as, 135–36 NP = NC, 157–58 number theory, 68 observation: entanglement and, 147; in outcome, 144 Occam’s razor, 19–23 100 factorial (100!)

The Search for Superstrings, Symmetry, and the Theory of Everything by John Gribbin

Albert Einstein, Arthur Eddington, complexity theory, dark matter, Dmitri Mendeleev, Ernest Rutherford, Fellow of the Royal Society, Higgs boson, Isaac Newton, Large Hadron Collider, Murray Gell-Mann, Richard Feynman, Schrödinger's Cat, Stephen Hawking

We may not have to wait too long to find out just how good a theory M-theory really is, and whether it is indeed the long sought-after theory of everything. The kind of energies needed to probe the predictions of M-theory should be achieved at the latest high energy particle accelerator, the Large Hadron Collider (LHC), which is expected to begin operating at CERN in the middle of the first decade of the twenty-first century. This follows, coincidentally, the pattern in which major developments in string theory have occurred in the middle of each of three successive decades—the 1970s, the 1980s, and the 1990s.

…

By choosing a specific value of the average SUSY mass, the CERN team can make the three lines cross at a point; the value of the SUSY mass needed to do this trick is only a little higher than the energies so far reached in particle colliders, at around 1,000 GeV. This is excellent news, since the next generation of particle accelerator, the Large Hadron Collider at CERN, will be able to probe precisely this energy range, testing the theory of supersymmetry (and doing some other neat tricks discussed in Appendix II). If all the calculations are correct, and SUSY particles do exist, then they may be discovered before the year 2010. And if those accelerators fail to find SUSY particles with masses around 1,000 GeV?

…

Existing accelerators at Brookhaven can reach 5 GeV per nucleon, using silicon-28. With new booster systems (sometimes known as ‘pre-accelerators’), both labs will soon be able to handle heavier nuclei, including lead, but only at about the same relativistic factors. But by the end of the 1990s Brookhaven's Relativistic Heavy Ion Collider (RHIC) and CERN's Large Hadron Collider (LHC) should both become operational. RHIC will run at about 200 GeV per nucleon, while the LHC should reach 300 GeV per nucleon. These are equivalent to energy densities of 3 GeV per fm3 at a temperature of 200 MeV for RHIC, and 5 GeV per fm3 at 220 MeV for the LHC, both well in the range where, theory says, the quark-gluon plasma should form.

The Greatest Story Ever Told--So Far by Lawrence M. Krauss

Alan Greenspan, Albert Einstein, complexity theory, cosmic microwave background, cosmological constant, dark matter, Ernest Rutherford, Higgs boson, How many piano tuners are there in Chicago?, Isaac Newton, Large Hadron Collider, Magellanic Cloud, Murray Gell-Mann, Plato's cave, public intellectual, RAND corporation, Richard Feynman, Richard Feynman: Challenger O-ring, the scientific method, time dilation

To make matters worse, it would take more fuel than there is mass in the galaxy to power a single such voyage, at least using conventional rockets of the type now in use. Nevertheless, science fiction woes aside, “time dilation”—as the relativistic slowing of clocks is called with regard to moving objects—is very much real, and very much experienced every day here on Earth. At high-energy particle accelerators such as the Large Hadron Collider, for example, we regularly accelerate elementary particles to speeds of 99.9999 percent of the speed of light and rely on the effects of relativity when exploring what happens. But even closer to home, relativistic time dilation has an impact. We on Earth are all bombarded every day by cosmic rays from space.

…

The Tevatron did garner one great success, the long-anticipated discovery, in 1995, of the mammoth top quark, 175 times the mass of the proton, and the most massive particle yet discovered in nature. With no clear competition therefore, within fourteen months of the demise of the SSC the CERN council approved the construction of a new machine, the Large Hadron Collider, in the LEP tunnel. Design and development of the machine and detectors would take some time to complete, so the LEP machine would continue to operate in the tunnel for almost another six years before having to close down for reconstruction. It would then take almost another decade to complete construction of the machine and the particle detectors to be used in the search for the Higgs and/or other new physics.

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., 12 dimensional analysis, 36 Dirac, Paul Adrien Maurice, 85, 91–95 antiparticle discovery by, 95, 97, 114, 115 combination of quantum mechanics and relativity by, 92, 95, 151 Einstein on, 91 electron equation of, 92–94, 99, 114 Feynman compared with, 97–98 Feynman’s first meeting with, 92 Feynman’s research based on, 99 mathematical prediction of new particle by, 93–94, 143 personality of, 91–92, 98 quantum theory of radiation and, 98, 99 Dirac equation, 92–94 displacement current, 37 double-slit experiment with light, 74–76, 77, 88 Dyson, Freeman, 85, 106, 235 E Eddington, Sir Arthur Stanley, 135 Eightfold Way (Gell-Mann), 193–94 Einstein, Albert, 4, 42, 49–68 background of, 46 Bose-Einstein condensation research by, 185–86 clocks relative to moving objects (time dilation) research of, 58–61 creativity and intellectual confidence of, 52 Dirac described by, 91 Galileo-Maxwell paradox resolution by, 49–54, 58, 64–65 General Theory of Relativity of, 10, 42, 68, 85, 110, 126, 295 gravity and, 114 inferences about real world using measurements and, 61–65 letter to President Roosevelt from, 129 Minkowski’s four-dimensional “space-time” theory and, 66–68, 71 Planck’s relationship with, 80–81 relativity discovery of, 95 ruler measurement example of relativity and, 65–67 space and time theory of, 55–58, 66, 68 Special Theory of Relativity of, 68, 80 electric charges Faraday’s research on, 25–30, 37–38, 68, 195 quantum electrodynamics (QED) and symmetry of, 106, 107 electric fields, Farady’s visualization of action of, 27–30, 193–94 electricity, Maxwell’s theory of magnetism and, 36–39, 48, 94, 218, 219 electromagnetic waves calculation of speed of, 42, 50–51 Faraday cage shield against, 195 Maxwell on light as, 42, 219 Maxwell’s discovery of, 41, 42, 46, 74 as particles, 81, 82 superconductors and different polarizations of, 199–200 electromagnetism gauge symmetry in quantum theory of, 111 Maxwell’s research on, 39–43, 46, 50–51, 68, 74, 109 electrons Dirac’s equation describing, 92–94 electric charge configurations of, 93–94 Feynman’s measurement of trajectories of, 100–102 mathematical expression of wave function of, 77 spin angular momentum of, 127, 164 spin configurations of, 93 Young’s double-slit experiment with beams of, 75–77 electroweak symmetry, 254, 277, 282, 283–84, 285, 287, 290, 294, 296–97 electroweak theory, 229, 278 publications questioning, 227 validation of, 228, 259 electroweak unification, 216–17, 218, 222, 231, 250, 259, 278 Englert, François, 206–7, 211, 271 European Organization for Nuclear Research (CERN), 225, 236 as dominant particle physics laboratory, 259, 262 Gargamelle detector at, 223–24, 225 Large Electron-Positron (LEP) Collider at, 262–63 Large Hadron Collider (LHC) at, 61, 263–74, 275, 284, 285, 286–87, 299 proton accelerator at, 222–23, 251 Super Proton Synchrotron (SPS) at, 251–52, 260, 262 evolution, 3, 5, 20 exclusion principle (Pauli), 123, 127 F Faraday, Michael, 24–30, 38 background of, 24–25 impact of discoveries of, 30, 31, 46, 68, 109 magnetic induction discovery of, 26–27, 30, 36 Maxwell’s meetings with, 36 Maxwell’s research and, 37, 38 research on electric charges and magnets by, 25–30, 37–38, 68, 195 visualization of action of fields by, 27–30, 193–94 Faraday cage, 195 Feenberg, Eugene, 169 Fermat, Pierre de, 98–99 Fermi, Enrico, 125–32 artificial radioactivity and, 128 background of, 126–27 experimental approach to physics used by, 129–30, 142 impact of research of, 125–26 neutrino named by, 123, 127, 130 neutron decay theory of, 127–29, 130–32, 136, 142, 143, 145–46, 149 nuclear research in Manhattan Project and, 129 potential dangers in releasing energy of atomic nucleus and, 129 statistical mechanics established by, 127 weak interaction theory of, 161, 162, 164 Yang’s work with, 153 Yukawa’s research and, 143, 144, 145–46 Fermi interaction, 136 Fermilab (Fermi National Accelerator Laboratory, Batavia, Illinois), 31, 251, 261, 262–63 fermions, 155, 185, 186, 233, 282, 283 Fermi Problems, 130 Feynman, Richard, 85, 97–106, 125, 159, 160, 228 antiparticles and, 100, 102 atomic bomb research of, 134 Bethe’s approach and, 134 Bjorken’s research on quarks and, 233 Block’s research on weak interaction and, 157–58 Dirac compared with, 97–98 Dirac’s first meeting with, 92 Dirac’s research used by, 99 electron trajectory measurement in time and, 100–102, 130 quantum electrodynamics (QED) and, 99, 102–6, 142, 175, 221, 235 research approach used by, 175, 245 on understanding quantum mechanics, 71 weak interaction research of, 159, 163–64 Fizeau, Hippolyte, 42 Fourier analysis, 126 Franklin, Benjamin, 170–71 Friedman, Jerry, 160, 232–33 G Galileo Galilei, 5, 21, 45–48 Catholic Church’s trial of, 45, 47 Einstein on Galileo-Maxwell paradox, 48–54, 58, 64–65 motion and rest state theory of, 45–48, 49, 70, 97, 168, 245 gamma rays, 116 neutron mass measurement using, 119 Rutherford’s discovery of, 119–20 Gargamelle detector, CERN, 223–24, 225 Garwin, Dick, 160 gauge bosons, 214, 217, 233, 254, 277, 278 gauge invariance, 109, 172, 198, 199, 228 gauge symmetry chessboard analogy to explain conservation of energy in, 108–9 description of, 108 differences in philosophical viewpoints on, 109–10 quantum electrodynamics and, 111–12 understanding nature of reality using, 110 Weyl’s naming of, 110–11 gauge transformation, 109 Geiger, Hans, 116, 118 Gell-Mann, Murray Glashow’s work with, 178 quarks and, 163, 193–94, 231–32, 233–34, 236, 240 scale equations of, 237 symmetry scheme of, 193, 214 weak interaction research of, 163–64 Yang-Mills theory and, 240–41 General Theory of Relativity (Einstein), 10, 42, 68, 85, 110, 126, 295 Genesis, 19, 43 Georgi, Howard, 276–77, 278, 279 Gilbert, Walter, 204–5 Gladstone, William, 26 Glashow, Sheldon, 177–79 approach to research used by, 178 background of, 177–78, 212 CERN research and, 252 electroweak unification and, 216–17, 218, 222, 278 Grand Unification and, 277, 279 on Higgs’s research, 207, 254, 276 Krauss’s career and, 213, 214 neutral currents and, 222, 225, 234 quarks and, 234, 241 Scottish Universities Summer School courses from, 203–4 weak interaction research of, 178–79, 207, 219, 223, 225, 276–77 Weinberg’s research and, 212–13, 218 Gold, Tommy, 113, 121 Goldstone, Jeffrey, 188, 203, 204, 206, 214 Goldstone bosons, 206, 214–15, 217 Grand Unified Theory (GUT), 277–79, 282–83, 290, 291, 292–93, 294 gravity dimensional analysis of, 36 Einstein’s research on, 114 Newton’s research on, 5, 27–28, 38, 48 quantum theory of, 110 Greenberg, Oscar, 233, 240 Gross, David, 235–41, 277 asymptotic freedom discovery of, 238–41, 245 background of, 235 Gell-Mann’s influence on, 236 quantum chromodynamics and, 241 research on quarks by, 236–37 scaling research of, 237–39 Yang-Mills theory and, 239, 240–41 group theory, 276 Guralnik, Gerald, 207 Gürsey, Feza, 123 Guth, Alan, 290, 291–92 H Hagen, C.

Uncharted: How to Map the Future by Margaret Heffernan

"World Economic Forum" Davos, 23andMe, Affordable Care Act / Obamacare, Airbnb, Alan Greenspan, Anne Wojcicki, anti-communist, Atul Gawande, autonomous vehicles, banking crisis, Berlin Wall, Boris Johnson, Brexit referendum, chief data officer, Chris Urmson, clean water, complexity theory, conceptual framework, cosmic microwave background, creative destruction, CRISPR, crowdsourcing, data science, David Attenborough, discovery of penicillin, driverless car, epigenetics, Fall of the Berlin Wall, fear of failure, George Santayana, gig economy, Google Glasses, Greta Thunberg, Higgs boson, index card, Internet of things, Jaron Lanier, job automation, Kickstarter, Large Hadron Collider, late capitalism, lateral thinking, Law of Accelerating Returns, liberation theology, mass immigration, mass incarceration, megaproject, Murray Gell-Mann, Nate Silver, obamacare, oil shale / tar sands, passive investing, pattern recognition, Peter Thiel, prediction markets, RAND corporation, Ray Kurzweil, Rosa Parks, Sam Altman, scientific management, Shoshana Zuboff, Silicon Valley, smart meter, Stephen Hawking, Steve Ballmer, Steve Jobs, surveillance capitalism, TED Talk, The Signal and the Noise by Nate Silver, Tim Cook: Apple, twin studies, University of East Anglia

This paradoxical combination of super-human scientific detail with human improvisation requires a mindset that is both open to change, to disconfirmation and correction, but which can function in a discipline that demands absolute precision. Such punctilious flexibility is a CERN hallmark, as critical to the institution’s management as its science. As director general between 1994 and 1998, Christopher Llewellyn-Smith led one of the most ambitious phases of CERN’s existence: the funding of the Large Hadron Collider. In 1983, the W and Z bosons had been discovered at CERN – a discovery for which Carlo Rubbia and his colleague Simon van der Meer were awarded the Nobel Prize. This proved the existence of bosons (a particle, named after scientists Bose and Einstein) and spurred the hunt for the Higgs boson, as first proposed by Peter Higgs in 1964.

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But it didn’t explain the foundational belief at CERN: that great, valuable discoveries derive not from planning but from adhering to a total commitment to the pursuit of new knowledge. Cleaving to that guiding principle while refusing to constrain the work with guarantees made the gigantic cost of what became the Large Hadron Collider a tough sell for Llewellyn-Smith. Billions of dollars – and no forecast return? That CERN has generated valuable spin-offs, however, is unarguable. Today, smaller accelerators of the kind pioneered at CERN are used in the semiconductor industry, for sterilisation of food, sewage and in hospitals, for non-destructive testing of materials and in cancer therapies.

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Shared ambition drives avid collaboration: not to fall short, not to let each other down, to bring your best with a passion to do together something that could never be done alone. Everyone has expertise but everyone also needs help for the project to yield results. So much of the talk at CERN is so abstract – invisible particles, complex theories, unproven hypotheses, amorphous organisational structures – that it is a surprise to see, at the entrance to the Large Hadron Collider, a wall of giant spanners. The test of pure theory turns out to be mightily mechanical and, until DUNE is up and running, the LHC is the biggest single piece of machinery in the world. Inside it, proton beams (and sometimes heavy ion beams) are aimed at each other to produce collisions. These can’t be seen but pass through detectors that send signals to one thousand computers at the rate of millions of gigabytes per second.

Learning Scikit-Learn: Machine Learning in Python by Raúl Garreta, Guillermo Moncecchi

computer vision, Debian, Everything should be made as simple as possible, Higgs boson, Large Hadron Collider, natural language processing, Occam's razor, Silicon Valley

See more on his website at http://www.hjortgaard.net/. Noel Dawe is a Ph.D. student in the field of Experimental High Energy Particle Physics at Simon Fraser University, Canada. As a member of the ATLAS collaboration, he has been a part of the search team for the Higgs boson using high energy proton-proton collisions at CERN's Large Hadron Collider (LHC) in Geneva, Switzerland. In his free time, he enjoys contributing to open source scientific software, including scikit-learn. He has developed a significant interest toward Machine learning, to the benefit of his research where he has employed many of the concepts and techniques introduced in this book to improve the identification of tau leptons in the ATLAS detector, and later to extract the small signature of the Higgs boson from the vast amount of LHC collision data.

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Then we use this data to train a model that will predict the same target class for new unseen instances. Supervised learning methods are nowadays a standard tool in a wide range of disciplines, from medical diagnosis to natural language processing, image recognition, and searching for new particles at the Large Hadron Collider (LHC). In this chapter we will present several methods applied to several real-world examples by using some of the many algorithms implemented in scikit-learn. This chapter does not intend to substitute the scikit-learn reference, but is an introduction to the main supervised learning techniques and shows how they can be used to solve practical problems.

We Are the Nerds: The Birth and Tumultuous Life of Reddit, the Internet's Culture Laboratory by Christine Lagorio-Chafkin

"Friedman doctrine" OR "shareholder theory", 4chan, Aaron Swartz, Airbnb, Amazon Web Services, Bernie Sanders, big-box store, bitcoin, blockchain, Brewster Kahle, Burning Man, compensation consultant, crowdsourcing, cryptocurrency, data science, David Heinemeier Hansson, digital rights, disinformation, Donald Trump, East Village, eternal september, fake news, game design, Golden Gate Park, growth hacking, Hacker News, hiring and firing, independent contractor, Internet Archive, Jacob Appelbaum, Jeff Bezos, jimmy wales, Joi Ito, Justin.tv, Kickstarter, Large Hadron Collider, Lean Startup, lolcat, Lyft, Marc Andreessen, Mark Zuckerberg, medical residency, minimum viable product, natural language processing, Palm Treo, Paul Buchheit, Paul Graham, paypal mafia, Peter Thiel, plutocrats, QR code, r/findbostonbombers, recommendation engine, RFID, rolodex, Ruby on Rails, Sam Altman, Sand Hill Road, Saturday Night Live, self-driving car, semantic web, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, slashdot, Snapchat, Social Justice Warrior, social web, South of Market, San Francisco, Startup school, Stephen Hawking, Steve Bannon, Steve Jobs, Steve Wozniak, Streisand effect, technoutopianism, uber lyft, Wayback Machine, web application, WeWork, WikiLeaks, Y Combinator

. | Internet--Social aspects Classification: LCC HM743.R447 L34 2018 | DDC 302.30285--dc23 LC record available at https://lccn.loc.gov/2018015680 ISBNs: 978-0-316-43537-6 (hardcover), 978-0-316-43536-9 (ebook) E3-20180507-DANF Contents Cover Title Page Copyright Author’s Note Part I This Guy Has No Shame How to Start a Startup Not Your Standard Fixed-Point Combinator Front Page of the Internet It’s Online Hell Summer How to Act Like a Real Adult Rounding Error The Algorithm and the Cupboard You Are Making Us Sound Stupid We Are the Nerds The Deal Part II Chasing That Moment Millionaires’ Ball You Aren’t a Bank Teller A Moment Before Dying The Physicist, the Information Cowboy, the Hacker, and the Troll Mister Splashy Pants and the Large Hadron Collider Benign Neglect Tools, Yo Part III Take Me Home The Ones That Got Away Geek Woodstock Exodus and Ill Will Free-Speech Sandbox Blackout Meet Your New CEO NOT BAD! The Id Part IV Omniscient Guardians of the Depths The Internet Bus The 117th Boston Marathon Money on the Mind Every Man Is Responsible for His Own Soul Tiny Boxes Unbelievable Because It’s So Weird Closer to Yes The Poltergeist 10 Part V Revenge and Revenge Porn Fame and Its Inverse AMAgeddon The Return of Steve Fuzzy Approach “Serendipity” and “Bullshit” r/The_Donald Spezgiving What’s Good for the United States This Is My Whole Life Reddit 4.0 Salesman Emeritus Live from Hollywood All Together Now Photos Acknowledgments Sources Notes Newsletters Author’s Note I woke up in Austin, Texas, on March 13, 2011, to an email from Alexis Ohanian.

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And thousands of young hackers and scientists, cut from a similar cloth to Swartz’s, posted often on related issues: copyright, government secrets, and individuals’ privacy rights. Doing so was safe here, among like-minded peers, and behind a pseudonymous account name. Mister Splashy Pants and the Large Hadron Collider Perhaps as compensation for the previous year’s anticlimactic post-acquisition Halloween, over the messy first year of Reddit’s life within Condé Nast, Ohanian and Huffman had learned how to celebrate. In August 2007, the crew flew back to Boston for Slowe and Sakillaris’s actual big Greek wedding celebration, in which Huffman and Ohanian were groomsmen.

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Its hotness algorithm, plus its karma tracking, were dual secret engines, chugging away out of the awareness of all but the most avid technologists and programmers but starting to influence more and more of the Internet and popular culture. * * * Around the globe on September 10, 2008, on the front pages of newspapers were reports that the Large Hadron Collider, an ultra-powerful particle collider in the world’s most complex laboratory, the European Organization for Nuclear Research, was complete, and had begun conducting initial tests. These news stories were geek catnip: This was the single largest machine on the planet, assembled over the course of a decade in a bunker underground.

The Half-Life of Facts: Why Everything We Know Has an Expiration Date by Samuel Arbesman

Albert Einstein, Alfred Russel Wallace, Amazon Mechanical Turk, Andrew Wiles, Apollo 11, bioinformatics, British Empire, Cesare Marchetti: Marchetti’s constant, Charles Babbage, Chelsea Manning, Clayton Christensen, cognitive bias, cognitive dissonance, conceptual framework, data science, David Brooks, demographic transition, double entry bookkeeping, double helix, Galaxy Zoo, Gregor Mendel, guest worker program, Gödel, Escher, Bach, Ignaz Semmelweis: hand washing, index fund, invention of movable type, Isaac Newton, John Harrison: Longitude, Kevin Kelly, language acquisition, Large Hadron Collider, life extension, Marc Andreessen, meta-analysis, Milgram experiment, National Debt Clock, Nicholas Carr, P = NP, p-value, Paul Erdős, Pluto: dwarf planet, power law, publication bias, randomized controlled trial, Richard Feynman, Rodney Brooks, scientific worldview, SimCity, social contagion, social graph, social web, systematic bias, text mining, the long tail, the scientific method, the strength of weak ties, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Tyler Cowen, Tyler Cowen: Great Stagnation

Elaborating on several of the themes already discussed, what he looks for are situations in which there are cases of false positives, instances where a finding is “discovered” even though it’s not actually real. In a wonderful bit from The Daily Show, correspondent John Oliver interviews Walter Wagner, a science teacher who tried to prevent, via lawsuit, the Large Hadron Collider from being turned on. The Large Hadron Collider is a massive particle accelerator capable of generating huge amounts of energy, and Wagner was concerned that it could create a black hole capable of destroying the earth. When Oliver presses Wagner on the chances that the world will be destroyed, he states that “the best we can say right now is about a one in two chance.”

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., 174 Godwin’s law, 105 Goldbach’s Conjecture, 112–13 Goodman, Steven, 107–8 Gould, Stephen Jay, 82 grammar: descriptive, 188–89 prescriptive, 188–89, 194 Granovetter, Mark, 76–78 Graves’ disease, 111 Great Vowel Shift, 191–93 Green, George, 105–6 growth: exponential, 10–14, 44–45, 46–47, 54–55, 57, 59, 130, 204 hyperbolic, 59 linear, 10, 11 Gumbel, Bryant, 41 Gutenberg, Johannes, 71–73, 78, 95 Hamblin, Terry, 83 Harrison, John, 102 Hawthorne effect, 55–56 helium, 104 Helmann, John, 162 Henrich, Joseph, 58 hepatitis, 28–30 hidden knowledge, 96–120 h-index, 17 Hirsch, Jorge, 17 History of the Modern Fact, A (Poovey), 200 Holmes, Sherlock, 206 homeoteleuton, 89 Hooke, Robert, 21, 94 Hull, David, 187–88 human anatomy, 23 human computation, 20 hydrogen, 151 hyperbolic growth rate, 59 idiolect, 190 impact factors, 16–17 inattentional blindness (change blindness), 177–79 India, 140–41 informational index funds, 197 information transformation, 43–44, 46 InnoCentive, 96–98, 101, 102 innovation, 204 population size and, 135–37, 202 prizes for, 102–3 simultaneous, 104–5 integrated circuits, 42, 43, 55, 203 Intel Corporation, 42 interdisciplinary research, 68–69 International Bureau of Weights and Measures, 47 Internet, 2, 40–41, 53, 198, 208, 211 Ioannidis, John, 156–61, 162 iPhone, 123 iron: magnetic properties of, 49–50 in spinach, 83–84 Ising, Ernst, 124, 125–26, 138 isotopes, 151 Jackson, John Hughlings, 30 Johnson, Steven, 119 Journal of Physical and Chemical Reference Data, 33–35 journals, 9, 12, 16–17, 32 Kahneman, Daniel, 177 Kay, Alan, 173 Kelly, Kevin, 38, 46 Kelly, Stuart, 115 Kelvin, Lord, 142–43 Kennaway, Kristian, 86 Keynes, John Maynard, 172 kidney stones, 52 kilogram, 147–48 Kiribati, 203 Kissinger, Henry, 190 Kleinberg, Jon, 92–93 knowledge and facts, 5, 54 cumulative, 56–57 erroneous, 78–95, 211–14 half-lives of, 1–8, 202 hidden, 96–120 phase transitions in, 121–39, 185 spread of, 66–95 Koh, Heebyung, 43, 45–46, 56 Kremer, Michael, 58–61 Kuhn, Thomas, 163, 186 Lambton, William, 140 land bridges, 57, 59–60 language, 188–94 French Canadians and, 193–94 grammar and, 188–89, 194 Great Vowel Shift and, 191–93 idiolect and, 190 situation-based dialect and, 190 verbs in, 189 voice onset time and, 190 Large Hadron Collider, 159 Laughlin, Gregory, 129–31 “Laws Underlying the Physics of Everyday Life Really Are Completely Understood, The” (Carroll), 36–37 Lazarus taxa, 27–28 Le Fanu, James, 23 LEGO, 184–85, 194 Lehman, Harvey, 13–14, 15 Leibniz, Gottfried, 67 Lenat, Doug, 112 Levan, Albert, 1–2 Liben-Nowell, David, 92–93 libraries, 31–32 life span, 53–54 Lincoln, Abraham, 70 linear growth, 10, 11 Linnaeus, Carl, 22, 204 Lippincott, Sara, 86 Lipson, Hod, 113 Little Science, Big Science (Price), 13 logistic curves, 44–46, 50, 116, 130, 203–4 longitude, 102 Long Now Foundation, 195 long tails: of discovery, 38 of expertise, 96, 102 of life, 38 of popularity, 103 Lou Gehrig’s disease (ALS), 98, 100–101 machine intelligence, 207 Magee, Chris, 43, 45–46, 56, 207–8 magicians, 178–79 magnetic properties of iron, 49–50 Maldives, 203 Malthus, Thomas, 59 mammal species, 22, 23, 128 extinct, 28 manuscripts, 87–91, 114–16 Marchetti, Cesare, 64 Marsh, Othniel, 80–81, 169 mathematics, 19, 51, 112–14, 124–25, 132–35 Matthew effect, 103 Mauboussin, Michael, 84 Mayor, Michel, 122 McGovern, George, 66 McIntosh, J.

Age of Discovery: Navigating the Risks and Rewards of Our New Renaissance by Ian Goldin, Chris Kutarna

"World Economic Forum" Davos, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, Airbnb, Albert Einstein, AltaVista, Asian financial crisis, asset-backed security, autonomous vehicles, banking crisis, barriers to entry, battle of ideas, Bear Stearns, Berlin Wall, bioinformatics, bitcoin, Boeing 747, Bonfire of the Vanities, bread and circuses, carbon tax, clean water, collective bargaining, Colonization of Mars, Credit Default Swap, CRISPR, crowdsourcing, cryptocurrency, Dava Sobel, demographic dividend, Deng Xiaoping, digital divide, Doha Development Round, double helix, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, epigenetics, experimental economics, Eyjafjallajökull, failed state, Fall of the Berlin Wall, financial innovation, full employment, Galaxy Zoo, general purpose technology, Glass-Steagall Act, global pandemic, global supply chain, Higgs boson, Hyperloop, immigration reform, income inequality, indoor plumbing, industrial cluster, industrial robot, information retrieval, information security, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invention of the printing press, Isaac Newton, Islamic Golden Age, Johannes Kepler, Khan Academy, Kickstarter, Large Hadron Collider, low cost airline, low skilled workers, Lyft, Mahbub ul Haq, Malacca Straits, mass immigration, Max Levchin, megacity, Mikhail Gorbachev, moral hazard, Nelson Mandela, Network effects, New Urbanism, non-tariff barriers, Occupy movement, On the Revolutions of the Heavenly Spheres, open economy, Panamax, Paris climate accords, Pearl River Delta, personalized medicine, Peter Thiel, post-Panamax, profit motive, public intellectual, quantum cryptography, rent-seeking, reshoring, Robert Gordon, Robert Metcalfe, Search for Extraterrestrial Intelligence, Second Machine Age, self-driving car, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart grid, Snapchat, special economic zone, spice trade, statistical model, Stephen Hawking, Steve Jobs, Stuxnet, synthetic biology, TED Talk, The Future of Employment, too big to fail, trade liberalization, trade route, transaction costs, transatlantic slave trade, uber lyft, undersea cable, uranium enrichment, We are the 99%, We wanted flying cars, instead we got 140 characters, working poor, working-age population, zero day

These academic migrants spread and connect the world’s brain power. Cross-border research collaboration, which accounted for less than one-tenth of all published papers in 1995, now accounts for almost one-third.43 The most heavily collaborated paper in academic history—a May 2015 physics paper based on research at the Large Hadron Collider in Geneva—counted 5,154 co-authors from all over the world.44 Curing cancer is now a 24-hour research effort by virtual teams from leading labs around the world. At the end of their day, researchers hand off their latest labors to the next time zone; the next morning, they pick up where their foreign colleagues left off.

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That’s because our computer-driven devices keep getting better and better at collecting the data researchers want—in Lintott’s case, images of distant galaxies—but they are still quite poor at recognizing the patterns we’re looking for or at separating meaningful signals from meaningless noise. The result is a massive, ever-growing backlog of data-to-be-studied-someday. CERN’s Large Hadron Collider in Switzerland produces nearly a gigabyte of new data every second about how fundamental particles behave.24 The world’s DNA sequencing machines together churn out one to two gigabytes per second about how our genes work.25 At NASA, data floods from the sky: its various missions generate about 150 gigabytes per second of new observations about our universe.26 (For comparison, in 2015 Facebook’s 1.5 billion-plus users together uploaded about five gigabytes per second.

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OldWeather asks the public’s help to transcribe ships’ logs going back to the mid-nineteenth century (old logs form the most complete set of long-term climate data in existence, but like ancient Greek texts in Aldus’s day, they lie scattered, gathering dust, in maritime museums and archives the world over). Ancient Lives assembles archeology buffs to help translate thousands of 2,000-year-old Egyptian papyri (no knowledge of hieroglyphics required). Higgs Hunters invites anyone to help sift through data from the Large Hadron Collider for more evidence of the Higgs boson and other exotic particles. Zooniverse is only one citizen science platform. Others include Tomnod (tomnod.com), where volunteers scour satellite photos to help stop illegal fishing or search for missing aircraft, and EyeWire (eyewire.org), a game that helps to map the human brain.

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

Although Nikolai Kondratiev was the first to study the economic effects of technology on prices, wages, interest rates, industrial production and consumption in 1925, Joseph Schumpeter was responsible for their entry into academia. 7In this paper, the model is driven by technological change that arises from intentional investment decisions made by profit-maximizing agents. 8See “A Failed Philosopher Tries Again.” 9(i) LatAm sovereign debt crisis - 1982, (ii) Savings and loans crisis - 1980s, (iii) Stock market crash - 1987, (iv) Junk bond crash - 1989, (v) Tequila crisis - 1994, (vi) Asia crisis - 1997 to 1998, (vii) Dotcom bubble - 1999 to 2000, (viii) Global financial crisis - 2007 to 2008. 10LHC: The Large Hadron Collider is the world’s largest and most powerful particle accelerator located at the CERN, the European Organization for Nuclear Research (Conseil Européen pour la Recherche Nucléaire). The LHC is a 27- kilometre ring of superconducting magnets that accelerates particles such as protons to the speed of light before colliding them to study the quantum particles that are inside the protons. On the 4th of July 2012, the ATLAS and CMS experiments at CERN’s Large Hadron Collider discovered the Higgs boson, the elementary particle that explains why particles have mass.

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The first scholars of complexity theory began their formulations at the Santa Fe institute, and based their study of complex systems on abstract non-linear transformative computer simulations. They attempted to recreate the same phenomenon seen in complex systems, be it rain forests or collisions of protons in the large hadron collider (LHC 10), in massive computer-aided simulations. By adopting this approach, they attempted to achieve a higher level of understanding comprehensive systems consistent in the real world. In the past, this group of scientists were largely ignored by mainstream academia as traditional academics found their conclusions too vague and metaphoric.

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relative industry shares risk innovation CDOs, CLOs and CDSs non-financial firms originate, repackage and sell model originate-to-distribute model originate-to-hold model principal component production and exchange sharding Blockchain FinTech transformation global Fintech financing activity private sector skeleton keys AI-led high frequency trading amalgamation Blockchain fragmentation process information asymmetries Kabbage KYC/AML procedures KYC process machine learning P2P lending sector payments and remittances sector physical barriers rehypothecation robo-advisors SWIFT and ACH transferwise solution pathways digital identity and KYC private and public utilization scalability TBTF See(Too Big to Fail (TBTF)) television advertisement Financialization SeeFragmentation Financial Stability Oversight Committee (FSOC) Financial system Financial Technology (FinTech) capital markets Carney, Mark CHIPS financial services financing activities histroy insurance sector investment/wealth management lending platforms payments Foreign direct investment (FDI) Fractional Reserve banking base and broad money capital requirements central banks commercial banks exchanging currency fractional banking governments monetary policies monetary policy objectives Tier 1, Tier 2, and Tier 3 capital value of a currency Fragmentation concept of current economic malaise dial-up Internet access evolutionary biology Haldane, Andy information asymmetry limitations problem-solving approaches regulatory-centric approach systemic risk TBTF US telecoms industry G Genetic algorithm (GA) Gramm-Leach-Bliley Financial Modernization Act Greenspan, Alan Gresham’s law Guardtime H Haldane, Andy Heterogenous interacting agents High-frequency trading (HFT) Human uncertainty principle HYPR I Implicit contracts Information and communication technologies (ICTs) Institute for New Economical Thinking (INET) Insurance sector InterLedger Protocol (ILP) Internal Revenue Service (IRS) iSignthis J Junk bonds K Kashkari, Neel Kelton, Stephanie Kim-Markowitz Portfolio Insurers Model Know Your Business (KYB) Know Your Customer (KYC) advantage Atlantic model concept of contextual scenario development of documents empirical approach Government digital identity programs identity identity and KYC/AML services Kabbage KYC-Chain manifestations merchant processor multidimensional attributes multiple sources Namecoin blockchain OpenID protocol procedural system regulatory institutions tokenized identity transactional systems value exchange platforms vast-ranging subject Zooko’s triangle kompany.com L Large hadron collider (LHC) Living Will Review process M Macroeconomic models types cellular automata (CA) equilibrium business-cycle models genetic algorithm (GA) neural networks rational expectations structural models traditional structural models vector autoregression (VAR) models Macroeconomic theories Man-in-the-middle (MITM) Marketing money cashless system crime and taxation economy IRS money Seigniorage tax evasion Mathematical game theory McFadden Act Mincome, Canada Minority Game (MG) Money anddebt See alsoDebt and money capitalism cash obsession CRS report currencies floating exchange functions gold and silver history of money histroy real commodities transfer of types of withdrawn shadowbanking See(Shadow banking and systemic risk) utilitarian approach Multiple currencies Bitcoin Obituaries bitcoin price BTC/USD and USD/EUR volatility contractual money cryptocurrencies differences free banking Gresham’s law legal definition legal status private and government fiat private money quantitative model sovereign cash volatility N Namecoin blockchain Namibia Natural Language Processing (NLP) NemID Neo-Keynesian models Neuroplasticity New Keynesian models (NK models) O Occupational Information Network (ONET) Office of Scientific Research and Development (OSRD) OpenID protocol Originate, repackage and sell model Originate-to-distribute model P Paine, Thomas Palley, Thomas I.

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

Rogers 332 Homo omnis (Homni) 300 Honjo, Tasuko 58 Hooke, Robert 333 Horgan, John 118, 168 Hossenfelder, Sabine 121–2 Howard Hughes Medical Institute 322 Howes, Anton 24, 172 hubris 122 Huebner, Jonathan 77–9, 81, 86, 91, 94, 97 Hugo, Victor 27 human frontier 7–19, 27, 40–1, 147–8, 156, 158, 249, 277–8, 336, 342–3 and artificial intelligence 250 diminishing returns of the 98 getting stuck at the 45 moral 132, 138 putting to rest 42 and science 123, 124 slowing down at the 14, 86–7, 131 and women 269 hydrogen 145 Hypatia of Alexandria 304 IBM 33, 184, 240, 265, 296, 312 Idea Paradox 178–9, 187, 191, 217, 226, 250, 254, 283–4, 301, 312, 342 ideas ‘0-I’ ideas 31 and economic growth 88, 89–92 nature of 17–18 protection 89 and research and development 90–1 slowdown 90–1 spread of 89–90 world-changing 5–6 see also big ideas illiteracy 277 imagination 16, 236 immunotherapy 57–61 income global 278 median 95 incrementalism 34, 71, 279 India 44, 71, 213, 264–8, 275, 277, 279–80, 284, 294–5, 308, 313, 326–8 individualism 282 Industrial Enlightenment 27 Industrial Revolution 242–3, 252–3, 295, 301 First (IIR) 79–81, 253, 259, 289, 306, 325 Fourth (4IR) 82, 86, 253–4 Second (2IR) 79–80, 81, 83, 84, 86, 104, 253, 289 Third (3IR) 81–2, 83–4, 86, 92, 253–4 inequality 251 infant mortality rate 10, 54 influence 28, 32–3 Initial Public Offerings (IPOs) 95 Inklings 124, 295 innovation 16, 18, 25, 31, 96, 98, 161, 183–5, 214, 274, 286, 288, 296–7, 298, 339 age of 5 breakthrough 32–3 curve of 77–9 disruptive 34 epochal 31 and human capital 277 and industrial revolution 84 and military technology 316–17 normal rates of 177–8 normalisation of 172 parasitic 194 radical 95 risky nature 335 scale 83 slowdown 83, 85 society's attitude to 17, 18 Innovation Illusion 13 institutional revolution 286–301, 309–10, 328–32, 337–8 Intel 92, 253, 272 intellectual, the, death of 110 intellectual property (IP) 89, 195–6, 251, 331 intelligence 247, 299 collective 339 ‘intelligence explosion’ 238 limits to 166–79 interconnectedness 274, 299–300 interest rates 95 International Exhibition of Modern Art, The 103 International Mathematics Olympiad 276 International Space Station 70 Internet 85, 128–9, 183, 185, 196, 246–7, 253–4, 265–6, 272, 274, 297, 300, 315, 329 invention 11, 15, 16, 156–8, 274, 286, 288, 339 and Bell Labs 180–4 and cities 270–2 industrial 24–5 macro- 31, 81 micro- 31 and military technology 316–17 and patents 97 IP see intellectual property IPOs see Initial Public Offerings iron oxide 89 Islam 133, 340 Islamic caliphate 259, 260 Islamic State 305 ITER 146 Jackson, Andrew 67 Jainism 108 Japan 264, 266, 268, 279, 296, 305 Jefferson, Thomas 211 Jenner, Edward 47 Jesus 24, 216, 303 jet engines 69–70 jetpacks 71, 72 Jiankui, He 255–7, 280, 285 job automation 228 job destruction 96 Jobs, Steve 159, 186 Jones, Benjamin F. 156, 158–9, 160–1 Jones, Charles I. 90–1, 93, 94, 152 joy 170–1 Joyce, James 103, 166 Jung, Carl 104 Justinian 304 Kahn, Bob 253 Kahn, Herman 129 The Year 2000 9, 12, 13 Kaku, Michio 337 Kardashev, Nikolai 337 Kardashev Scale 337–43 Kauffmann, Stuart 203 Kay, John 24–5 Kelly, Kevin 300 Kelly, Mervin 182, 206 Kepler, Johannes 36, 229 Khmer Rouge 305 Kim Il-Sung 114 Klimt, Gustav 188 Knossos 153 knowledge ‘burden of knowledge’ effect 154–65, 175, 178, 235, 338 human frontier of 7–19 Koch, Robert 38 Kodak 184 Koestler, Arthur 36, 39 Kokoschka, Oskar 188 Korea 138, 266, 268, 305 see also North Korea; South Korea Kremer, Michael 274 Kristeva, Julia 111 Kuhn, Thomas 29, 30, 159 Kurzweil, Ray 79 Kuznets, Simon 31 labour 88 Lakatos, Imre 121 Lamarck, Jean-Baptiste 35, 164 Langley, Samuel Pierpont 66 Laozi 108 Large Hadron Collider (LHC) 118, 233, 239 Latin America 266–7, 275, 295 Latour, Bruno 111 Lavoisier, Antoine 29, 34 Lawrence Berkeley National Laboratory 234–5, 296 Lawrence, D.H. 103 lawyers 205–6 Lazarsfeld, Paul 189 Le Figaro (newspaper) 64 Le Mans 64 Le sacre du printemps (The Rite of Spring) 99, 100–2, 104 Leeuwenhoek, Antonie van 231 left wing politics 113 Leibniz, Gottfried Wilhelm 25 Lem, Stanisław 44–5 Lenin, Vladimir Ilyich 188 lenses 231 Leonardo da Vinci 155 Lessing, Doris 152 Lewis, C.S. 124 LHC see Large Hadron Collider Li, Danielle 317–18 liberal democracy 111–12 life expectancy 52–5, 57, 93–4, 169 lift 65 light 75–7 Lilienthal, Otto 62, 335 Lister, Joseph 332 literature 103, 108, 124 Locke, John 25, 137, 138 Lockheed Martin 184, 296 London 133 loonshots 31–2 Loos, Adolf 103, 188 Lorenz, Edward 163 low-hanging fruit paradox 149–54, 167, 178 Lucretius 35, 155 Lulu and Nana (genetically edited twins) 255–7, 264 Luther, Martin 230 Lyell, Charles 34, 35 Lynn, Vera 105 M-theory 120 Mach, Ernst 188 machine learning (ML) 225–7, 233–4, 237, 243, 338 Madonna 105 magnetism 74–7 Mahler, Gustav 188 mail order 84–5 Malevich, Kazimir 103 Malik, Charles 134–6, 140 Malthus, Thomas 35 managerialism 204–5, 206–7 Mandelbrot, Benoit 163 Manhattan Project 119, 144–5, 148, 289, 296, 315, 317–18 Manutius, Aldus 253–4 Mao Zedong 328 Maoism 114 Marcellus 4 Marconi, Guglielemo 216, 289 Margulis, Lynn 203 Mars 218, 296, 318, 338, 341 Marx, Karl 36, 329 Massachusetts Institute of Technology (MIT) 88, 146, 184–5, 296, 314, 316, 327 see also MIT Technology Review materials science 234–5 Maxwell, James Clerk 74–7, 79, 80, 166 Demon (thought experiment) 76 Treatise on Electricity and Magnetism 74–7 Mayan civilisation 43 Mazzucato, Mariana 185, 194, 318 McCloskey, Deirdre Nansen 24 McCormick, Cyrus 11 McKeown, Thomas 53 McKinsey 34, 246 medicine 45, 46–62, 70–3, 93–4, 98, 124–6, 217–18, 338 see also drugs mega-authored papers 157 Meister, Joseph 48 Mendeleev, Dmitri 149 Menlo Park lab 286–7, 293 Merton, Robert 328 Mesopotamia 25, 291 Mesoudi, Alex 164 micro-organisms 49–51 microscopes 49, 232 Microsoft 33, 265 Middle East 138 migration 272–3 military technology 3–4 Minecraft 86 Minoans 43, 153 Minsky, Marvin 227 Mises, Ludwig von 189 MIT see Massachusetts Institute of Technology MIT Technology Review 255 Mitchell, Joni 104 modern art 103 modernity 11, 80, 81, 83–4, 85 Mokyr, Joel 25, 31, 44, 68, 81 molecule libraries 56 Mont Pelerin Society 329 Montagu, Lady Mary Wortley 335 Montgolfier brothers 65 Moon missions 70, 71, 218, 263, 315, 316 moonshots 8, 59, 136, 214, 317 Moore, Gordon 92 Moore's Law 55, 84, 92, 93, 97, 240 Morgan, J.P. 287, 288 Morris, Ian 260–1, 306 Morse, Samuel 289 motor vehicles 68–71, 95, 107–8, 219, 289 Motorwagen 68 Mozart, Wolfgang Amadeus 159 multiculturalism 268 multiverse 170, 342 music 99–108, 115, 188 Musil, Robert 188 Musk, Elon 71, 247 Mussolini, Benito 114 mysterians 166, 249 nanotechnology 242, 243, 245, 341 Napoleon Bonaparte 49 Napoleon III 50, 51 narratives, breakdown of grand 115 National Aeronautics and Space Administration (NASA) 71–2, 233, 315–16, 319 National Health Service (NHS) 56, 57 National Institute of Health (NIH) 60, 120, 185–6, 247, 319, 322 nationalism 213 natural selection 35–6, 37, 109, 118, 244 Nature magazine 12, 121, 157, 211, 220, 229 Nazis 48, 132, 190 Negroponte, Nicholas 13 neo-Enlightenment 98 Netherlands 24, 231, 283 neural networks, deep learning 225, 227, 233 Neurath, Otto 189 neuroscience 247 new molecular entities (NMEs) 93 ‘new normals’ 32 New Scientist (magazine) 122 new technology 95 disruptive 96 New York 103, 134 Newton, Isaac 25, 29, 34, 37, 74–5, 155, 159, 232, 341 Ng, Andrew 262 NHS see National Health Service Nielsen, Michael 117 Nigeria 267, 279 NIH see National Institute of Health Nijinsky, Vaslav 99–100 Nixon, Richard 59 NMEs see new molecular entities noble gases 149 Nokia 183 Nordhaus, William 186 norms, ‘new’ 32 North Korea 305 Novacene 238 Novartis 61 nuclear fission 144, 145–6, 148 nuclear fusion 145–8, 234, 317, 341 nuclear power 85, 119, 143–8, 220, 221, 290 nuclear weapons 45, 143, 144, 311 Oak Ridge laboratory 143, 147 Obama, Barack 59 Obninsk 144 Odlyzko, Andrew 184 Office of Scientific Research and Development (OSRD) 316–17 Ogburn, William 39 oil 80 oligopolies 96 optical devices 231–2 orbits, elliptical 36 organisations breakthrough 294–9 see also companies originality 24, 28, 31–3, 152, 177, 283 lack of 108 Ørsted, Hans Christian 74–5 OSRD see Office of Scientific Research and Development Ottomans 277, 308 Oxford University 123–6, 127, 296 Packalen, Mikko 201, 202, 321 Page, Larry 326 Paine, Thomas 137 painting 176–7 panpsychism 340 paper 230, 259 paradigm rigidity 160 paradigm shifts 29, 33, 105, 109, 130, 164, 222, 250, 339 Parfit, Derek 203 Paris 99–103, 110, 132, 135, 205 particle physics 117–18, 119, 120–1, 122 partisanship 209–10 Pasteur, Louis 46–53, 57, 60–1, 71, 77, 79, 139, 232–3, 296, 332, 338 pasteurisation 50, 51 patents 64, 83, 156–8, 194–6, 271–2, 292–3, 297 new classes 97 patronage 322 Paul, St 303 Pauli, Wolfgang 159 Pauling, Linus 118, 323–4 PCR see polymerase chain reaction peer learning 326–7 peer review 320–1 penicillin 38, 52, 125 Penrose, Roger 124 Pentagon, Naval Air War Center 77 pessimism, rational 123–31, 150 pet food 147 Pfizer 61 pharmaceutical industry 31, 55–7, 60, 70 see also drugs Philo of Byzantium 4–5 philosophy 103–4, 111–12, 115, 121, 124, 339 Photoshop 162 physics 74–7, 79, 80, 116–22, 124, 131, 140, 159–62, 166, 239, 242–3, 332, 341 Picasso, Pablo 36, 101, 152 Pierce, John R. 182 Pitcairn Island 42–3 Planck, Max 104, 160, 296 planets, elliptical orbit 36 plasma 145, 146 Plato 3, 108, 169, 291, 304 Plotinus 303 Plutarch 4 polio 53 political policy 114–15 politics 111–15, 208–13 polymerase chain reaction (PCR) 202 Popper, Karl 189 population growth 78, 79 exponential 11 populism 208, 211, 214, 280–1, 307 post-scarcity society 340 post-truth world 213, 215 Pot, Pol 114 Pound, Ezra 103 present 13 Presley, Elvis 36, 152 ‘priming’ 4 Princeton 180, 296 printing press 36, 230, 253–4 problems, catastrophic 42–4 production lines 104 productivity growth 82 profit 186 progress acceleration 8 linear 29 mirage of 5 nature of 13 protein-folding problem 223–6, 228–9 Proust, Marcel 103 Prussia 50 Ptolemaic astronomical system 30 Ptolemy 303 public bodies 205 public health policy 53 PubMed 28, 116 Punic Wars, Second 3 Pythagoras 304 PYTHIA 237 quantum computing 240–1, 263, 296, 312 quantum physics 159, 166, 341 rabies 48, 51 radiation 57 radioactive elements 149 railways 67, 69 Ratcliffe, Peter 124 rational pessimism 123–31, 150 Ravel, Maurice 101 RCA 33, 289 Reagan, Ronald 211 Rees, Martin 167–8 Reformation 230, 233, 328 refugees 220 regulatory burden 205–6 Relativity Theory, General 104, 117 religion 108, 214, 303–4, 340 Rembrandt 236 Renaissance 130, 156, 177, 230, 233, 252, 254 reproducibility crisis 121 research and development 128, 180–7, 214, 252, 286–90, 312, 339–40 agricultural 92–3 autonomous vehicles 219 cancer 59–61 Chinese 262–3 cleantech 195 drugs 55–7, 61, 92–4, 119, 161, 172–3, 217–18, 234, 245, 315, 338 and financialism 192 funding 202–3, 314–24 global spend 128 government funding 314–19 and ideas 90–1 and India 265, 266 military 314–17, 319 multipolar 258 nuclear 147 productivity 91–5, 97–8, 307 and scaling up 279 specialisation 156, 157–8 and tax credits 331 and training 158–60 and transportation 70, 72 and universities 200–4 revolution, diminishing nature 74–98 Ridley, Matt 281, 325 right wing politics 113, 211 rights 132–40 risk 193, 251, 313, 335–6 risk society 329 risk-aversion 210–11 risk-minimisation strategies 330 roads 66, 67 Rocket engine 26 Roerich, Nicholas 100 Rome 3–4, 43 fall of 151, 187, 190, 303–6 Romer, Paul 88–91, 94 Roosevelt, Eleanor 132, 133–6, 139–40 Rose, Jacqueline 111 Rosetta Stone 155 Rotten, Johnny 104 Roux, Emile 48 Royal Institution 75, 154, 292 Royal Society 25, 75, 154, 292, 326 Royal Society of Arts, Manufactures and Commerce 25, 292 Russia 11, 71, 111, 150, 213, 279 see also Soviet Union Russian Chemical Society 149 Rutherford, Ernest 119, 140 S-curve model 32, 33, 35 Sagan, Carl 306, 337 Salvarsan 52 sanitation 53–4 Sarewitz, Dan 175 Sartre, Jean-Paul 110 satellites 9, 70, 153, 181–2, 272, 315–16 saturation, at the limit 166–79 Saturn 75–6 Saussure, Ferdinand de 109 Scaling Revolution 232 scaling up 255–85, 293–5, 298–9, 301–2, 308, 314–15, 317, 337–8 Schiele, Egon 188 Schliemann, Heinrich 153 Schmidt, Eric 262 Schnitzler, Arthur 188 Schoenberg, Arnold 103, 104, 188 Schrödinger, Erwin 124, 237, 332 Schumpeter, Joseph 189 science 104, 115–25, 131, 157, 159–60, 201–2, 276, 332–3 limits of 168 see also biology, chemistry; physics Science (journal) 118, 164, 175, 229, 257 Science Education Initiative (SEI) 327 Scientific American (magazine) 122 Scientific Revolution 29–30, 123, 130, 229–33, 252–3, 291 Sears Roebuck 84–5 Second World War 138–9, 143–4, 148, 296, 314, 316–17, 319 Sedol, Lee 226–7 seed drills 25 SEI see Science Education Initiative semiconductors 180–1, 245, 338 Semmelweis, Ignaz 216 sensory perception 167 sewing machines 11, 33 Shakespeare, William 169 Shannon, Claude 182, 184 shareholder returns 193, 194, 217 Shaw, D.

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Likewise, the Higgs boson fits into a pattern of particle discovery that, in the twentieth century, populated a hitherto undreamt-of array of particles, from neutrons to antimatter. In 2013 just two people, Peter Higgs and François Englert, won the Nobel Prize for the discovery of the Higgs boson. Yet 3000 people were named as authors on the key papers that went into finding it. CERN spent some $6 billion building the Large Hadron Collider, a major infrastructure with thousands more workers, builders, engineers and support staff. One or two people are hardly responsible for the discovery; all that activity is built atop fairly old predictions from individual minds. Expenditure, numbers of PhDs and publications have all grown between ten- and a hundredfold; yet scientific progress and significant discoveries, in the eyes of its most important contemporary exponents, haven't.

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Demis Hassabis himself makes the link explicit, calling AI a sort of general-purpose Hubble space telescope for science.20 Big ideas like AlphaFold and AlphaGo, instances of the big idea of deep learning neural networks, are steadily making a difference at the coalface. To see how AI reshapes ideas, consider the volume of data produced by contemporary experiments. At CERN, the Large Hadron Collider produces 25 gigabytes of data every second.21 NASA missions churn out more than 125 gigabytes of data every second.22 Climate scientists, particle physicists, population ecologists, derivatives traders and economic forecasters all generate and must process vast amounts of data. Each moreover addresses complex dynamical systems.

Big Data Analytics: Turning Big Data Into Big Money by Frank J. Ohlhorst

algorithmic trading, bioinformatics, business intelligence, business logic, business process, call centre, cloud computing, create, read, update, delete, data acquisition, data science, DevOps, extractivism, fault tolerance, information security, Large Hadron Collider, linked data, machine readable, natural language processing, Network effects, pattern recognition, performance metric, personalized medicine, RFID, sentiment analysis, six sigma, smart meter, statistical model, supply-chain management, warehouse automation, Watson beat the top human players on Jeopardy!, web application

Of course, Amazon, Google, and Facebook are huge enterprises and have access to petabytes of data for analytics. However, they are not the only examples of how Big Data has affected business processes. Examples abound from the scientific, medical, and engineering communities, where huge amounts of data are gathered through experimentation, observation, and case studies. For example, the Large Hadron Collider at CERN can generate one petabyte of data per second, giving new meaning to the concept of Big Data. CERN relies on those data to determine the results of experiments using complex algorithms and analytics that can take significant amounts of time and processing power to complete. Many pharmaceutical and medical research firms are in the same category as CERN, as well as organizations that research earthquakes, weather, and global climates.

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Big science is now paired with Big Data. There are far-reaching implications in how big science is working with Big Data; it is helping to redefine how data are stored, mined, and analyzed. Large-scale experiments are generating more data than can be held at a lab’s data center (e.g., the Large Hadron Collider at CERN generates over 15 petabytes of data per year), which in turn requires that the data be immediately transferred to other laboratories for processing—a true model of distributed analysis and processing. Other scientific quests are prime examples of Big Data in action, fueling a disruptive change in how experiments are performed and data interpreted.

The Star Builders: Nuclear Fusion and the Race to Power the Planet by Arthur Turrell

Albert Einstein, Arthur Eddington, autonomous vehicles, Boeing 747, Boris Johnson, carbon tax, coronavirus, COVID-19, data science, decarbonisation, deep learning, Donald Trump, Eddington experiment, energy security, energy transition, Ernest Rutherford, Extinction Rebellion, green new deal, Greta Thunberg, Higgs boson, Intergovernmental Panel on Climate Change (IPCC), ITER tokamak, Jeff Bezos, Kickstarter, Large Hadron Collider, lockdown, New Journalism, nuclear winter, Peter Thiel, planetary scale, precautionary principle, Project Plowshare, Silicon Valley, social distancing, sovereign wealth fund, statistical model, Stephen Hawking, Steve Bannon, TED Talk, The Rise and Fall of American Growth, Tunguska event

These very high energies allowed the nuclei of atoms to get close enough to interact, rather than more passively bumping off one another. A lot of knowledge about subatomic physics has been gleaned in this way, and the tactic of smashing particles for knowledge continues today in experiments conducted at the Large Hadron Collider at CERN, the European Organization for Nuclear Research. In those early days of atomic research, the machines were a lot smaller, but the discoveries were just as big, if not bigger. Rutherford himself oversaw a series of experiments in which nuclei were accelerated to very high energies and smashed into other nuclei.

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What if we have to rely on government attempts to do fusion, which so far have utilized huge machines? There’s no doubt that the price tags for JET ($2.6 billion), NIF ($4.1 billion), and ITER ($22 billion) are high, but maybe that’s not intolerable. Those sums aren’t so different from the cost of the Large Hadron Collider at CERN ($5.3 billion), the Square Kilometre Array ($1 billion), and the most expensive big science project ever, the International Space Station ($120 billion). The next generation of particle collider will probably cost $25 billion. Even with their high price tags, these are all extremely worthwhile programs that will enhance our species’ existence.

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See also renewable energy Banqiao Dam failure (1975), China, 181 energy crisis solution using, 36–37 lack of plants for, 37 public support for using, 40 world energy consumption and, 34 hydrogen composition of humans and, 86 fusion using isotopes of, 51 nuclear fusion reactions with, 87, 93–94 star formation and, 74, 75, 76, 77 Sun’s fusion reactions and, 79, 83–84 tokamak plasma and, 95, 101, 104 hydrogen bombs atomic bombs compared with, 166 Bikini Atoll testing (1953) of, 161–64, 173–74 controlled fusion reactors for power compared with, 8, 166, 167 net energy gain in, 47 nuclear fusion and fission basis for, 166 proposed space exploration use of, 214 radiation exposure from, 163, 174 Teller’s idea of using to generate electricity, 115–16 HyperJet Fusion Corporation, 143 ignition definition of, 9 EAST tokamak in China and, 193 hotspot ignition, 124 increased temperature and fusion reactions for, 92 JET and, 92 Lawson’s theory and equations on conditions for, 109 Livermore progress in, 16 magnetic fusion machines and, 185, 217 NIF possibilities for, 126, 188, 190, 191 Imperial College London, 26, 73, 96–97, 126–27, 144 inertial confinement fusion, 10 China’s use of, 14 costs of, 122, 198, 206 driver focusing mechanism in, 116–20 First Light Fusion’s use of, 24, 135, 190, 197–98 fusion plasmas timing in, 113–14 Halite-Centurion experiments and, 131, 190–91 laser improvements in, 190–91 later use of simulations replacing, 23 LIFE power plant prototype for, 199, 206 Los Alamos National Laboratory and, 24 low meltdown possibility in, 168–69 MagLIF experiment and, 157–58, 190 magnetic confinement compared with, 113–14 mechanism of, 10 mix of temperature, density, and confinement in, 113 net energy gain goal for, 130–32, 190–91, 199, 217 NIF’s use of, 17, 111, 112–13, 118, 126–29, 134, 188–91, 194, 198, 199, 212 Nuckolls’s experiments and, 116–18 plasma instabilities in, 129 plasma physics’ challenge for, 120 reactor design and, 195, 196–97 shock waves in, 134, 135 start-ups use of, 22 target fabrication in, 121–23, 126–28 Teller’s conception of, 115–16 timing and number of repeat shots in, 197–98 Intergovernmental Panel on Climate Change (IPCC), 33–34, 36, 45 International Atomic Energy Agency, 14 International Energy Agency, 205, 206 International Space Station, 202 IPSOS poll, 40 ITER tokamak, Cadarache, France, 186–88, 193, 194, 197, 201 breeding tritium and, 196 construction delays in, 187–88 cost of, 202, 203–4 design of 187–88 expense of buildings, 202, 203–4 high temperatures for fusion in, 195 international agreement for building, 186–88, 191 international satellite sites for, 187 net energy gain goal and, 191 plasma Q goal of, 188 Japan atomic bombings (1945) in, 154 ITER tokamak, Cadarache, France, and, 186–87 JT-60 tokamak in, 185 Jernigan, Tammy, 78 Joint European Torus (JET) reactor building and shared management of, 88–89, 106–7 confinement of plasma in, 186 control room for monitoring data in, 92–93 cost of, 107, 202 deuterium alone used in, 94–95 high temperatures for fusion in, 91–95, 194 ignition and, 92 magnetic fields for plasma confinement during, 96 maintaining internal chamber wall conditions in, 104–6 physical setting for, 90 Q measure and, 92, 100, 105, 107–8, 183–84 Rimini’s role investigating instabilities of, 98–99, 102–3 robotics at, 196–97 safety of working environment at, 180 success of energy gain in, 107–8, 183–84, 191 trapping hot hydrogen in, 95–96 JT-60 tokamak, Japan, 185 Kingham, David, 33, 139–40, 141, 153–54, 205 Korea Superconducting Tokamak Advanced Research (KSTAR), 184, 185 Laberge, Michel, 145 Large Hadron Collider, CERN, 52, 202 Larmor, Joseph, 96 Larmor radius, 96 laser fusion, 120, 192 lasers, in inertial confinement fusion, 117–19 lasers, Maiman’s invention of, 117 Laser MegaJoule, France, 192 Lawrence, Ernest O., 111, 173, 183 Lawrence Livermore National Laboratory, California, 78, 111–12 Halite-Centurion experiments at, 131, 190–91 inertial fusion energy goal of, 17 LIFE power plant prototype at, 199, 206 location of, 110–11 magnetic confinement device at, 97–98 NIF at.

Meantime: The Brilliant 'Unputdownable Crime Novel' From Frankie Boyle by Frankie Boyle

Big Tech, Large Hadron Collider, late capitalism, lateral thinking, printed gun, sovereign wealth fund, Stephen Hawking, technoutopianism, Turing test, WikiLeaks

She pantomimed a shrug. ‘Thanks. So … I hope you don’t mind, but … I’d never really understood that you and Malcolm weren’t a couple. It was a religious … thing?’ She made a little noise of agreement. ‘Yes. It really wasn’t anything sexual. He was kind of obsessed with the Large Hadron Collider more than anything.’ ‘The Large Hadron Collider?’ ‘Aye, that thing they have out in Switzerland. He was terrified of it. Supposedly, if they get it wrong, it will create all these wee, super dense particles called strangelets. They’ll be so dense they sink down to the Earth’s core. The first we’ll know about it is the whole planet will suddenly turn into a quasar.’

…

Our field is full of people with a crippling lack of social skills.’ Sophie smiled at me. ‘You scored quite well.’ ‘What did I lose points for?’ ‘You gave him directions to a bubble tea bar in East London. Can I ask you something, Felix? Do you have anything else on your mind?’ I thought about this. ‘I worry that the Large Hadron Collider will turn the Earth into a quasar,’ I answered, truthfully. ‘Okay. Maybe.’ Tom nodded enthusiastically. ‘And maybe a lot of stuff. Maybe it’ll open a stargate and turn our souls into Air BnBs for the Voodoo Papas. You’ve got to let go a bit, man.’ ‘I just think it should be a bigger deal.

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

The scale of the SSC was gigantic: it was to be more than fifty miles in circumference and would accelerate protons up to energies of 20 trillion electron volts at a cost of more than $10 billion. To give a sense of scale, an electron volt is a typical energy of the chemical reactions that form the basis of life. The energy of the protons in the SSC would have been eight times greater than that of the Large Hadron Collider now operating in Geneva that was recently in the limelight for discovering the Higgs particle. The demise of the SSC was due to many, almost predictable, factors, including inevitable budget issues, the state of the economy, political resentment against Texas where the machine was being built, uninspired leadership, and so on.

…

Despite some of the seminal contributions that physics and physicists have made to biology, a prime example being the unraveling of the structure of DNA, many biologists appear to retain a general suspicion and lack of appreciation of theory and mathematical reasoning. Physics has benefited enormously from a continuous interplay between the development of theory and the testing of its predictions and implications by performing dedicated experiments. A great example is the recent discovery of the Higgs particle at the Large Hadron Collider at CERN in Geneva. This had been predicted many years earlier by several theoretical physicists as a necessary and critical component of our understanding of the basic laws of physics, but it took almost fifty years for the technical machinery to be developed and the large experimental team assembled to mount a successful search for it.

…

A major reason that the physical and biological sciences have made the tremendous progress they have is that the systems under study can be manipulated or contrived to test specific well-defined predictions and consequences derived from proposed hypotheses, theories, and models. Giant particle accelerators, such as the Large Hadron Collider in Geneva, Switzerland, where the Higgs particle was recently discovered, are a quintessential example of such artificially controlled experimentation. By combining results from the analysis of many experiments involving ultrahigh energy collisions between particles with the development of a sophisticated mathematical theory, physicists have over many years discovered and determined the properties of the fundamental subatomic constituents of matter as well as the forces of interaction between them.

Reinventing Discovery: The New Era of Networked Science by Michael Nielsen

Albert Einstein, augmented reality, barriers to entry, bioinformatics, Cass Sunstein, Climategate, Climatic Research Unit, conceptual framework, dark matter, discovery of DNA, Donald Knuth, double helix, Douglas Engelbart, Douglas Engelbart, Easter island, en.wikipedia.org, Erik Brynjolfsson, fault tolerance, Fellow of the Royal Society, Firefox, Free Software Foundation, Freestyle chess, Galaxy Zoo, Higgs boson, Internet Archive, invisible hand, Jane Jacobs, Jaron Lanier, Johannes Kepler, Kevin Kelly, Large Hadron Collider, machine readable, machine translation, Magellanic Cloud, means of production, medical residency, Nicholas Carr, P = NP, P vs NP, publish or perish, Richard Feynman, Richard Stallman, selection bias, semantic web, Silicon Valley, Silicon Valley startup, Simon Singh, Skype, slashdot, social intelligence, social web, statistical model, Stephen Hawking, Stewart Brand, subscription business, tacit knowledge, Ted Nelson, the Cathedral and the Bazaar, The Death and Life of Great American Cities, The Nature of the Firm, The Wisdom of Crowds, University of East Anglia, Vannevar Bush, Vernor Vinge, Wayback Machine, Yochai Benkler

Want to know what Stephen Hawking is thinking about these days? Go to the arXiv, search on “Hawking,” and you can read his latest paper—not something he wrote a few years or decades back, but the paper he finished yesterday or last week or last month. Want to know the latest on the hunt for fundamental particles of nature at the Large Hadron Collider (LHC)? Go to arXiv, search on “LHC,” and you’ll get a pile of papers to make you stagger. If you get a kick out of surprising people, it might make for unusual cocktail party conversation: “So, did you see the latest on the LHC’s hunt for the Higgs particle? Turns out . . .” Of course, it’s not all easy reading.

…

Hydra misses the quarter-finals of Freestyle tournament, June 11, 2005. http://www.chessbase.com/newsdetail.asp?newsid=2446. [39] Chess Base. PAL / CSS report from the dark horse’s mouth, June 22, 2005. http://www.chessbase.com/newsdetail.asp?newsid=2467. [40] The chess games of Hydra (Computer). http://www.chessgames.com/perl/chessplayer?pid=87303. [41] Tom Chivers. Large Hadron Collider rival Tevatron “has found Higgs boson,” say rumours. Daily Telegraph, July 12, 2010. [42] Hyunyoung Choi and Hal Varian. Predicting the present with Google trends. Google Research blog, April 12, 2009. http://googleresearch.blogspot.com/2009/04/predicting-present-with-google-trends.html

…

See also citations; papers, scientific Justinian (emperor), 158 Kacheishvili, Giorgi, 25 Karpov, Anatoly, 18 Kasparov, Garry, 15–18 on hybrid chess tournament, 114 limits on expertise of, 32 Kasparov versus the World, 15–18 amplifying collective intelligence in, 21, 66, 75 collective insight and, 66–68 conversational critical mass in, 30 dynamic division of labor in, 34–36 expert attention and, 24–26, 28, 66 microcontributions in, 64 shared praxis in, 75 superiority to committees, 39 Katznelson, Yitzhak, 212 Kay, Alan, 58 Kelly, Kevin, 221, 233 Kepler, Johannes, 104, 172–73 Kepler Mission, 201 Khalifman, Alexander, 26 Kleinberg, Jon, 217 knowledge: aggregated by the market, 37–39 current change in construction of, 10, 206 entire body of, 123 of information commons, 59 modern expansion of, 31–32 public accessibility of, 96. See also meaning found in knowledge Knuth, Donald, 58 Krush, Irina, 16–18, 24–26, 35, 66, 67–68, 74 Lakhani, Karim, 218 language translation by machine, 124–26 Lanier, Jaron, 223 Large Hadron Collider (LHC), 161 Large Synoptic Survey Telescope (LSST), 107, 151 lasers, 157 Lauer, Tod, 100–101, 103, 114 lean manufacturing, 36 Leibniz, Gottfried Wilhelm, 174 Lessig, Lawrence, 220 Lévy, Pierre, 217, 221 libraries, and new knowledge tools, 235–36 line-free configurations, 209–10, 212 Lintott, Chris, 133, 134–35 Linus’s Law, 223 Linux: conscious modularity in development of, 51–52, 56–57 microcontributions to, 63 near-fracturing of, 49–50 origin of, 20, 44–45 release 2.0, 52 societal change and, 158 ubiquity of, 45 Lockheed Martin Skunk Works, 36 Lockyer, Joseph Norman, 138 machine translation, 124–26 Mackay, Charles, 218 Mad Max (film), 34 Magellanic clouds, 99 Manhattan Project, 36 markets: collaboration markets, 85, 86, 87, 182, 196 delivering social benefits of science, 156–57, 158 online collaboration compared to, 37–38 subsumed by online tools, 38–39, 224 Masum, Hassan, 171 mathematical proof.

The Knowledge Machine: How Irrationality Created Modern Science by Michael Strevens

Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, Atul Gawande, coronavirus, COVID-19, dark matter, data science, Eddington experiment, Edmond Halley, Fellow of the Royal Society, fudge factor, germ theory of disease, Great Leap Forward, Gregor Mendel, heat death of the universe, Higgs boson, Intergovernmental Panel on Climate Change (IPCC), invention of movable type, invention of the telescope, Isaac Newton, Islamic Golden Age, Johannes Kepler, Large Hadron Collider, longitudinal study, Louis Pasteur, military-industrial complex, Murray Gell-Mann, Peace of Westphalia, Richard Feynman, Stephen Hawking, Steven Pinker, systematic bias, Thales of Miletus, the scientific method, Thomas Bayes, William of Occam

So it goes with all scientific reasoning: the interpretation of evidence demands likelihoods, and scientists are not only permitted but encouraged to use their subjective plausibility rankings in that role. When these rankings agree, scientists agree on the treatment of the evidence. In 2016, a marten—a small member of the weasel family—gnawed through a power cable at the Large Hadron Collider at CERN, in Switzerland, destroying itself and seriously damaging the collider’s power supply. There was no discrepancy of plausibility rankings in this case: the many scientists working at the facility contemplated the small, smoking corpse and concurred that “something had gone wrong.” The collider would need major repairs and subsequent batteries of tests before its data could be trusted.

…

In some cases, scientists who may have quite opposing theoretical perspectives and ambitions come together to form a temporary community sharing an experimental purpose and capable, because of its size and unity, of doing things beyond the means of a single research group. Of the scientists who searched for the top quark at Fermilab near Chicago in the 1990s or the Higgs boson at the Large Hadron Collider near Geneva in the 2010s, some were hoping to confirm the predictions of physics’ Standard Model—which implies that these particles exist—while others were hoping to overturn the Standard Model (“I hate the Standard Model,” said one to me), and others still were agnostic. They agreed, nevertheless, that the experiments were worth all their time and a lot of money.

…

., 304n methodological innovations encompassed by, 117–19 and methods outlined in Principia, 137, 191, 248–49 moral strategy for teaching, 258–59 negative clause, 118–19, 195 Newton and, 142, 191–92, 245, 273 Newton’s law of universal gravitation and, 188 Newton’s outlining of essential aspects, 137–38 objectivity and, 118, 162 principle of total evidence and, 315n procedural consensus and, 117–18 quantum mechanics and, 147, 150, 151 rigid specifications for public announcements, 118 scientific argument vs. private reasoning in, 163–64, 181, 235, 238, 249–51, 264–66, 273 and Scientific Revolution, 243 scientific vs. unscientific reasons, 181 and seventeenth century natural philosophy, 192–94 and shallow conception of explanation, 142, 195 simplemindedness and, 259–60 as sine qua non of modern science, 202 sterilization and, See “sterilization” of scientific argument string theory and, 284–85 supremacy of observation in, 173–97 and tedium of empirical work, 256 and theoretical cohorts, 139–40 and Tychonic principle, 116 Whewell and, 180, 191, 205 irrationality and “golem” model of science, 287 of iron rule, 9, 201–8, 237–38 and science education, 256–57 and Scientific Revolution, 242 and teaching of iron rule to Atlanteans, 258 Jahren, Hope, 37, 255 James I (king of England), 105 Jesus Christ, 187, 250–52 Jupiter (planet), 106 Kamlah, Andreas, 296n Kant, Immanuel, 136 Keller, Alexander, 300n Kelvin, Lord (William Thomson), 74–79, 81–85, 181 Kennefick, Daniel, 298n Kepler, Johannes, 27, 106, 193 Keynes, John Maynard, 188, 212, 214 kinetic theory of heat, 90–92, 94, 108, 109 Krauss, Lawrence, 261 Kuhn, Thomas, 6, 31 and Aristotle’s physics, 123–24 belief in science’s power to create new knowledge, 32–33 birth and early years, 22–23 commonalities with Popper, 38–40 on Copernicanism, 27 and Copernican revolution, 26–27 and crisis, 28 and dogmatism, 258 and Eddington’s eclipse expedition, 46–47 errors in paradigm concept, 46–47, 238, 298n extraphilosophical claims, 40 and history of gravity, 137 and iron rule of explanation, 102, 103 on motivation, 38, 116, 203, 282 and objectivity, 85–86 and partisans, 57 on prevailing paradigm as sole worldview of science, 289 recommendations for healthy science, 282–83 on relation of experimental inquiry to paradigm, 36 on rules of science, 304n Lab Girl (Jahren), 255 Laboratory Life (Latour and Woolgar), 61 Lakatos, Imre, 30 lambda (subatomic particle), 228, 230 Language of God, The (Collins), 181 Large Hadron Collider, 81 latitudinarianism, 75 Latour, Bruno, 60–63, 68 “law of higgledy-piggledy,” 219, 236 Lawrence, D. H., 267 leap of faith, 30 Leibniz, G. W., 136, 138, 243 Leonardo da Vinci, 242 Lesbos, 125 L’Hôpital, Marquis de, 140 Libbrecht, Ken, 171–72 liberal arts, 274 liberal democracy, iron rule vs., 268 liberalism, 252 lieutenants of the Scientific Revolution, 192–94 life, history of, 175 light in Cartesian physics, 133 and Eddington’s expedition to test Einstein’s gravitation theory, 42–50, 43, 44, 68–73, 155–61 and ether, 143 Galileo and, 290 Michelson–Morley experiment, 112–14 speed of, 72, 112–14 superposition and, 144 wave/particle duality, 144, 150 Lindberg, David, 117 Lloyd, Seth, 37 Loew ben Bezalel, Judah, 285–86 logic as insufficient grounds for falsification, 281 and theory, 18–19 Logic of Scientific Discovery, The (Popper), 13–14 longitudinal studies, 35–36 LRF (hormone), 99, 304n Luther, Martin, 242, 245 Macleay, William Sharp, 214–18 macrocosm, consonance with microcosm, 210, 236 Mantell, Gideon, 175, 176 maps, 54–55 Marsh, O.

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

In par­tic­u ­lar, large neuroscience efforts ­today are almost universally promoted as big data proj­ects. The data requirements for t­hese proj­ects certainly merits the term. The Kavli Foundation notes that the BRAIN Initiative must survive a “data deluge”: “Mea­sur­ing just a fraction of the neurons in the brain of a single mouse could generate nearly as much data as the 17 mile-­ long Large Hadron Collider or the most advanced astronomical observatories.” 4 Kavli highlights a theme that runs prominently in the lit­er­a­t ure of both Big Brain proj­ects: the marriage of data-­driven AI to neuroscience is both an information technology challenge and a huge opportunity, as the ability to manipulate more data about the brain is thought to translate to successful research.

…

But this concern aside, it is the shallow logic b­ ehind such approaches that spell deeper trou­ble for the institution of science. H IGGS BOSON In 2012, scientists discovered a long-­m issing piece of the standard model of physics, the Higgs boson. The discovery of Higgs boson is often attributed to an impressive piece of technology, the massive Large Hadron Collider (LHC) straddling the French-­Swiss border. The LHC is seventeen miles of tubing constituting the world’s largest supercollider. Scientists used the LHC to design an experiment specifically testing for the existence of a particle accounting for mass in the universe, dubbed the “Higgs boson” a­ fter Peter Higgs, the scientist who first predicted its existence.

…

., 253, 255–256, 268 Kasparov, Garry, 219 Kavli Foundation, 249, 255 Keilis-­Borok, Vladimir, 260 Kelly, Kevin, 42, 241–242, 285–286n7 Kenall, Amye, 249 Kepler, Johannes, 104 kitch, 61–63 knowledge: computational, 178–182; deductive reasoning and, 110–112; infinite amount of, 54; as prob­lem for induction, 124; used in inference, 102 knowledge-­based systems, 107 knowledge bases, 178–181 knowledge repre­sen­t a­t ion and reasoning (KR&R), 175–176 Koch, Christof, 253, 256 Kundera, Milan, 60–61 Kurzweil, Ray, 35, 38, 84, 274; on consciousness, 78–79; on f­ uture of AI, 70, 74; hierarchical pattern recognition theory of, 264–266; on h­ uman intelligence, 251; Law of Accelerating Returns of, 42, 47–48, 67; on singularity, 46; on superintelligent machines, 2; on Turing test, 193–194 308 I ndex ladder of causation, 130, 174 Lakatos, Imre, 48 Laney, Doug, 292n5 language. See natu­ral language Lanier, Jaron, 84, 244, 277; on encouraging ­human intelligence, 239; on erosion of personhood, 270, 272–273 Large Hadron Collider (LHC), 254–255 Law of Accelerating Returns (LOAR), 42, 47–48 learning: definition of, 133; by ­humans, 141 LeCun, Yann, 75 Legos theory of cognition, 266 Lenat, Doug, 74 Levesque, Hector, 76, 216; on attempts at artificial general intelligence, 175, 186; on Goostman, 192; pronoun disambiguation prob­lem of, 203; on Winograd schemas, 195–196, 198–201 Loebner Prize, 59 Logic Theorist (AI program), 51, 110 Lord of the Rings (novels; Tolkien), 229–230 Lovelace, Ada, 233 Marcus, Gary, 131, 183; on brittleness prob­lem, 126; on correlation and causation, 259; on DeepMind, 127, 161–162; on Google Duplex, 227; on Goostman, 192; on Kurzweil’s pattern recognition theory, 265; on limitations of AI, 75–76; on machine reading comprehension, 195; on superintelligent computers, 81; on Talk to Books, 228 Markram, Henry, 252–254, 273; on AI, 251; on big data versus theory, 256–258, 267, 268; on hive mind, 245–246, 276; H ­ uman Brain Proj­ect ­u nder, 247–250; Legos theory of cognition by, 266; on theory in neuroscience, 261, 262 Marquand, Alan, 232 mathe­matics: functions in, 139; Gödel’s incompleteness theorems in, 12–14; Hilbert’s challenge in, 14–16; Turing on intuition and ingenuity in, 11 Mathews, Paul M., 256, 267 Mayer-­Schönberger, Viktor, 143, 144, 257 McCarthy, John, 50, 107, 285n11 Microsoft Tay (chatbot), 229 Mill, John Stuart, 242, 243 machine learning: definition of, 133; Miller, George, 50 empirical constraint in, 146–149; minimax technique, 284n1 frequency assumption in, 150–154; Minsky, Marvin, 50, 52, 222 Mitchell, Melanie, 165 model saturation in, 155–156; as narrow AI, 141–142; as simulation, Mitchell, Tom, 133 138–140; supervised learning in, model saturation, 155–156 modus ponens, 108–109, 168–169 137 machine learning systems, 28–30 monologues, Turing test variation using, 194–195, 212–214 MacIntyre, Alasdair, 70–71 I ndex monotonic inference, 167 Mountcastle, Vernon, 264 Mumford, Lewis, 95, 98 “The Murders in the Rue Morgue” (short story, Poe), 89–94 Musk, Elon, 1, 75, 97 narrowness, 226–231 Nash, John, 50 National Resource Council (NRC), 53, 54 natu­ral language: AI understanding to, 228–229; computers’ understanding of, 48, 51–55; context of, 204; continued prob­lems with translation of, 56–57; in speech-­ driven virtual assistance applications, 227; Turing test of, 50, 194; understanding and meaning of, 205–214; Winograd schemas test of, 195–203 neocortical theories: Hawkins’s, 263; Kurzweil’s, 264–266 neural networks, 75 neuroscience, 246; collaboration in, 245–247; Data Brain proj­ects in, 251–254; ­Human Brain Proj­ect in, 247–251; neocortical theories in, 263–268; theory versus big data in, 255–256, 261–262 Newell, Allan, 51, 110 news stories, 152–154 Newton, Isaac, 187, 276 Nietz­sche, Friedrich Wilhelm, 63 no f­ ree lunch theorem, 29 noisy channel approach, 56 non-­monotonic inference, 167–168 normality assumption, 150–151 309 Norvig, Peter, 77, 155, 156 nuclear weapons, 45 Numenta (firm), 263 observation: generalizing from, 117–118; in induction, 115; limitations of, 121; turning into data, 291n12 operant conditioning (behaviorism), 69 orthography, 205 overfitting (statistical), 258–261 Page, Larry, 56 Pearl, Judea, 130–131, 174, 291n13 Peirce, Charles Sanders, 95–99; on abduction, 25–26, 160–168; on abductive inference, 99–102, 190; on guessing, 94, 183–184; on “Logical Machines,” 232–233, 273; theft of watch from, 157–160, 289–290n5; on types of inference, 171–172, 181; on weight of evidence, 24 Peirce, Juliette, 98 Perin, Rodrigo, 266 PIQUANT (AI system), 221–224 Poe, Edgar Allan, 89–94, 99, 102 Polanyi, Michael, 73–74 Popper, Karl, 70–71, 122 positivism, 63 pragmatics (context for natu­ral language), 204, 206, 214–215, 296n1 predictions, 69–73; big data used for, 143–144; induction in, 116, 124; limits to, 130 predictive neuroscience, 254 probabilistic inference, 102 programming languages for early computers, 284n2 310 I ndex scripts, 181–182 se­lection prob­lem, 182–184, 186–190 self-­d riving cars, 127, 278; saturation prob­lem in, 155–156 random sampling, 118 self-­reference, in mathe­matics, 13 reading comprehension, 195 semantic role labeling, 138–139 real-­t ime inference, 101 semantics, 206 reasoning, 176 Semantic Web, 179 religion, 63 semi-­supervised learning, 133–134 sequential classification, 136–137 resource description framework sequential learning, 136–137 (RDF), 179 R.U.R.

Is the Internet Changing the Way You Think?: The Net's Impact on Our Minds and Future by John Brockman

A Declaration of the Independence of Cyberspace, Albert Einstein, AltaVista, Amazon Mechanical Turk, Asperger Syndrome, availability heuristic, Benoit Mandelbrot, biofilm, Black Swan, bread and circuses, British Empire, conceptual framework, corporate governance, Danny Hillis, disinformation, Douglas Engelbart, Douglas Engelbart, Emanuel Derman, epigenetics, Evgeny Morozov, financial engineering, Flynn Effect, Frank Gehry, Future Shock, Google Earth, hive mind, Howard Rheingold, index card, information retrieval, Internet Archive, invention of writing, Jane Jacobs, Jaron Lanier, John Markoff, John Perry Barlow, Kevin Kelly, Large Hadron Collider, lifelogging, lone genius, loss aversion, mandelbrot fractal, Marc Andreessen, Marshall McLuhan, Menlo Park, meta-analysis, Neal Stephenson, New Journalism, Nicholas Carr, One Laptop per Child (OLPC), out of africa, Paul Samuelson, peer-to-peer, pneumatic tube, Ponzi scheme, power law, pre–internet, Project Xanadu, Richard Feynman, Rodney Brooks, Ronald Reagan, satellite internet, Schrödinger's Cat, search costs, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Skype, slashdot, smart grid, social distancing, social graph, social software, social web, Stephen Hawking, Steve Wozniak, Steven Pinker, Stewart Brand, synthetic biology, Ted Nelson, TED Talk, telepresence, the medium is the message, the scientific method, the strength of weak ties, The Wealth of Nations by Adam Smith, theory of mind, trade route, upwardly mobile, Vernor Vinge, Whole Earth Catalog, X Prize, Yochai Benkler

To make a definitive leap into artificial reality, we’ll need both more ingenuity and more computational power. Fortunately, both could be at hand. The SETI@home project has enabled people around the world to donate their idle computer time to sift radio waves from space, advancing the search for extraterrestrial intelligence. In connection with the Large Hadron Collider (LHC) project, CERN—where, earlier, the World Wide Web was born—is pioneering the GRID computer project, a sort of Internet on steroids that will allow many thousands of remote computers and their users to share data and allocate tasks dynamically, functioning in essence as one giant brain.

…

It’s like having a private particle accelerator on my desktop, a way of throwing things into violent juxtaposition, with the resulting collisions reordering my thinking. The result is new particles—ideas!—some of which are BDTs and many of which are nonsense. But the democratization of connections, collisions, and therefore thinking is historically unprecedented. We are the first generation to have the information equivalent of the Large Hadron Collider for ideas. And if that doesn’t change the way you think, nothing will. The Web Helps Us See What Isn’t There Eric Drexler Engineer, molecular technologist; author, Engines of Creation As the Web becomes more comprehensive and searchable, it helps us see what’s missing in the world.

…

People with differing ideas and backgrounds can test their theories against the world, and may the best idea win. The fact that the information can be looked at by so many different kinds of people from anywhere on Earth is the Internet’s true power—and the source of my fascination with it. Right now, a little kid can browse the raw data coming from the Large Hadron Collider; he can search the stars for signals of alien life with the SETI project. Anyone can discover the next world-changing breakthrough. That’s the point of the Internet. Also, the contribution of search engines in simplifying the research process can’t be underestimated. This enables us to conduct research instantly, on our own terms.

Demystifying Smart Cities by Anders Lisdorf

3D printing, artificial general intelligence, autonomous vehicles, backpropagation, behavioural economics, Big Tech, bike sharing, bitcoin, business intelligence, business logic, business process, chief data officer, circular economy, clean tech, clean water, cloud computing, computer vision, Computing Machinery and Intelligence, congestion pricing, continuous integration, crowdsourcing, data is the new oil, data science, deep learning, digital rights, digital twin, distributed ledger, don't be evil, Elon Musk, en.wikipedia.org, facts on the ground, Google Glasses, hydroponic farming, income inequality, information security, Infrastructure as a Service, Internet of things, Large Hadron Collider, Masdar, microservices, Minecraft, OSI model, platform as a service, pneumatic tube, ransomware, RFID, ride hailing / ride sharing, risk tolerance, Salesforce, self-driving car, smart cities, smart meter, software as a service, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Stuxnet, Thomas Bayes, Turing test, urban sprawl, zero-sum game

The level of detail available can be crucial in some contexts. Granularity can be thought of in different ways: it may be in terms of time as is the case with how precisely an observation is captured. This is critical for sporting events like downhill skiing. It could also be resolution as is the case with the Large Hadron Collider, the world’s largest and most powerful particle accelerator at CERN in Switzerland, where the granularity level is down to subatomic particles. In some cases, even the right data can be without value if the granularity is too high. Think of autonomous vehicles navigating through a city. If they work with maps that are accurate to within a few meters no matter how precise, it might prove fatal.

…

v=cIsIKv1lFZw (September 27, 2019) a video by Bjarke Ingels: architecture should be more like Minecraft Chapter 8 The Power of Habit: Why We Do What We Do, and How to Change , Charles Duhigg, Random House, 2013 Chapter 9 Scoring Points, How Tesco Continues to Win Customer Loyalty , Clive Humby, Terry Hunt and Tim Phillips, Kogan Page, 2008 The World’s Most Valuable Resource is no longer Oil but Data , The Economist, May 6th 2017 Enterprise Integration Patterns , Gregor Hohpe and Bobby Woolf, Addison Wesley, 2003 The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modelling, Ralph Kimball and Margy Ross, Wiley 2013 Hadoop: The Definitive Guide, Tom White, O’Reilly Media, 2015 Chapter 10 www.wired.com/2010/11/1110mars-climate-observer-report/ (October 2, 2019) a story about the Mars Climate Orbiter’s crash https://bleacherreport.com/articles/2760821-olympic-mens-alpine-skiing-results-2018-medal-winners-for-slalom (October 2, 2019) the results of the 2018 Olympic show a difference less than 1.5 seconds between number 1 and 10 https://home.cern/science/computing/processing-what-record (October 2, 2019) a description of what the Large Hadron Collider processes Chapter 11 The Magical Number Seven, Plus or Minus Two Some Limits on Our Capacity for Processing Information , George A. Miller, Psychological Review Vol 101, no. 2, page 343–352, 1955 https://pubs.opengroup.org/architecture/togaf8-doc/arch/chap29.html (October 2, 2019) a description of the Open Group’s format for Principles Index A American National Institute of Standards and Technology (NIST) Architectural layers Architecture standards connectivity data devices integration platform Array of Things (AoT) Artificial intelligence (AI) Alvelor project Amsterdam 311 challenges history issues autonomous vehicles and ethics ecological human intelligence optimization paradox political accountability public demand unacceptable implementation unclear benefits unpredictable human element solutions Availability AWS B Better Approach To Mobile Adhoc Networking (B.A.T.M.A.N.)

Space Chronicles: Facing the Ultimate Frontier by Neil Degrasse Tyson, Avis Lang

Albert Einstein, Apollo 11, Apollo 13, Arthur Eddington, asset allocation, Berlin Wall, Boeing 747, carbon-based life, centralized clearinghouse, cosmic abundance, cosmic microwave background, dark matter, Gordon Gekko, high-speed rail, informal economy, invention of movable type, invention of the telescope, Isaac Newton, James Webb Space Telescope, Johannes Kepler, Karl Jansky, Kuiper Belt, Large Hadron Collider, Louis Blériot, low earth orbit, Mars Rover, Mars Society, mutually assured destruction, Neil Armstrong, orbital mechanics / astrodynamics, Pluto: dwarf planet, RAND corporation, Ronald Reagan, Search for Extraterrestrial Intelligence, SETI@home, space junk, space pen, stem cell, Stephen Hawking, Steve Jobs, the scientific method, trade route

Long before the bomb, and continuing through the entire Cold War, America sustained a fully funded particle physics program. Then the Berlin wall comes down in 1989, and within four years the entire budget for the Super Collider gets canceled. What happens now? Europe says, “We’ll take the mantle.” They start building the Large Hadron Collider at CERN, the European Organization for Nuclear Research, and now we’re standing on our shores and looking across the pond, crying out, “Can we join? Can we help?” MP: I remember an interesting exchange from those hearings you’re talking about. One senator who was evaluating the continued expense for the Super Collider said to Steven Weinberg, a physicist testifying before Congress, “Unfortunately, one of the problems is that it’s hard for me to justify this expense to my constituents, because, after all, nobody eats quarks.”

…

As far as basic research goes, we’ve got the Hubble telescope; we’re going to have a laboratory on Mars in a few years; we have the spacecraft Cassini in orbit around Saturn right now, observing the planet and its moons and its ring systems. We’ve got another spacecraft on its way to Pluto. We’ve got telescopes being designed and built that will observe more parts of the electromagnetic spectrum. Science is getting done. I wish there was more of it, but it’s getting done. MP: But not the Large Hadron Collider, which is getting done by the Europeans. JG: There’s one other potential case for space travel that we haven’t really talked about. Earlier you alluded to the idea that if we become a spacefaring people, we might need to use the Moon and Mars as a sort of Quik Mart. Do you think we could make the practical case that we need to venture out into space because Earth will at some point become uninhabitable?

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., 4, 8, 11, 12, 13, 17, 79, 136, 219, 225 “Moon” speech of, 13, 79, 148–49, 191–92 Kennedy Space Center, 14–15, 16, 140, 145, 161, 220, 229 Kepler, Johannes, 115 Kinsella, Gary, 249–50 Korea, Republic of (South Korea), xiv Korean War, 149 Korolev, Sergei, 123–24, 126 Kubrick, Stanley, 128–29 Kuiper Belt, 168, 245 Kuwait, 27 Lagrange, Joseph-Louis, 173, 176 Lagrangian points, 72, 145, 173–76 gravity and, 172–74 launches from, 177 libration paths and, 174 NASA satellites and, 176 Laika (dog), 122 Langley, Samuel P., 216–17 Laplace, Pierre-Simon de, 117–18 Large Hadron Collider, 80, 82 lasers, 167 Lauer, Matt, 210–11 Launching Science, 169–70 Leno, Jay, 144–45 Le Verrier, Urbain-Jean-Joseph, 248 L5 Society, 175 life: chemical components of, 35–36 diversity of, 34–35 extinction episodes of, 49 extraterrestrial, see extraterrestrial life on Mars, 48, 259 search for, 41, 325 light, 30, 90, 93, 258 speed of, 109, 164, 195 LightSail-1, 167 Lindbergh, Charles, 110 Lindsay, John, 67 Lockheed Martin, 236 Lombardi Comprehensive Cancer Center, 23 long-period comets, 46–47 Lovell, Jim, 112 low Earth orbit (LEO), 113 Luna 9 rover, 70 Luna 13 rover, 70 Lunar Orbiter Image Recovery Project, 149–50 Lunar Orbiter spacecraft, 149 Lunar Reconnaissance Orbiter (LRO), 150 MacHale, Des, 234 Madonna, 203 Magellan, Ferdinand, 95, 96 Major Mysteries of Science (Garbedian), 110 Manhattan Project, 80 many-body problem, 117–18 Mars, 7, 8, 14, 40, 46, 55, 77, 115, 129, 168, 188, 195, 200, 209 cratering on, 52 Earth viewed from, 27 life on, 48, 259 methane on, 31, 78, 138 proposed mission to, 78–79, 81–83 rocks ejected from, 48–49 rovers on, 130–33, 134, 138, 163, 198 Soviet achievements and, 122 water on, 48, 134, 138, 201, 227 Mars Express Orbiter, 138 Mars Global Surveyor, 138 Marshall Space Flight Center, 67 Mars Society, 236 mass extinction, 51 McAuliffe, Christa, 243 McDonald’s, 238 McNair, Ron, 234 Mécanique Céleste (Laplace), 117 Mercury (god), 108 Mercury (planet), 52, 115, 118 orbit of, 248 Mercury program, 7, 114 MESSENGER probe, 139 meteorites, 48 Tunguska River impact of, 50 see also asteroids methane, 30 on Mars, 31, 78, 138 on Titan, 138–39 Mexico, 50 microscope, 85–86 Microsoft, 136 microwaves, 41, 90, 91–92, 129, 141 microwave telescope, 91–92 Milky Way galaxy, 34, 41, 93, 97–101, 143, 147, 259 Andromeda galaxy and, 118–19 orbit of stars in, 118 radio emissions from center of, 90 Shapley-Curtis debate on, 98–101 Mir space station, 6, 165, 319 Mitchell, Edgar, 3 Mongols, 205–6 Moon, xiii–xiv, 4, 5, 6, 8, 11, 12, 13, 14, 21, 46, 47, 66, 69, 70, 71, 72, 86, 89, 97, 111–12, 119, 132, 149, 186, 195, 196, 200, 220, 245 cratering on, 50, 57 Earth viewed from, 27 40th anniversary of landing on, 144 proposed return mission to, 55–56, 76–77, 83 rocks ejected from, 48 Soviet achievements and, 122 see also Apollo program, Apollo 11 motion, third law of, 153, 158 multiverse, 259 NanoSail-D, 167 NASA Flexibility Act of 2004, 330 National Academy of Public Administrations, 322 National Academy of Sciences, 11, 98, 325 National Aeronautics and Space Act of 1958, xv, 4, 58, 66, 125, 252, 265–91, 328 access to information in, 273–74 aerospace vehicle in, 282–84 amended text of, 265–91 appropriations in, 284–85, 286 awards in, 278–79 civilian-military liaison in, 271 congressional reporting in, 271 excess land in, 272 insurance in, 281–84 international cooperation in, 271, 291 inventions in, 276–78 jurisdiction in, 290 launch vehicle contracts in, 285–86 lawsuits in, 279–80 misuse of name in, 285 National Advisory Committee in, 272–73 prize authority in, 286 property leases in, 289 property rights in, 276–77 purpose and objectives of, 265–67 recovery authority in, 290 security in, 274–75 transfer of functions in, 273 upper atmosphere research in, 290–91 National Aeronautics and Space Administration Authorization Act of 2000, 326–27 National Aeronautics and Space Agency (NASA), 59–60, 89, 114, 162, 166–68, 192, 199–200, 203, 219, 305, 306, 309 acquisition of space science data and, 314–15 additional activities of, 313–14 aero-space transportation technology integration plan of, 323–24 anchor tenancy contracts and, 308–9 Astronaut Pen of, 194 budget of, xiv, 10, 12, 15, 56, 75, 150, 169–70, 209–10, 212, 228, 237 carbon cycle research program of, 325–26 civil rights movement and, 66–67 creation of, 5–6, 66–67, 125, 267 decision making at, 146 deputy administrator of, 328 divisions of, 9 Earth science data sources and, 315–16 economic impact of, 237 expert input and, 146–47 Exploration Award of, 146–47 functions of, 265–72 future and, 252–53 Human Space Flight Innovative Technology program of, 324 international politics and, 5–7 Mars rovers and, 130–34 new Mars mission and, 77–78 new Moon mission and, 56, 77–78 number of employees of, 236 Obama on role of, 11–12 Obama’s vision of, 11–17 100th anniversary of flight initiative and, 326 payloads of, 313–14 political partisanship and, 4–5, 13–14 reorganization of, 329 scientific value of, 9–11 spending by, xv, 7–9, 25, 193–94, 331–32, 333–35 statutory provisions applicable to, 293–94 use of government facilities and, 309 vision statement of, 68 working capital fund of, 328 see also specific centers, programs, and vehicles National Air and Space Museum, 7–8, 23, 144 National Commission on Excellence in Education, 58 National Defense Education Act of 1958, 125 National Defense Scholarships, 125 National Geographic channel, 231 National Institute of Standards and Technology, 12, 306–7 National Institute on Disability and Rehabilitation Research, 306 National Institutes of Health, 209 National Museum of Natural History, 98 National Research Council, 169, 322 National Science Foundation, 11–12, 23, 125, 219, 305 National Security Council, 124 National Space Grant College and Fellowship Act of 1987, 295–303 administrative services, 301 appropriations, 303 competitive awards, 303 contracts, 298–99 fellowship program in, 300–301 functions of, 297–98 grants in, 298–99 identity of needs in, 299 personnel services in, 301 purpose of, 295–96 regional consortium in, 300 reports to Congress in, 302–3 review panel in, 301 National Space Institute, 175 National Space Society, 146, 175, 236 National Space Symposium, 222 National Technical Information Service, 304 “Nation at Risk, A,” 58 Natural History, xiii NBC, 144, 178 Neptune, 27, 36, 46, 115, 119, 157 discovery of, 248 Netherlands, 7 neutrinos, 94 Newcomb, Simon, 216 New Horizons spacecraft, 168 New Scientist, 123 Newton, Isaac, 65, 113–17, 119, 153, 158, 192, 247, 257 New York, N.Y., 96, 124, 224, 238 New York Times, 55, 96, 110, 124, 216–17 NEXT ion propulsion system, 170 Nigeria, 23 nitrogen, 101, 239, 240, 258 Nixon, Richard M., 4–5, 225 Nobel, Alfred Bernhard, 88 Nobel Prize, 88–89, 94, 206 North Atlantic Drift current, 93 North Carolina, 109, 216 Northrop Grumman, 236 Norway, 7 NOVA (TV series), 231 novae, 100 NRA, 236 nuclear power, 159, 168–69 numbers: Arabic, 205 increasing powers of, 237–38 Obama, Barack, 11, 14–16, 76, 186–87, 252 space policy and, 77 Obama administration, 75 Office of Federal Housing Enterprise Oversight, 311 Office of Human Spaceflight, 323–24 Office of Life and Microgravity Sciences and Applications, 323 Office of Management and Budget, 318 Office of Research and Technology Applications, 303–4, 305 Ohio, 4–5, 184–85 O’Neill, Gerard K., 8, 175 Onizuka, Ellison, 243 Opportunity (Mars exploration rover), 130–32, 138 orbits, 113–20 of Earth, 115 elongated, 115–16 free fall and, 119 many-body problem and, 117–18 of Mercury, 248 of Pluto, 115 sling-shot effect and, 119–20 of stars, 118 suborbital trajectories and, 114 three-body problem and, 116–17 of Venus, 115 Orellana, Francisco de, 197 organic chemistry, 36, 48 Origin of Species (Darwin), 98 oxygen, 31, 35–36, 101, 158, 239, 240, 258 ozone, 51, 93 Pakistan, 49 Panama Canal, 87 panspermia, 48–49, 259 Parliament, British, 217 “Passport to the Universe” (Druyan and Soter), 256 Pegasus, 108 Penzias, Arno, 92 perturbation theory, 118 Peru, 196–97 Pfeiffer, Michelle, 203 photosynthesis, 31 Pigliucci, Massimo, 75–83 Pioneer anomaly, 244–45, 248–51 Pioneer program: Pioneer 0, 245 Pioneer 3, 245 Pioneer 4, 245 Pioneer 5, 245 Pioneer 9, 245 Pioneer 10, 118, 244–45, 247, 248–50 Pioneer 11, 168, 244–45, 247, 249 Pioneer 12, 245 Pioneer 13, 245 Pizarro, Gonzalo, 196–97 planetary motion, first law of, 115 Planetary Society, 166–67, 193, 236, 250 Pluto, 82, 112, 118, 128, 168, 195, 201 orbit of, 115 Pravda, 121 Prescott, William H., 196 Presidential Commission on Implementation of United States Space Exploration Policy, 59–60, 146 President’s Commission on Higher Education, 125 Prince (singer), 203 Principia (Newton), 113 Project Prometheus, 169–70 propulsion: alternate fuels for, 157–59 antimatter drive and, 170–71 chemical fuel for, 163 electricity and, 165 in-space, 170 ion-thruster engine and, 164–65, 170 nuclear power and, 159, 168–69 rocket equation and, 153–54, 157 and slowing down, 155–56 solar sails and, 159, 165–67, 170 third law of motion and, 153, 158 xenon gas and, 164–65 Proxima Centauri, 195–96 Ptolemy, Claudius, 34, 65 pulsars, 29 Qatar, 5 quasars, 91 R-7 rocket, 126 racism, 66–67 radioisotope thermoelectric generators (RTGs), 168–69 radio telescopes, 91 radio waves, 28–29, 30, 31, 39, 90–91 radium, 96 RAND Corporation, 218 Ranger 7 spacecraft, 70 Reagan, Ronald, 5, 6 relativity, general theory of, 94–95, 101, 248, 250 relativity, special theory of, 195–96 Republicans, 4–5, 15, 17, 224–25 Resnik, Judith, 243 robots, 129, 134 in space exploration, 57, 89–90, 128, 130–32, 187, 198, 199, 202 rocket equation, 153–54, 157 rockets: flybys and, 157 liquid-fueled, 192 phallic design of, 222–23 propulsion of, see propulsion Rodriguez, Alex, 114 Röntgen, Wilhelm, 94, 96, 135 Royal Society, 216 Russia, xiv, 6, 22, 162, 168 ISS and, 319 Star City training center of, 73, 74, 207 Sagan, Carl, 27, 28, 43, 193, 256 Salyut space module, 6 Sarge (comedian), 234 satellites, xiii, xiv, 60, 71, 94 communication, 129 first US, 124–25 Saturn, 31, 82, 112, 115, 119, 138, 157, 168, 210, 225, 245 radio emissions from, 90–91 Saturn V rocket, 15, 127, 154, 158, 172, 214, 219, 220, 229 as a wonder of the modern world, 232–33 Schmitt, Harrison, 69, 132 Schwarzenegger, Arnold, 153 science, 206, 226 Arabs and, 205–6 discovery and, 98 emerging markets and, 209–10 literacy in, 57–59, 230–31, 235–36 multiple disciplines and, 209–10 Scientific American, 223 scientific method, 86 Scobee, Dick, 242 Seeking a Human Spaceflight Program Worthy of a Great Nation, 146 Senate, US, 5, 146, 328 Aeronautical and Space Sciences Committee of, 272 and appointments to Commission on Future of Aerospace Industry, 316 Appropriations Committee of, 321, 329 Commerce, Science, and Transportation Committee of, 288, 321, 323, 324, 329 sense of wonder, 64–65 September 11, 2001, terrorist attacks, 206 Sesame Street (TV show), 257 SETI (search for extraterrestrial intelligence), 41, 325 Shapley, Harlow, 98–101 Shatner, William, 180 Shaw, Brewster, 221 Shepard, Alan B., 114 short-period comets, 46 Siberia, 50 Sims, Calvin, 55–62 Sirius, 178 Skylab 1 (space station), 214 slingshot effect, 119–20 Smith, George O., 175 Smith, Michael, 242 Smithsonian Institution, 216 solar sails, 159, 165–67, 170 solar system, 34, 259 many-body problem and, 117–18 perturbation theory and, 118 solar wind, 176, 235, 245 solid rocket boosters, 155 Soter, Steven, 256 sound, speed of, 108–9 sound barrier, 109 South Africa, xiv South Pole, 76 Soviet Union, xiii, 8, 94, 133, 194, 215, 218 US rivalry with, 5–6, 59, 79, 87, 121–27, 133, 192, 219 see also Sputnik space, space exploration: colonization of, 57, 60, 102–3 cosmic microwave background in, 92, 94–95 cross-discipline endeavor in, 24–25, 230 culture and, 72–74, 147–48, 210–11 early attitudes toward, 217–18 economic motivation for, 200–201 factions against, 8–10 in Galef/Pigliucci interview of author, 75–83 inventions statute and, 311 justification for funding of, 78–81 militarization of, 60 numbers employed in, 236–37 politics and, 3–5 proposed programs and missions for, 201–2 robots and, 57, 89–90, 128, 130–32, 187, 198, 199, 202 significance of, 102 Soviet achievements in, 122–26 special interests and, 5, 236–37 stellar nurseries in, 93 technological innovation and, 12 US-Soviet rivalry and, 5–6, 59, 79, 87, 121–27, 133, 192, 219 war as driver of, 219–20 Space Cowboys (film), 162 Space Exploration Initiative, 8 Space Foundation, 221–22 Spaceguard Survey, The: Report of the NASA International Near-Earth Object Detection Workshop, 50 space junk, 176 space shuttle, 7, 12, 25, 109, 160–62, 165, 201, 202, 228, 281 contingency funding for, 321–22 fuel of, 158 launch costs of, 320–22 main parts of, 154–55 pricing policy for, 314 retirement of, 14–16, 143, 214 speed of, 222 use policy for, 312–13 weight of, 155 see also specific vehicles Space Station Freedom, 6, 8 Space Studies Board, 169 Space Technology Hall of Fame, 221, 230–31, 237 Space Telescope Science Institute, 10, 23, 135–36 Space Transportation System, 314 space travel, 191–98 coasting in, 247 in Colbert–author interview, 186–88 danger of, 198 financing of, 193–94 in Hollywood movies, 194–95 Moon missions and, 192–93 robots and, 198 special relativity and, 195–96 Space Travel Symposium, 111 Spain, 7, 87 spectroscopy, 30 Spirit (Mars exploration rover), 130–33, 138 Spitzer Space Telescope, 139 Sputnik, xiii, 5, 59, 79, 113–14, 133, 192, 218 50th anniversary of, 226 US response to, 122–24 Star City (training center), 73, 74, 207 Stars & Atoms (Eddington), 107 Star Trek (TV series), 3, 164, 170 45th anniversary of, 178–81 human behavior and, 180 technology of, 179 Star Trek: The Motion Picture (film), 37–38 Star Wars (film series), 131 State Department, US, 312 Stewart, Jon, 4 Stone, Sharon, 203 subatomic particles, 94 Sugar, Ron, 221 Sun, 27, 28, 29, 33, 46, 58, 72, 97, 112, 117, 118, 138, 195, 245 Copernican principle and, 34 energy emitted by, 93 fusion in, 101 neutrinos emitted by, 94 planets’ orbits and, 115 Superconducting Super Collider, 6–7, 80–81 Sweden, 7 Swift, Philip W., 223 Swift Gamma Ray Burst Explorer, 139 Switzerland, 7 Sykes, Wanda, 17 Systems of the World, The (Newton), 113 Taj Mahal, 88 Tamayo-Méndez, Arnaldo, 122 TASS, 123 Taylor, Charles E., 219 technology, 89, 200, 226 aero-space integration plan for, 323–24 in alien observation of Earth, 29–32 CRDAs policy on transfer of, 304–6 energy conservation and, 96 engineering, 95 Industrial Revolution and, 95 information, 95 leadership and, 23 multiple disciplines and, 135–37 nonsectarian philosophies and, 206 predicting future of, 215–16 progress in, 218–19 space exploration and, 135 of Star Trek, 179 US lag in, 21–22 telescopes, 71, 82, 85–86, 94, 141, 225 microwave, 91–92 radio, 91 ultraviolet, 93 Tereshkova, Valentina, 122 Texas, 6 Thompson, David, 221 three-body problem, 116–17 Three Gorges Dam, 22, 233 Three Mile Island meltdown, 168 Titan, 31 Huygens probe to, 138–39 methane on, 138–39 Today Show (TV show), 210–11 Tonight Show (TV show), 144–45 Toth, Viktor, 250 Townsend, W.

Paradox: The Nine Greatest Enigmas in Physics by Jim Al-Khalili

Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, butterfly effect, clockwork universe, complexity theory, dark matter, Edmond Halley, Edward Lorenz: Chaos theory, Ernest Rutherford, Henri Poincaré, Higgs boson, invention of the telescope, Isaac Newton, Johannes Kepler, Laplace demon, Large Hadron Collider, luminiferous ether, Magellanic Cloud, Olbers’ paradox, Pierre-Simon Laplace, Schrödinger's Cat, Search for Extraterrestrial Intelligence, The Present Situation in Quantum Mechanics, time dilation, Wilhelm Olbers

When choosing my greatest enigmas in physics, I have not homed in on the biggest unsolved problems—for example, what dark matter and dark energy, which between them make up 95 percent of the contents of our universe, are made of, or what, if anything, was there before the Big Bang. These are incredibly difficult and profound questions to which science has yet to find answers. Some, like the nature of dark matter, that mysterious stuff that makes up most of the mass of galaxies, may well be answered in the near future if particle accelerators like the Large Hadron Collider in Geneva continue to make new and exciting discoveries; others, like an accurate description of a time before the Big Bang, may remain unanswered forever. What I have aimed to do is make a sensible and broad selection. All the paradoxes I discuss in the following chapters deal with deep questions about the nature of time and space and the properties of the Universe on the very largest and smallest of scales.

…

But let’s quickly look at another real-world example, where this effect is important (we will come on to one more a bit later). The slowing down of time in high-speed travel is known as “time dilation” and is routinely taken into account in physics experiments, particularly those in which subatomic particles are accelerated in “atom smashers” such as the Large Hadron Collider at CERN in Geneva. There, particles can reach speeds so close to that of light that if such “relativistic” effects were not taken into account, the experiments would not make any sense. So, the lesson we learn from Einstein’s Special Theory of Relativity is that a consequence of the constancy of the speed of light is that time runs more slowly during high-speed motion.

Swimming With Sharks: My Journey into the World of the Bankers by Joris Luyendijk

activist fund / activist shareholder / activist investor, bank run, barriers to entry, Bonfire of the Vanities, bonus culture, collapse of Lehman Brothers, collective bargaining, corporate raider, credit crunch, Credit Default Swap, Emanuel Derman, financial deregulation, financial independence, Flash crash, glass ceiling, Gordon Gekko, high net worth, hiring and firing, information asymmetry, inventory management, job-hopping, Large Hadron Collider, light touch regulation, London Whale, Money creation, Nick Leeson, offshore financial centre, regulatory arbitrage, Satyajit Das, selection bias, shareholder value, sovereign wealth fund, the payments system, too big to fail

You have 1,000 vice-presidents vying for 10 managing director posts. People will do anything to get ahead – backbiting, backstabbing, the whole nine yards. For those of us who find life surrounded by other people difficult enough as it is, the requirement to network is hellish.’ After completing his PhD he worked on the Large Hadron Collider at CERN in Geneva. ‘Many people I know from back then are still at universities, doing research and climbing the slippery slope to professorships and fellowships. They work the same astonishingly long hours as I do, yet get paid a fraction. From a purely scientific perspective, they get to do some really, really interesting work.

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(Davies) 1 financial sector (see also bankers; banks; City; global financial crisis): amorality in 1, 2, 3, 4 ‘animal’ types within 1 blame culture in 1 blog’s negative comments on 1 Brown’s praise for 1 and caveat emptor 1, 2, 3, 4, 5, 6 and charity donations 1 code of silence governs 1, 2, 3, 4 competition vs co-operation in 1 countries/blocs played against each other by 1 ethical dilemmas in 1 immune to exposure 1 and insider jokes 1 IT’s role in 1, 2 and patches and workarounds 1 ‘map’ of 1 and mergers and acquisitions 1, 2, 3, 4 countries’ legal systems affected by 1 number of employees in 1 politicians identify with 1 post-crash books about 1, 2 PR people within 1, 2 and project finance 1 protest demonstrations against 1 regulators identify with 1 remuneration in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 bonuses 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 and leisure-time spending 1 restructuring in 1 scandals within 1, 2, 3 (see also rogue traders) Barings 1 FX 1, 2 HSBC 1, 2 JP Morgan 1, 2 LIBOR 1, 2, 3 London Whale, see Iksil, Bruno Société Générale 1 UBS 1 sport and war analogies within 1 whistle blowers within 1, 2, 3 women in, men’s attitudes towards 1 Financial Services Authority 1 Financial Times 1, 2 F9 model monkeys 1 Fool’s Gold (Tett) 1 Freud, Sigmund 1 Fukushima 1 FX scandal 1 GDP (gross domestic product) 1 Geithner, Timothy 1 Gekko, Gordon (film character) 1, 2 global financial crisis, see financial crash Goldman Sachs 1, 2, 3 as exception to short-termism 1 Geithner’s and Clinton’s lucrative speeches to 1 London trading floor of, a ‘toxic and destructive environment’ 1 as ‘pure’ investment bank 1 banking licence subsequently acquired by 1 Smith’s book on 1 Smith’s NYT piece on 1, 2 Goodfellas 1 greed 1, 2, 3, 4, 5, 6 gross domestic product (GDP) 1 Gross Misconduct: My Year of Excess in the City (Thompson) 1 Guardian: distrust of 1 finance blog of: first interviews posted on 1 ‘Going native …’ subtitle of 1 readers’ comments posted on 1, 2, 3, 4, 5, 6, 7, 8 responses to interviews on 1, 2 traditional banking said to be under-represented on 1 guardiannews.com/jlbankingblog, see under Guardian Haldane, Andrew 1 Halliburton 1 Hancock, Matthew 1 Harrington, William J 1 hedge funds 1, 2, 3 and ‘unorthodox’ investment strategies 1 high-frequency trading 1, 2, 3, 4 high-net-worth individuals 1 house prices 1 How I Caused the Credit Crunch: A Vivid and Personal Account of Banking Excess (Ishikawa) 1 HSBC 1 annual results announcement of 1, 2 and drugs money 1, 2 mixed investment–commercial nature of 1 human resources (HR) (see also recruitment), and redundancy 1, 2 Iksil, Bruno (‘London Whale’) 1, 2 incentives: and accountancy firms 1 ‘perverse’ 1, 2, 3, 4, 5 need to remove 1 short-termism encouraged by 1 Initial Public Offering (IPO) 1, 2 insurance: banking’s overlap with 1 enormous reach of 1 investment banks (see also banks): ‘animal’ types within 1 books about 1 as ‘casinos’ 1, 2, 3 and ‘castes’ 1 vs commercial 1, 2 commercial banks begin to take over 1 culpability of, in global financial crash 1 daily routine of 1, 2, 3 definition of, clarified 1 and dot-com bubble 1, 2, 3 job titles within 1, 2, 3 radically changed ownership structure of 1 and risk and compliance 1, 2, 3, 4, 5, 6 (see also regulators) risk-taker–risk-bearer dichotomy in 1 and ‘rock’n’roll trader’ 1 speculation by 1 subcultures engendered by 1 Iraq 1 Ishikawa, Tetsuya 1 IT 1, 2 jlbankingblog, see under Guardian job titles, in investment banks 1, 2, 3 JP Morgan 1 Blair’s role in 1, 2, 3 rogue trader at 1, 2 Kerviel, Jérôme 1 KPMG 1 Krugman, Paul 1 Lagarde, Christine 1 Large Hadron Collider 1 Leeson, Nick 1 Lehman Brothers: capital buffers of 1 collapse of 1, 2, 3, 4, 5 inadequate buffers of 1 as ‘pure’ investment bank 1 Lewis, Michael 1 Liar’s Poker (Lewis) 1, 2 LIBOR scandal 1, 2, 3 Lloyds, annual results announcement of 1, 2 London riots 1 London Stock Exchange, and ‘my word is my bond’ 1, 2 London Whale, see Iksil, Bruno Master of the Universe 1, 2, 3 Masters of Nothing: How the Crash Will Happen Again Unless We Understand Human Nature (Hancock, Zahawi) 1 Masters of the Universe 1 passim, 1, 2 (see also banker types) cold fish’s scorn for 1 criticism of sector resented by 1 sector readily defended by 1 megabanks 1 (see also banks) mergers and acquisitions 1, 2, 3, 4 countries’ legal systems affected by 1 Merrill Lynch 1 middle office 1, 2, 3, 4, 5 more power and status in, post-crash 1 Monkey Business: Swinging through the Wall Street Jungle (Rolfe, Troob) 1 Moody’s 1, 2 Morgan Grenfell 1 My Life as a Quant (Derman) 1 ‘my word is my bond’ 1, 2 neutrals 1, 2, 3, 4, 5, 6, 7 (see also banker types) in political parties 1 New York Times 1, 2, 3, 4 9, 5 trader exploits 1 Nissen, George 1 Occupy London 1 operational risk 1 The Origin of Financial Crises (Cooper) 1 ‘other people’s money’ mentality 1 Oxfam 1 Paulson, Hank 1 Permanent Subcommittee on Investigations (US) 1 politicians: as best chance to wrest power from financial sector 1 identification of, with financial sector 1 justified cynicism about 1 neutrals among 1 powerlessness of, in face of global finance 1 private schools formerly attended by 1 teeth grinders among 1 project finance 1, 2 prop trading 1, 2, 3, 4 Prudential Regulation Authority 1 PwC 1 quants (quantitative analysts) 1, 2, 3, 4 ‘animal’ types among 1 with Asperger’s 1, 2 geeks among 1 rating agencies 1, 2, 3, 4, 5 and CDOs 1 Moody’s 1, 2 ‘oligopoly’ of 1 paid by banks 1 RBS, annual results announcement of 1, 2 recruitment 1, 2 (see also redundancy) and short-termism 1 redundancy 1, 2, 3, 4, 5, 6 (see also recruitment) as ‘enhanced severance’ 1 as rite of passage 1 termed ‘the cull’ 1 in UK vs US 1, 2 and work-related visas 1 regulators 1 fighting symptoms rather than cause 1 and Financial Services Authority, Financial Conduct Authority, Prudential Regulation Authority 1 identification of, with financial sector 1 ‘idiots’ description applied to 1, 2 ‘losing people at all levels’ post-crash 1 numbers working for 1 and self-declaration 1 religion 1 remuneration 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 bonuses 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 and leisure-time spending 1 restructuring 1 riots, in London 1 risk: ability to weigh 1 and departmental specialisations 1 managers, salaries of 1 operational 1 sovereign 1 takers of vs bearers of 1 risk and compliance 1, 2, 3, 4, 5, 6 (see also regulators) disparaged 1 and self-declaration 1 ‘rock’n’roll trader’ 1 rogue traders 1 at Barings 1, 2 at JP Morgan 1 at Société Générale 1 at UBS 1, 2 Rosenbaum, Ron 1 Rubin, Robert 1 Rusbridger, Alan 1 Saddam Hussein 1 Salomon Brothers 1 Samuel Montagu 1 Sants, Hector 1 scandals 1, 2, 3 (see also rogue traders) Barings 1 FX 1, 2 HSBC 1, 2 JP Morgan 1, 2 LIBOR 1, 2, 3 London Whale, see Iksil, Bruno Société Générale 1 UBS 1 school system, UK 1 Schroders 1 Schumer, Charles E 1 short-termism 1, 2 Sid (trader, broker) 1 passim, 1, 2 Smith Brothers 1 Smith, Greg 1, 2, 3, 4 social Darwinism 1 Société Générale 1 mixed investment–commercial nature of 1 Sorkin, Andrew Ross 1 sovereign risk 1 Sports Illustrated 1 Square Mile, see City Stcherbatcheff, Barbara 1 Stock Exchange, former 1 Summer, Lawrence 1 ‘tax optimisation’ 1 technical analysis 1 teeth grinders 1, 2, 3, 4 (see also banker types) in political parties 1 Tett, Gillian 1 ‘too big to fail’ 1, 2, 3, 4 and ability to blackmail 1 ‘too big to manage’ 1 Traders, Guns and Money (Das) 1 Twin Towers: terrorist attacks on 1, 2 trader exploits 1 UBS 1 rogue trader at 1 van Ees, Peter 1 Van Rompuy, Herman 1 venture capitalists 1 Verey, Michael 1 volatility 1 Voss, Rainer 1, 2, 3 Wall Street 1, 2, 3 Watergate 1 Wawoe, Kilian 1, 2 Weber, Axel 1 Weiser, Stanley 1 whistle blowers 1, 2, 3 ‘Why I Am Leaving Goldman Sachs’ (Smith) 1, 2 Why I Left Goldman Sachs (Smith) 1 The Wolf of Wall Street 1 Wolfe, Tom 1 working hours 1, 2, 3 World Trade Center: terrorist attacks on 1, 2 trader exploits 1 Zahawi, Nadhim 1 About the Author Joris Luyendijk was born in Amsterdam.

The Milky Way: An Autobiography of Our Galaxy by Moiya McTier

affirmative action, Albert Einstein, Arthur Eddington, Burning Man, Cepheid variable, cosmic microwave background, cosmological constant, dark matter, Eddington experiment, Edward Charles Pickering, Ernest Rutherford, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, heat death of the universe, Henri Poincaré, Higgs boson, Isaac Newton, James Dyson, James Webb Space Telescope, Karl Jansky, Kickstarter, Large Hadron Collider, Magellanic Cloud, overview effect, Pluto: dwarf planet, polynesian navigation, Search for Extraterrestrial Intelligence, Stephen Hawking, the scientific method

They’ve built detectors that they hoped would be sensitive enough to perceive the tiny amount of energy produced when a hypothetical dark matter particle collides with the nucleus of a normal atom, usually xenon or germanium. Your scientists have even attempted to make their own WIMPs in that big Swiss ring they call the Large Hadron Collider. It’s been forty years—a long time for you humans!—and your scientists still haven’t given up hope of finding the WIMPs. But their lack of success has urged them to consider other possible explanations for dark matter. Most of the particles I’ve mentioned thus far—photons, Higgs boson, quarks, but not the hypothetical WIMP—are part of your scientists’ standard model of particle physics.

…

It is a theoretical way for black holes to dissipate their energy. Pairs of particles form on the boundary between a black hole and the vacuum of space, except the particles are just as likely to be on the outside of the black hole as the inside. The particles on the outside escape and carry a tiny bit of the black hole’s energy with them. 2The Large Hadron Collider is a giant circular tunnel built underground in Switzerland. Particles rush around the 16.6-mile circumference, building up speed before they crash into each other with enough energy to produce other, more exotic particles. Chapter Fourteen: Doomsday 1To hear how I believe the nine worlds of Norse mythology line up with the planets in our solar system, listen to the “Norse Cosmology” episode of the Spirits podcast.

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

That’s generally a fine way to think, as long as your confidence in x is high and y isn’t superimportant. But when you’re talking about something that could radically determine the future (or future existence of) humanity, 75 percent confidence isn’t enough. Nor is 90 percent enough, or 99 percent! We’d never have built the Large Hadron Collider if there was a 1 percent (let alone 10 percent) chance of its actually spawning black holes that consumed the world—there were, instead, extremely compelling arguments against that. Let’s see whether those compelling reasons not to worry about AGI exist, and if not, let’s make our own. A NEW WISDOM OF THE BODY ERIC J.

…

Perhaps, given all the information we have about nature, some machine will actually come up with the right answers; indeed, perhaps some physicists have already come up with the answers. But the true role of data is to confirm which answers are the correct ones. If some physicist or some machine figures it out, they have no way to convince anyone else that they have the actual answer. Laboratory dark matter detectors or the CERN Large Hadron Collider or possibly a future Chinese collider might get the needed data, but not a thinking machine. ARE WE GOING IN THE WRONG DIRECTION? SCOTT ATRAN Anthropologist, Centre National de la Recherche Scientifique, Paris; author, Talking to the Enemy: Violent Extremism, Sacred Values, and What It Means to Be Human Machines can perfectly imitate some of the ways humans think all of the time, and can consistently outperform humans on some thinking tasks all of the time, but computing machines as usually envisioned will not get human thinking right all of the time, because they process information in ways opposite to humans’ in domains associated with human creativity.

…

It’s possible in some special cases (e.g., mathematics and some parts of physics) to advance knowledge through pure reasoning. But across the spectrum of scientific activity, scientific knowledge advances almost exclusively by the collection of empirical evidence for and against hypotheses. This is why we built the Large Hadron Collider, and it’s why all engineering efforts involve building and testing prototypes. This step is clearly feasible, and indeed there already exist some “automated scientists.” Second, these experiments must discover new simplifying structures that can be exploited to sidestep the computational intractability of reasoning.

Tracers in the Dark: The Global Hunt for the Crime Lords of Cryptocurrency by Andy Greenberg

2021 United States Capitol attack, Airbnb, augmented reality, bitcoin, Bitcoin Ponzi scheme, Black Lives Matter, blockchain, Brian Krebs, Cody Wilson, commoditize, computerized markets, COVID-19, crowdsourcing, cryptocurrency, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, forensic accounting, Global Witness, Google Glasses, Higgs boson, hive mind, impulse control, index card, Internet Archive, Jeff Bezos, Julian Assange, Large Hadron Collider, machine readable, market design, operational security, opioid epidemic / opioid crisis, pirate software, Ponzi scheme, ransomware, reserve currency, ride hailing / ride sharing, rolodex, Ross Ulbricht, Satoshi Nakamoto, Skype, slashdot, Social Justice Warrior, the market place, web application, WikiLeaks

That drive to create a kind of hive-mind calculator of epic proportions—how to efficiently split problems of gargantuan complexity between dozens, hundreds, or thousands of normal computers—carried him through a PhD and into a career working on quantum physics visualizations and early virtual reality demonstrations. By the time he was forty, he was managing a group of computer scientists who worked with the European Organization for Nuclear Research—also known as CERN—tasked with storing and interpreting the petabytes of results from the Large Hadron Collider’s search for the Higgs boson, which produced hundreds of times as much data as the entire collection of the Library of Congress every year. Gronager was now building computer systems to grapple with some of the most massive data sets in the world. But he wasn’t particularly interested in solving the mysteries of the universe’s subatomic composition.

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GO TO NOTE REFERENCE IN TEXT A YouTube video of Karpelès: Patrick Nsabimana, “MtGox CEO Mark Karpales Interrupted by Protester at MtGox Headquarters,” YouTube, Feb. 15, 2014, youtube.com. GO TO NOTE REFERENCE IN TEXT A central pillar of the Bitcoin economy: Matthew Kimmell, “Mt. Gox,” CoinDesk, July 22, 2021, coindesk.com. GO TO NOTE REFERENCE IN TEXT the Large Hadron Collider’s search: “Storage,” CERN, home.cern. GO TO NOTE REFERENCE IN TEXT The 2011 Prague conference: “European Bitcoin Conference 2011, Prague Nov. 25–27,” forum thread on Bitcointalk, Aug. 30, 2011, bitcointalk.org. GO TO NOTE REFERENCE IN TEXT programmer named Amir Taaki: Andy Greenberg, “How an Anarchist Bitcoin Coder Found Himself Fighting ISIS in Syria,” Wired, March 29, 2017, wired.com.

…

Gox theft case and, 100, 103–5, 118, 120 Kennedy, Maddie, 310–12 kingpin statute, 18, 219 Kober, Alice, 44 Korean National Police Agency. See National Police Agency (South Korea) Kraken (cryptocurrency exchange), 91, 96, 99–100 Krebs, Brian, 57–8 Kryptos (sculpture), 43 L Laos, 162 Large Hadron Collider, 96 Lazarus Group, 288 Lebua (Bangkok hotel), 166 Lee, Youli: Welcome to Video case and, 269–71, 279–80 Lehman Brothers, 94 Levchenko, Kirill, 46, 52 Levin, Jonathan: AlphaBay case and, 168–70, 199–202 at Chainalysis, 137–8, 200 Gambaryan, Tigran, and, 199–201, 238–9, 292 Individual X case and, 292–4 Welcome to Video case and, 243–6, 283 Liberty Reserve (cryptocurrency), 291 Line (messaging app), 205 Linear A, 44 Linear B, 44 Linux Unified Key Setup, 183 Liu, Jesse, 283 LocalBitcoins (peer-to-peer exchanger), 152 Love Zone (CSAM website), 191 Luno (cryptocurrency exchange), 324 Lysyanskaya, Anna, 45 M M (Thai agent), 212–13 Manchin, Joe, 34 Mandiant, 296 Mansoor, Ahmed, 310–11 Marion, Louisa: Cazes, Alexandre, case and, 175, 185, 204, 209, 215–16 Dutch police takeover of Hansa and, 191 Marriott (Bangkok hotel), 238 Maxwell, Gregory, 61–2, 107 May, Timothy, 28–30, 33, 37 McCoy, Damon, 62 McMillan, Robert, 336 Mehrotra, Kartikay, 345 Meiklejohn, Sarah: biography of, 43–5 Bitcoin traceability and, 41–3, 46–7 blockchain analysis by, 42–3, 48–56 Chainalysis job offer to, 319–20 clustering techniques developed by, 51, 53, 84, 100, 170 “Fistful of Bitcoins” paper by, 55–6, 59, 98, 320 Greenberg, Andy, and, 59–60, 320–3 Gronager, Michael, and, 319–20 Krebs, Brian, and, 58 mother of, 43 privacy coin research by, 300 at University College London, 319 views on privacy of, 44–5, 61–2, 320–3 Weaver, Nick, and, 84 Zcash study by, 323 Merz, Cade, 336 Miller, Robert (pseud.): AlphaBay case and, 144–5, 148, 154–5, 158–60, 164, 167, 185, 209, 215 at Athenee hotel, 205–6 Baltimore Task Force and, 161 biography of, 143–4 dark web drug cases and, 153–4 Mohammad, Michael Rahim, 281 Møller, Jan, 101–2, 105–7, 169.

But What if We're Wrong? Thinking About the Present as if It Were the Past by Chuck Klosterman

a long time ago in a galaxy far, far away, Affordable Care Act / Obamacare, British Empire, citizen journalism, cosmological constant, dark matter, data science, Easter island, Edward Snowden, Elon Musk, Francis Fukuyama: the end of history, Frank Gehry, George Santayana, Gerolamo Cardano, ghettoisation, Golden age of television, Hans Moravec, Higgs boson, Howard Zinn, Isaac Newton, Joan Didion, Large Hadron Collider, Nick Bostrom, non-fiction novel, obamacare, pre–internet, public intellectual, Ralph Nader, Ray Kurzweil, Ronald Reagan, Seymour Hersh, Silicon Valley, Stephen Hawking, TED Talk, the medium is the message, the scientific method, Thomas Kuhn: the structure of scientific revolutions, too big to fail, Y2K

And so they could presumably prevent their simulated creatures from crashing the simulation or discovering its limitations.” Well, fine. I give up. Pour me a drink. Simulate me, don’t simulate me—it’s all equally hopeless. We’re just here, and there’s nowhere else to be. [8]Particle Fever is a 2013 documentary about the Large Hadron Collider in Switzerland. It depicts the final seven years of the five-decade search for the Higgs boson, the so-called God particle at the core of everything we believe about deep physics and the origin of existence. The film is elucidated through the words of many perceptibly brilliant people, a few of whom spend much of the movie expressing dark apprehension over what will happen if the massive $9 billion LHC does not locate the Higgs particle.

…

., 17, 218 “Killing of Osama bin Laden, The” (Hersh), 151–53 King, Stephen, 27–28 Klosterman, Chuck, background, 195–96 Klosterman’s Razor, 17, 42–43 Knausgaard, Karl Ove, 213 Koko (gorilla), 255–56 Krakauer, Jon, 52 Kuhn, Thomas, 114–16, 224–26 Kurzweil, Ray, 228 L.A. Noire (video game), 128–29 language describing colors, 147–48 permanence of words, 19–21 TV dialogue, 166–67 unfamiliarity of, 57 Large Hadron Collider (LHC), 130–31 Lear, Norman, 173 Led Zeppelin, 60n Lennon, John, 60n, 67n, 86 Lethem, Jonathan, 86–87 Lewis, Jerry Lee, 60n, 79 Lewis, Sinclair, 92 lies and untruths, 154–57 life after death, 11–12 Limbaugh, Rush, 185 Lincoln, Abraham, 24, 96, 173n, 218 Linklater, Richard, 139–44, 150–51 literature, criticism of, 7–8, 10 London Review of Books, 151 lucid dreaming, 137, 141 Lugar, Richard, 260 MacCambridge, Michael, 181 machines, and attempts to kill people, 227 Mad Men (TV show), 164–65 Madison, James, 207, 210 Mahler, Jonathan, 152 Man Without a Country, A (Vonnegut), 43 Manhattan, attack on police in, 150–51 marching music, 64–65 marginalization, 41–42, 81 Marley, Bob, 65 Marlowe, Christopher, 94 “Mathematics of the Past” (Kasparov), 136 Mathog, Mike, 109n Matrix, The (film), 28–30, 122n, 227 Maugham, W.

Generation A by Douglas Coupland

Burning Man, call centre, Drosophila, Higgs boson, hive mind, index card, Large Hadron Collider, Live Aid, Magellanic Cloud, McJob, Neil Armstrong, new economy, post-work, Ronald Reagan, Silicon Valley, stem cell, Stephen Hawking

How amazing to see all that mythology acting itself out in real time, fuelled by genuine human sentience! Real life can be mythologically sci-fi, too. For example, my father spends five days a week at CERN, on the French side of Geneva, and is technically only a hundred metres away from its Large Hadron Collider. Soon he’ll be moving to offices closer to the Low Energy Antiproton Ring. If that’s not sci-fi, what is? So anyway, on the flight to Sweden—specifically to the town of Solna, outside Stockholm, home of the European Centre for Disease Prevention and Control—I spoke at length about the Yamato and World of Warcraft to the three militarytards minding me.

…

Here’s what happened: we were at the Compact Muon Solenoid facility, where my father had two friends who worked in a big, ugly underground chamber that looked like the jumbo insides of an air conditioner and went on for twenty-five kilometres. One might wonder what a Compact Muon Solenoid is. I did. It’s a 12,500-ton digital camera with 100 million pixels that takes 3-D pictures of Large Hadron Collider collisions 40 million times per second. Want more? There were twenty people with me in the group—a few scientists, my father and a polytechnic school group from Marseilles. The adults were arguing about whether we were technically in France or Switzerland, while the students were discussing Higgs Boson particles and their stamp collections and staring at me like I was a rare animal.

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

We may not be sure what a “particle” is, said Schrödinger, but “we have now gained [insight] into what it is not; it is not a durable little thing with individuality.” All we have from experiments are the records of events, which we examine long after the events have happened—an observation that is, if anything, even more true today of experiments involving machines like the Large Hadron Collider than it was for the simpler experiments of Schrödinger’s day. If we see an electron in position A, and later (even a split second later) see an electron in nearby (even very nearby) position B, we have no way of knowing whether it is, in fact, the same electron. And particles which have neither well-defined trajectories nor well-defined individuality simply are not particles.

…

Halifax, Lord Halley, Edmond Hamilton, William Hasenöhrl, Friedrich (Fritz) Heidelberg Heisenberg, Werner: concept of half-integer quantum numbers; concept of quantum uncertainty; Copenhagen Interpretation; education and career; influence; matrix mechanics; Nobel Prize; Physics and Beyond; relationship with Schrödinger; Schrödinger’s view of his work; Solvay Congress; theory of quantum world; work on quantum jumps Heisenberg’s Uncertainty Principle Heitler, Walter Heligoland Hemingway, Ernest Herbert, Nick heredity Hertz, Heinrich Hess, Victor Hibben, John hidden variables Hindenberg, Field Marshal Hiroshima, nuclear bombing Hitler, Adolf: Austrian policy; defeat of France; imprisonment; invasion of Austria; invasion of Soviet Union; letter to Schrödinger; rise to power Hooke, Robert Hoover, Herbert Humboldt, Alexander von Huygens, Christiaan hydrogen atom IBM Research Center ICI (Imperial Chemical Industries) imaginary numbers In Search of the Multiverse (Gribbin) In Search of Schrödinger’s Cat (Gribbin) Innitzer, Cardinal Innsbruck: March household; meeting of German scientists (1924); professorship offer; quantum teleportation experiments; Schrödinger at interference pattern International Atomic Energy Agency Inward Bound (Pais) Irish Times Italian Physical Society Ithi, see Junger Jeans, James Jena Jennings, David Jews: anti-Semitism; in Austria; Einstein’s career; Hansi’s background; Lindemann’s aid to scientists; Nazism in Austria; Nazism in Germany; Schrödinger’s position Johns Hopkins University Jordan, Pascual Jung, Carl Junger, Itha (Ithi) Kavanagh, Patrick Kepler, Johannes Khrushchev, Nikita kinetic theory King’s College, London Kirchhoff, Robert Klein, Oskar Klimt, Gustav Kohlrausch, Fritz Kolbe, Ella Krauss, Felicie Krauss, Karl and Johanna Landé, Alfred Langevin, Paul Laplace, Pierre-Simon Large Hadron Collider lasers Laue, Max von: career; Schrödinger’s visit; view of Copenhagen Interpretation; work on X-ray crystallography laws of motion Lean, Lena Lehrbuch der Physik Leiden Leipzig Lemaître, Georges Lenard, Philipp light: Einstein’s work; faster-than-light communication; momentum; Newton’s work; particle theory; Planck’s work; polarized; quanta, see photons; Schrödinger’s work; spectroscopy; speed; wave theory Lindemann, Frederick Alexander Listener, The Lockheed Martin Lockyer, Joseph London, Fritz London: Imperial College; King’s College; University College Loschmidt, Josef MacEntee, Barbara MacEntee, Máire MacEntee, Margaret (née Browne) MacEntee, Seámus Mach, Ernst McCrea, William Madison Madrid magnetism Many Worlds Interpretation (MWI) March, Arthur: death; illness; in Innsbruck; Italian holiday; marriage; Oxford post; Princeton question; relationship with Schrödinger; return to Innsbruck March, Hilde: Arthur’s death; Arthur’s illness; in Belgium; birth of daughter; birth of grandson; in Dublin; education; in Graz; marriage; in Oxford; pregnancy; relationship with Schrödinger; return to Innsbruck March, Ruth George Erica (Schrödinger’s daughter), see Braunizer Mark, Hermann Marsden, Ernest matrices matrix mechanics Maxwell, James Clerk: achievements; background; death; education and career; influence; marriage; Maxwell distribution; statistical techniques; theory of electromagnetism; Treatise on Electricity and Magnetism; work on light May, Sheila Meitner, Lise Mendel, Gregor Michelson, Albert Millikan, Robert Andrews Minkowski, Hermann molecules: arrangements of atoms; Bohr’s work; Boltzmann’s work; Copenhagen Interpretation; DNA; formation; genes; Heisenberg’s work; helical structure; “of life”; Loschmidt’s work; macroscopic entanglement; Maxwell’s work; quantum computing; quantum teleportation; RNA; Schrödinger’s work momentum: Bohr’s work; Compton’s work; de Broglie’s work; Einstein’s work; EPR Paradox; Heisenberg’s work; law of conservation of; matrix mechanics; Newton’s laws; Schrödinger’s work Moore, Walter Morgan, Thomas Hunt Morley, Edward Moscow Declaration (1943) Mount Wilson experiment (1921) Multiverse Mussolini, Benito mutation Myles, see O’Nolan Nagasaki, nuclear bombing Napoleon National Academy of Sciences, US National University of Ireland Natural Philosophy of Cause and Chance (Born) Nature Nature of the Chemical Bond, The (Pauling) Naturwissenschaften, Die Nernst, Walther New York Newton, Isaac: education and career; laws of motion; laws of physics; Opticks; Principia; theory of gravity; work on light Nobel Committee Nobel Prize: Blackett (1948); Bohr (1922); Born (1954); Cockcroft (1951); Compton (1927); Crick (1962); Delbrück (1969); Dirac (1933); Einstein (1921); Heisenberg (1932); Hess (1936); Laue (1914); Millikan (1923); Pauling (1954); Planck (1918); Rutherford (1908); Schrödinger (1933); Walton (1951); Watson (1962); Wilson (1927) Nolan, Kate nuclear physics O’Brien, Conor Cruise O’Nolan, Brian (“Myles”) Opticks (Newton) Ortega, José Ostwald, Wilhelm Oxford Pagels, Heinz Pais, Abraham particle mechanics particle theory particles: alpha; anti-particles; beta; Bohr’s work; Born’s work; Bose’s work; bosons; Copenhagen Interpretation; Crick’s work; de Broglie’s work; Einstein’s work; entangled; fermions; Heisenberg’s work; Maxwell’s work; momentum; negatively charged (electrons); Newtonian physics; Newton’s work on light; number in Universe; phase space; photons; positively charged (protons); quantum chemistry; quantum teleportation; quantum transaction; radiation resistance; Schrödinger’s work; Solvay Congress; spin; “spooky action at a distance”; statistical mechanics; subatomic trajectory in cloud chamber; waves and; Young’s work Pauli, Wolfgang: career; Dublin visit; Feynman’s Princeton talk; on half-integer quantum numbers; Heisenberg’s letters; on matrix mechanics and wave mechanics; on measurement of atom; Solvay Congress Pauling, Linus phase space Philosophical Magazine photons: Aspect’s experiments; Bell’s work; Bose–Einstein statistics; Bose’s work; Clauser’s experiment; clones of; Compton’s work; Einstein’s work; entangled; green pamphlet on; light quanta; momentum; Planck’s work; polarization; quantum computing; quantum cryptography; quantum teleportation; Schrödinger’s work; Solvay Congress (1927); term photosynthesis Physica Physical Review Physical Review Letters Physics Physics and Beyond (Heisenberg) Physics Institute Physics World pilot wave model Pisa Planck, Max: career; discovery of “energy elements” (quanta); honours; influence; Nobel Prize; relationship with Schrödinger; Solvay Congress; successor at Berlin; work on black body radiation; work on electromagnetic radiation Planck’s Constant Podolsky, Boris Poincaré, Henri Pontifical Academy of Sciences positron Princeton: Bohm’s dismissal; Einstein Archive; Einstein at; Feynman at; Institute of Advanced Study; Schrödinger’s lectures Principia (Newton) probabilities: Born’s work; Copenhagen Interpretation; de Broglie’s work; Einstein’s work; Heisenberg’s work; quantum world; Schrödinger’s work; statistical rules probability wave Proceedings of the American Philosophical Society Proceedings of the Cambridge Philosophical Society Proceedings of the Royal Irish Academy Proceedings of the Royal Society proteins Prussian Academy quanta: Bohr’s work; Einstein’s work; light, see photons; Millikan’s experiments; Planck’s energy elements quantum chemistry quantum computers quantum cryptography quantum entanglement, see entanglement quantum jumps quantum mechanics: Aspect’s experiments; Bell’s work; Bohm’s work; Born and Jordan’s work; Copenhagen Interpretation; Cramer’s work; development; Dirac’s work; Eddington’s work; Einstein’s work; Heisenberg’s work; Innsbruck meeting (1924); interpretations of; Many Worlds Interpretation; and reality; Schrödinger’s cat; Schrödinger’s work; Solvay Congress (1927); superposition of states; term; transactional interpretation; transformation theory quantum numbers quantum physics: absurdity of; accuracy of; archives; Bohr’s work; “central mystery”; chemistry; chess board analogy; de Broglie’s work; development of; Einstein’s work; first version; Heisenberg’s work; lasers; and reality; Schrödinger’s work; second quantum revolution quantum reality quantum revolution: first; second quantum spin, see spin quantum states quantum statistics quantum teleportation quantum theory: birth of; Bohr’s work; Clauser’s experiments; cosmology and; education in; Einstein’s work; founding fathers; Heisenberg’s work; Rudolph’s work; Schrödinger’s work; statistical approach and Quantum Theory (Bohm) Quantum Theory and Measurement (ed.

Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room by David Weinberger

airport security, Alfred Russel Wallace, Alvin Toffler, Amazon Mechanical Turk, An Inconvenient Truth, Berlin Wall, Black Swan, book scanning, Cass Sunstein, commoditize, Computer Lib, corporate social responsibility, crowdsourcing, Danny Hillis, David Brooks, Debian, double entry bookkeeping, double helix, Dr. Strangelove, en.wikipedia.org, Exxon Valdez, Fall of the Berlin Wall, future of journalism, Future Shock, Galaxy Zoo, Gregor Mendel, Hacker Ethic, Haight Ashbury, Herman Kahn, hive mind, Howard Rheingold, invention of the telegraph, Jeff Hawkins, jimmy wales, Johannes Kepler, John Harrison: Longitude, Kevin Kelly, Large Hadron Collider, linked data, Neil Armstrong, Netflix Prize, New Journalism, Nicholas Carr, Norbert Wiener, off-the-grid, openstreetmap, P = NP, P vs NP, PalmPilot, Pluto: dwarf planet, profit motive, Ralph Waldo Emerson, RAND corporation, Ray Kurzweil, Republic of Letters, RFID, Richard Feynman, Ronald Reagan, scientific management, semantic web, slashdot, social graph, Steven Pinker, Stewart Brand, systems thinking, technological singularity, Ted Nelson, the Cathedral and the Bazaar, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Whole Earth Catalog, X Prize

And for the most part, that works very well, especially since the system is constructed so that generally you can proceed to get more information if necessary: You can follow the footnotes, or check the population figures against a second source, without the cost and expense of commissioning your own phalanx of census-takers. Our system of knowledge is a clever adaptation to the fact that our environment is too big to be known by any one person. A species that gets answers and can then stop asking is able to free itself for new inquiries. It will build pyramids and eventually large hadron colliders and Oreos. This strategy is perfectly adapted to paper-based knowledge. Books are designed to contain all the information required to stop inquiries within the book’s topic. But now that our medium can handle far more ideas and information, and now that it is a connective medium (ideas to ideas, people to ideas, people to people), our strategy is changing.

…

The institutions of science are not vanishing. Universities still confer degrees, funding agencies still provide grants, laboratories still accumulate equipment far beyond the means of curious amateurs. When someone pronounces about, say, physics, it still matters a great deal if that person is a senior scientist working on the Large Hadron Collider or is a self-taught hobbyist with a theory gleaned from some local blogs. But you no longer need to be standing on top of a wall to make your proclamations. Indeed, because we for the first time have a single medium for information, communication, and sociality, science cannot stay behind its institutional walls.

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

When it was announced in 1990, the human genome project was regarded as the greatest single data-gathering project in history, but the plunging cost of DNA sequencing means that multiples of its data are now churned out every year. This data is increasing rapidly and is widely distributed, making it impossible to study all of it comprehensively.22 The Large Hadron Collider generates too much data to even store on site, meaning that only certain kinds of events can be stored, leading to criticisms that once the Higgs boson particle was discovered, the data was unsuitable for discovering anything else.23 All science is becoming the science of big data. It’s this realisation that brings us back to Moore’s law – and Eroom’s.

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., 72–3 Galton, Francis, 140 game developers, 130 Gates’s law, 83 GCHQ (Government Communications Headquarters), 167, 174, 176–9, 189 genocide, 243 ghost cars (Uber), 118–9 G-INFO, 190 global mass surveillance, 179–80 Global Positioning System (GPS), 36–7, 42–3 Global Seed Vault, 54 global warming, 73, 193, 214 Glomar response, 165, 186 Godard, Jean-Luc, 143 Google, 84, 139, 230, 242 Google Alerts, 190 Google Brain project, 139, 148, 149, 156 Google Earth, 35–6 Google Home, 128–9 Google Maps, 177 Google Translate, 147–8, 156 Government Communications Headquarters (GCHQ), 167, 174, 176–9, 189 GPS (Global Positioning System), 36–7, 42–3 Graves, Robert, 159 Gravity’s Rainbow (Pynchon), 128 gray zone, 212–4 Great Nōbi Earthquake, 145 Greenland, 57–8 Green Revolution, 53 Greyball programme, 119, 120 guardianship, 251–2 H Hankins, Thomas, 102 Haraway, Donna, 12 Harvard Mark I machine, 30 Hayek, Friedrich, 156–7 The Road to Serfdom, 139 The Sensory Order: An Inquiry into the Foundations of Theoretical Psychology, 138–9 HealthyFoodHouse.com (website), 231–2 Heller, Joseph Catch-22, 187–8 Hermes, 134 Hersh, Seymour, 164 Hewlett-Packard, 143 hidden technological processes, 120 high-frequency trading, 14, 106–7, 108, 122, 124 high-throughput screening (HTS), 95–6 Hillingdon Hospital, 110–1, 111 Hippo programme, 32 Hofstadter, Douglas, 205–6 Hola Massacre, 170 homogenitus, 195, 196 Horn, Roni, 50, 201 How-Old.net facial recognition programme, 141 ‘How the World Wide Web Just Happened’ lecture, 78 HTS (high-throughput screening), 95–6 Hughes, Howard, 163 Hughes Glomar Explorer, 163–5 human genome project, 93 Human Interference Task Force, 251 human violence, 202 Humby, Clive, 245, 246 Hwang Woo-suk, 86–8 hyperobjects, 73, 75, 76, 194 hypertext, 79 I IBM Selective Sequence Electronic Calculator (SSEC), 30, 30–2, 31, 146 ICAO (International Civil Aviation Organisation), 68 ICARDA (International Center for Agricultural Research in the Dry Areas), 53–4, 55 ICT, 60–2 image recognition, 139–40 Infinite Fun Space, 149–50, 156 information networks, 62 information superhighway, 10 Infowars (Jones), 207 In Place of Fear (Bevan), 110 Institute of the Aeronautical Sciences, 26 integrated circuits, 79, 80 Intel, 80 International Center for Agricultural Research in the Dry Areas (ICARDA), 53–4, 55 International Civil Aviation Organisation (ICAO), 68 International Cloud Atlas, 195 Internet Research Agency, 235, 237 Inuit Knowledge and Climate Change, 199 The Invisibles (Morrison), 196–7 Isaksen, Ketil, 54 ISIL, 212–3 J Jameson, Fredric, 205 Jelinek, Frederick, 146–7 Jones, Alex Infowars, 207 Joshi, Manoj, 68–9 journalism, automated, 123–4 just-in-time manufacturing, 117 K K-129, 162–3 Karma Police operation, 175 Kasparov, Garry, 148–9, 157–8 Keeling Curve, 74, 74 Kennedy, John F., 169–70 Kinder Eggs, 215–6 Kiva robots, 114 Klein, Mark, 176–7 Kodak, 143 Krakatoa, eruption of, 202 Kunuk, Zacharias, 199, 200 Kuznets curve, 113 L Large Hadron Collider, 93 Lavoisier, Antoine, 78 Elements of Chemistry, 208–9 Lawson, Robert, 175–6 LD4, 104, 105 Leave Campaign, 194 Leibniz, Gottfried Wilhelm, 78 Levy, David, 158, 159 Lewis, Michael Flash Boys, 111–2 LifeSphere, 125 literacy in systems, 3–4 Lockheed Ocean Systems, 163 Logan, Walt (pseudonym), 165 Lombroso, Cesare, 140 London Stock Exchange, 110–1 Lovecraft, H.P., 11, 249 ‘low-hanging fruit,’ 93–4 M Macedonia, 233–4 machine learning algorithms, 222 machine thought, 146 machine translation, 147 magnetism, 77 Malaysian Airlines, 66 manganese noodles, 163–4 Manhattan Project, 24–30, 248 Mara, Jane Muthoni, 170 Mark I Perceptron, 136–8, 137 Maslow’s hierarchy of needs, 128–9 Matthews, James Tilly, 208–10, 209 Mauro, Ian, 199 McCarthy, Joe, 205 McGovern, Thomas, 57–8 McKay Brothers, 107, 110 memex, 24 Mercer, Robert, 236 Merkel, Angela, 174 metalanguage, 3, 5 middens, 56 migrated archive, 170–1 Minds, 150 miniaturisation principle, 81 Mirai, 129 mobile phones, 126 The Modern Prometheus (Shelley), 201 monoculture, 55–6 Moore, Gordon, 80, 80, 83 Moore’s law, 80–3, 92–4 Mordvintsev, Alexander, 154 Morgellons, 211, 214 Morrison, Grant The Invisibles, 196–7 Morton, Timothy, 73, 194 Mount Tambora, eruption of, 201 Moynihan, Daniel Patrick, 169 Munch, Edvard The Scream, 202 Mutua, Ndiku, 170 N NarusInsight, 177 NASA Ames Advanced Concepts Flight Simulator, 42 Natanz Nuclear Facility, 129 National Centre for Atmospheric Science, 68–9 National Geospatial-Intelligence Agency, 243 National Health Service (NHS), 110 National Mining Association, 64 National Reconnaissance Office, 168, 243 National Security Agency (NSA), 167, 174, 177–8, 183, 242–3, 249–50 National Security Strategy, 59 natural gas, 48 neoliberalism, 138–9 network, 5, 9 networks, 249 Newton, Isaac, 78 NewYorkTimesPolitics.com, 221 New York World’s Fair, 30–1 NHS (National Health Service), 110 9/11 terrorist attacks, 203–4, 206 ‘Nine Eyes,’ 174 1984 (Orwell), 242 NORAD (North American Air Defense Command), 33 North American Air Defense Command (NORAD), 33 ‘The Nor’ project, 104 Not Aviation, 190–1 NSA (National Security Agency), 167, 174, 177–8, 183, 242–3, 249–50 nuclear fusion, 97–8, 100 nuclear warfare, 28 Numerical Prediction (Richardson), 45 Nyingi, Wambugu Wa, 170 Nzili, Paulo Muoka, 170 O Obama, Barack, 180, 206, 231 Official Secrets Act, 189 Omori, Fusakichi, 145 Omori’s Law, 145 Operation Castle, 97 Operation Legacy, 171–2 Optic Nerve programme, 174 Optometrist Algorithm, 99–101, 160 O’Reilly, James, 185–6 Orwell, George 1984, 242 ‘Outline of Weather Proposal’ (Zworykin), 25–6 P Paglen, Trevor, 144 ‘paranoid style,’ 205–6 Patriot Act, 178 Penrose, Roger, 20 Perceptron, 136–8, 137 permafrost, 47–9, 56–7 p-hacking, 89–91 Phillippi, Harriet Ann, 165 photophone, 19–20 Pichai, Sundar, 139 Piketty, Thomas Capital in the Twenty-First Century, 112 Pincher, Chapman, 175–6 Pitt, William, 208 Plague-Cloud, 195, 202 Poitras, Laura, 175 Polaroid, 143 ‘predictive policing’ systems, 144–6 PredPol software, 144, 146 Priestley, Joseph, 78, 208, 209 prion diseases, 50, 50–1 PRISM operation, 173 product spam, 125–6 Project Echelon, 190 Prometheus, 132–4, 198 psychogeography, 103 public key cryptography, 167–8 pure language, 156 Putin, Vladimir, 235 Pynchon, Thomas Gravity’s Rainbow, 128 Q Qajaa, 56, 57 quality control failure of, 92–3 in science, 91 Quidsi, 113–4 R racial profiling, 143–4 racism, 143–4 ‘radiation cats,’ 251 raw computing, 82–3 Reagan, Ronald, 36–7 Reed, Harry, 29 refractive index of the atmosphere, 62 Regin malware, 175 replicability, 88–9 Reproducibility Project, 89 resistance, modes of, 120 Reuter, Paul, 107 Review Group on Intelligence and Communications Technologies, 181 Richardson, Lewis Fry, 20–1, 29, 68 Numerical Prediction, 45 Weather Prediction by Numerical Process, 21–3 Richardson number, 68 The Road to Serfdom (Hayek), 139 Robinson, Kim Stanley Aurora, 128 robots, workers vs., 116 ‘Rogeting,’ 88 Romney, Mitt, 206–7 Rosenblatt, Frank, 137 Roy, Arundhati, 250 Royal Aircraft Establishment, 188–9 Ruskin, John, 17–20, 195, 202 Rwanda, 243, 244, 245 S Sabetta, 48 SABRE (Semi-Automated Business Research Environment), 35, 38 SAGE (Semi-Automatic Ground Environment), 33, 34, 35 Samsung, 127 Scheele, Carl Wilhelm, 78 Schmidt, Eric, 241–5 The Scream (Munch), 202 Sedol, Lee, 149, 157–8 seed banks, 52–6 Seed Vault, 55 seismic sensors, 48 self-excitation, 145 ‘semantic analyser,’ 177 Semi-Automated Business Research Environment (SABRE), 35, 38 Semi-Automatic Ground Environment (SAGE), 33, 34, 35 semiconductors, 82 The Sensory Order: An Inquiry into the Foundations of Theoretical Psychology (Hayek), 138–9 Shelley, Mary Frankenstein, 201 The Modern Prometheus, 201 SIGINT Seniors Europe, 174 simulation, conflating approximation with, 34–5 Singapore Exchange, 122–3 smart products, 127–8, 131 Smith, Robert Elliott, 152 smoking gun, 183–4, 186 Snowden, Edward, 173–5, 178 software about, 82–3 AlphaGo, 149, 156–8 Assistant, 152 AutoAwesome, 152 DeepFace, 140 Greyball programme, 119, 120 Hippo programme, 32 How-Old.net facial recognition programme, 141 Optic Nerve programme, 174 PredPol, 144, 146 Translate, 146 Solnit, Rebecca, 11–2 solutionism, 4 space telescopes, 168–9 speed of light, 107 Spread Networks, 107 SSEC (IBM Selective Sequence Electronic Calculator), 30, 30–2, 31, 146 Stapel, Diederik, 87–8 Stapledon, Olaf, 20 steam engines, 77 Stellar Wind, 176 Stewart, Elizabeth ‘Betsy,’ 30–1, 31 Steyerl, Hito, 126 stock exchanges, 108 ‘The Storm-Cloud of the Nineteenth Century’ lecture series, 17–9 Stratus homogenitus, 195–6 studios, 130 Stuxnet, 129–30 surveillance about, 243–4 complicity in, 185 computational excesses of, 180–1 devices for, 104 Svalbard archipelago, 51–2, 54 Svalbard Global Seed Vault, 52–3 Svalbard Treaty (1920), 52 Swiss National Bank, 123 Syed, Omar, 158–9 systemic literacy, 5–6 T Taimyr Peninsula, 47–8 Targeted Individuals, 210–1 The Task of the Translator (Benjamin), 147, 155–6 TCP (Transmission Control Protocol), 79 technology acceleration of, 2 complex, 2–3 opacity of, 119 Teletubbies, 217 television, children’s, 216–7 Tesco Clubcard, 245 thalidomide, 95 Thatcher, Margaret, 177 theory of evolution, 78 thermal power plants, 196 Three Guineas (Woolf), 12 Three Laws of Robotics (Asimov), 157 Tillmans, Wolfgang, 71 tools, 13–4 To Photograph the Details of a Dark Horse in Low Light exhibition, 143 totalitarianism, collectivism vs., 139 Toy Freaks, 225–6 transistors, 79, 80 Translate software, 146 translation algorithms, 84 Transmission Control Protocol (TCP), 79 Tri Alpha Energy, 98–101 Trinity test, 25 trolling, 231 Trump, Donald, 169–70, 194–5, 206, 207, 236 trust, science and, 91 trusted source, 220 Tuktoyaktuk Peninsula, 49 turbulence, 65–9 tyranny of techne, 132 U Uber, 117–9, 127 UberEats app, 120–1 unboxing videos, 216, 219 United Airlines, 66–7 Uniting and Strengthening America by Fulfilling Rights and Ending Eavesdropping, Dragnet-collection and Online Monitoring Act (USA FREEDOM Act), 178 USA FREEDOM Act (2015), 178 US Drug Efficacy Amendment (1962), 95 V van Helden, Albert, 102 Veles, objectification of, 235 Verizon, 173 VHF omnidirectional radio range (VOR) installations, 104 Vigilant Telecom, 110–1 Volkswagen, 119–20 von Neumann, John about, 25 ‘Can We Survive Technology?

The Runaway Species: How Human Creativity Remakes the World by David Eagleman, Anthony Brandt

active measures, Ada Lovelace, agricultural Revolution, Albert Einstein, Andrew Wiles, Apollo 13, Burning Man, cloud computing, computer age, creative destruction, crowdsourcing, Dava Sobel, deep learning, delayed gratification, Donald Trump, Douglas Hofstadter, en.wikipedia.org, Frank Gehry, Gene Kranz, Google Glasses, Great Leap Forward, haute couture, informal economy, interchangeable parts, Isaac Newton, James Dyson, John Harrison: Longitude, John Markoff, Large Hadron Collider, lone genius, longitudinal study, Menlo Park, microbiome, Netflix Prize, new economy, New Journalism, pets.com, pneumatic tube, QWERTY keyboard, Ray Kurzweil, reversible computing, Richard Feynman, risk tolerance, Scaled Composites, self-driving car, Simon Singh, skeuomorphism, Solyndra, SpaceShipOne, stem cell, Stephen Hawking, Steve Jobs, Stewart Brand, synthetic biology, TED Talk, the scientific method, Watson beat the top human players on Jeopardy!, wikimedia commons, X Prize

Thanks to conservation and digital storage, we have constructed for ourselves a vast, readily accessible warehouse of raw materials. There is more available to bend, break and blend. There is more history on hand to absorb, process and beautify. And that’s not all. The rules that govern the sharing of new ideas are changing. The Large Hadron Collider is an example of research that transcends local culture: although their countries were in conflict, scientists from India and Pakistan, Iran and Israel, Armenia and Azerbaijan all joined under a common banner for a higher purpose – the search for scientific truth. Hand in hand with these cultural changes, computers enhance and democratize creativity, giving us new ways to manipulate what has come before us, whether it’s photographs, symphonies, or written text.

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Wheeler Elementary School (Burlington) ref1 Hobbes, Thomas ref1 Hockney, David ref1 Hokusai, Katsushika ref1 Holoroom ref1 Holz, Karl ref1 Honda ref1 honeybees ref1, ref2, ref3 Honeywell ref1 horses ref1 Hot Bertaa tea kettle ref1 How Buildings Learn (Brand) ref1 Hughes, Robert ref1 human form bending ref1, ref2, ref3 blending ref1, ref2 mythical creatures ref1 human genome project ref1 humor ref1 Iberian sculpture ref1 IBM ref1, ref2, ref3 Icebag (Oldenburg) ref1 idea flings ref1 idea quotas ref1 IDEO ref1, ref2 Idriss, Ali Mohamed Younes ref1 Ihering, Hermann von ref1 image recognition ref1 image-labeling ref1 imagination ref1, ref2, ref3 “Imagine Mars” project ref1 Indian dance ref1 indigenous art ref1 Industrial Revolution ref1, ref2, ref3 information economy ref1 instant replay ref1 insulin ref1 intravenous (iv) drips ref1 inventions see design iPad ref1 iPhone ref1, ref2, ref3, ref4 iPod ref1, ref2, ref3, ref4 Isaiah (Michelangelo) ref1 iTunes ref1 Ive, Jonathan ref1, ref2, ref3 IXI music player ref1 Japanese Imperial court ref1 Japanese Noh drama ref1 The Japanese Footbridge (Monet) ref1 Jay Z. ref1 Jesus phone (iPhone) ref1, ref2, ref3, ref4 “Jewish science” ref1 jigsaw method ref1 Jobs, Steve ref1, ref2, ref3, ref4 Johns, Jasper ref1, ref2, ref3 Johnson, Ben ref1 Johnson, Lonni Sue ref1, ref2 Johnson, Steve ref1 JR (artist) ref1 The Judgment of Paris (Raimondi) ref1 K-12 campuses ref1 Kahlo, Frida ref1, ref2 Kandinsky, Wassily ref1, ref2 Kettering, Charles ref1, ref2 Keystone Cops ref1 Khine, Michelle ref1 Killian, Michael ref1 kin selection ref1 King Jr, Martin Luther ref1 King Lear (Shakespeare) ref1 King Tee ref1 kingfisher ref1 Kitty Hawk (airplane) ref1 knives ref1 Koestler, Arthur ref1 Kramer, Hilton ref1 Kramer, Kane ref1, ref2 Kranz, Gene ref1, ref2, ref3, ref4 Krzywy Domek (“Warped Building”) ref1 Ku Klux Klan ref1 “Kubla Khan” (Coleridge) ref1 Kulich, Max ref1 Laarman, Joris ref1 The “Lady Blunt” Stradivarius ref1 Land, Edwin ref1, ref2 landscaping ref1 office ref1 Zen Gardens ref1 language bending ref1 blending ref1 cinema ref1 coding ref1 cultural conditioning ref1 Google Translate ref1 universal ref1, ref2 Large Hadron Collider ref1 Las Meninas (Velázquez) ref1 Picasso variations ref1 lasers ref1, ref2, ref3 The Last Judgment (Michelangelo) ref1 Lauter Piano Company ref1 LCD televisions ref1 Le Bordel d’Avignon (Picasso) ref1 Le Déjeuner sur l’herbe (Manet) ref1, ref2, ref3 Le Déjeuner sur l’herbe (Picasso) ref1 The LEGO Movie (2014) ref1 Leguia, Luis ref1 Leigh, Simone ref1 Lenard, Philipp ref1 Lennon, John ref1 Lenormand, Louis-Sébastien ref1 Les Demoiselles d’Alabama (Colescott) ref1 Les Demoiselles d’Avignon (Picasso) ref1, ref2, ref3, ref4, ref5 “Let Me Ride” (song) ref1 “Letter from Birmingham Jail” (King) ref1 Levi ref1 Lewis, Randy ref1 Lichtenstein, Roy ref1, ref2 “Life is Art” festival ref1 Ligeti, Györgi ref1 light bulbs ref1 Light Warlpiri ref1 Lightning Sonata (Cicoria) ref1 lions ref1 lipids ref1 liquid crystal displays ref1 literature bending ref1, ref2 breaking ref1, ref2 education ref1, ref2 mining history ref1 proliferating options ref1 see also drama Loewy, Raymond ref1 Longitude prize ref1 Longwell, Charles ref1 Lost in Space (tv) ref1 Lou Ruvo Center for Brain Health (Gehry building) ref1 Louis C.K. ref1 Louvre ref1 Lovelace, Ada ref1 Lowes, John Livingston ref1 Lowe’s (US retailer) ref1 McCarthy, John ref1 McCartney, Paul ref1 MacWorld ref1 Maeda, John ref1 Malevich, Kazimir ref1 mami wata (mermaid) ref1 The Man in the High Castle (Dick) ref1 Manet, Edouard ref1, ref2, ref3 Manley, Tim ref1 manufacturing economy ref1 Marclay, Christian ref1 Marlborough Gallery ref1 The Marriage of Figaro (Beaumarchais) ref1 Martin, George ref1 Massachusetts Institute of Technology ref1 Maternity (Brandt) ref1 mathematical techniques ref1 Maugham, W.

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

But that seemed to make scientific results contingent on the circumstances of their observation. Surely the whole point of a scientific experiment is to provide knowledge that can be generalized beyond the particular conditions under which it was obtained? Otherwise, what’s the point? If I (and a team of thousands) smash two protons together in the Large Hadron Collider at CERN and I see a new particle, I want to be able to conclude more than that I have discovered a new particle that appears when the LHC smashes protons together (and which I’d otherwise be obliged to call something like the ‘LHC-smashon’). I want to be able to assume that the new particle is a feature of nature, not of the specific experiment that made it.

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The particles with half-integer spin, meanwhile, are called fermions, and they are what make up everyday matter: electrons, protons, neutrons (those latter two are composites of fermions called quarks) and others. So spin divides fundamental particles into two groups. Why this should be so, no one knows. But many physicists hope that, as we probe beyond the Standard Model of particle physics using instruments such as the Large Hadron Collider at the CERN particle-physics centre in Geneva, we will discover an underlying relationship between bosons and fermions, perhaps via a new principle of physics called supersymmetry. When I say spin is quantized, I mean that a measurement of the magnetic moment it induces can only ever deliver one value of its magnitude, in two possible orientations.

Framers: Human Advantage in an Age of Technology and Turmoil by Kenneth Cukier, Viktor Mayer-Schönberger, Francis de Véricourt

Albert Einstein, Andrew Wiles, Apollo 11, autonomous vehicles, Ben Bernanke: helicopter money, Berlin Wall, bitcoin, Black Lives Matter, blockchain, Blue Ocean Strategy, circular economy, Claude Shannon: information theory, cognitive dissonance, cognitive load, contact tracing, coronavirus, correlation does not imply causation, COVID-19, credit crunch, CRISPR, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, deep learning, DeepMind, defund the police, Demis Hassabis, discovery of DNA, Donald Trump, double helix, Douglas Hofstadter, Elon Musk, en.wikipedia.org, fake news, fiat currency, framing effect, Francis Fukuyama: the end of history, Frank Gehry, game design, George Floyd, George Gilder, global pandemic, global village, Gödel, Escher, Bach, Higgs boson, Ignaz Semmelweis: hand washing, informal economy, Isaac Newton, Jaron Lanier, Jeff Bezos, job-hopping, knowledge economy, Large Hadron Collider, lockdown, Louis Pasteur, Mark Zuckerberg, Mercator projection, meta-analysis, microaggression, Mustafa Suleyman, Neil Armstrong, nudge unit, OpenAI, packet switching, pattern recognition, Peter Thiel, public intellectual, quantitative easing, Ray Kurzweil, Richard Florida, Schrödinger's Cat, scientific management, self-driving car, Silicon Valley, Steve Jobs, Steven Pinker, TED Talk, The Structural Transformation of the Public Sphere, Thomas Kuhn: the structure of scientific revolutions, TikTok, Tim Cook: Apple, too big to fail, transaction costs, Tyler Cowen

When astronomers pointed their telescopes to Neptune’s presumed position, they found it—exactly as predicted by the mental model. Or take the Higgs boson, a tiny elementary particle. In the 1960s physicists using the frames of quantum and particle physics predicted its existence. But it took fifty years and the Large Hadron Collider, which cost $10 billion to build, to gather sufficient data and prove them right. Thanks to their frame, they foresaw what they would discover. And in 2020, scientists were able to apply Einstein’s frame of relativity to predict the “dance” of one black hole around another, billions of light-years away heating matter equivalent to a trillion suns almost hour by hour.

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On the New York Times’s retraction of its 1920 article: Bjorn Carey, “New York Times to NASA: You’re Right, Rockets DO Work in Space,” Popular Science, July 20, 2009, https://www.popsci.com/military-aviation-amp-space/article/2009-07/new-york-times-nasa-youre-right-rockets-do-work-space/. On the Higgs boson: Sabine Hossenfelder, “The Uncertain Future of Particle Physics,” New York Times, January 23, 2019, https://www.nytimes.com/2019/01/23/opinion/particle-physics-large-hadron-collider.html. On black holes, see: Jonathan Amos, “Dancing Gargantuan Black Holes Perform on Cue,” BBC News, April 29, 2020, https://www.bbc.com/news/science-environment-52464250. On Blue Ocean Strategy: W. Chan Kim and Renée Mauborgne, Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant, expanded ed.

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

So far, physicists have been able to create antielectrons and antiprotons, as well as antihydrogen atoms, with antielectrons circulating around antiprotons. This was done at CERN and also at the Fermi National Accelerator Laboratory (Fermilab), outside Chicago, in its Tevatron, the second-largest atom smasher, or particle accelerator, in the world (second only to the Large Hadron Collider at CERN). Physicists at both labs slammed a beam of high-energy particles at a target, creating a shower of debris that contained antiprotons. Powerful magnets were used to separate the antimatter from ordinary matter. These antiprotons were then slowed down and antielectrons were allowed to mix with them, creating antihydrogen atoms.

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(This is how we research scientists interact with one another, by going to the blackboard or taking out a sheet of paper to solve a problem by writing down the equations.) We wrote down the equations for the Lorentz force, which Peck uses to accelerate his chips around Jupiter, but then we reduced the chips to the size of molecules and placed them into a hypothetical accelerator similar to the Large Hadron Collider at CERN. We could quickly see that the equations allowed for such a nanostarship to accelerate to nearly the speed of light, using only a conventional atom smasher based on the moon. Because we were reducing the size of our starship from a chip to a molecule, we could reduce the size of our accelerator from the size of Jupiter to a conventional atom smasher.

…

By the time a civilization has reached Type III status, its people have enough energy resources to probe the “Planck energy,” or 1019 billion electron volts, the energy at which space-time itself become unstable. (The Planck energy is a quadrillion times larger than the energy produced by our largest atom smasher, the Large Hadron Collider outside Geneva. It is the energy at which Einstein’s theory of gravity finally breaks down. At this energy, it is theorized that the fabric of space-time will finally tear, creating tiny portals that might lead to other universes, or other points in space-time.) Harnessing such vast energy would require colossal machines on an unimaginable scale, but if successful they might make possible shortcuts through the fabric of space and time, either by compressing space or by passing through wormholes.

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

None of the purely theoretical approaches was able to uncover the secret, which finally revealed itself through the probing of the experimenters, not the pencil-chewing of the theoreticians. Unlike previous collective scientific breakthroughs, such as the Manhattan Project, or subsequent ones, such as the landing of men on the Moon, the Large Hadron Collider or the Human Genome Project, there was no concerted organisation of the research. Institutions such as the Medical Research Council in the UK, the NIH in the US, and the Institut Pasteur and the Centre national de la recherche scientifique (CNRS) in France all supported key researchers, but the work had not been coordinated; there had been no committee or council that oversaw the project.

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In 2013, Ewan Birney’s group in Cambridge announced that they had written 739 kilobytes of computer data into DNA, using a code made out of groups of nucleotides.12 They synthesised DNA containing this encoded information, sequenced it and reconstructed the original files – these included a text file containing all of Shakespeare’s sonnets, a PDF version of Watson and Crick’s description of the double helix, an MP3 extract of Martin Luther King’s ‘I have a dream’ speech, and a JPEG image of the team’s laboratory. There was not a single error, and all the files were functional. The idea behind this proof of principle was to find a method that could guarantee future data storage in systems where huge amounts of data are being produced, such as at CERN, where the amount of data from the Large Hadron Collider and other experiments currently stands at more than 80 petabytes (1 petabyte (PB) = 1,000,000,000,000,000 bytes, or 1015 bytes) and is growing by at least 15 PB per year. At the moment, these data are stored on magnetic tape; DNA storage would be ideal for archiving data that rarely need to be accessed, in particular with the inevitable future decline in costs for reading and encoding DNA.

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Evelyn 29 hydrogen bomb 86 hydrogen bonding between DNA bases 58, 92, 101, 106 hydrophobicity and codon structure 292 hydrothermal vents 287 I Illumina Inc. 236 immune response codon variants 225 Neanderthal genes and 241 to pneumococci 35 RNA incorporation idea 140 inducible enzymes 153–7 information absent from Schrödinger’s views 19 bits as units 27, 144 communication as variable information 25 content of living things and genomes 84–5, 148, 298 Crick and Burnet on possible transfers 135, 138–40 entropy and 27–8, 30, 75, 151 evolutionary, from protein comparisons 140–1 ‘genetical information’ carried by DNA bases 111, 132 human conversation example 144–5 as metaphor 112, 147–9, 159, 203, 298, 300 in molecules other than DNA 275 nongenetic transmission 255 philosophers on the nature of 144, 149, 202–3, 297–303 role in biology 30, 73, 82–7, 119, 299–300 role in biology questioned 142, 144, 149 Shannon’s definition of 78, 82, 144, 147 information flow central dogma concern 262–3, 265, 306 in enzyme induction 307 protein → DNA disallowed 136, 138, 251–2, 265–6 protein → protein 253 in protein synthesis 168–9, 251 ‘Information in Contemporary Science’ colloquium 202, 205 information storage potential of DNA 271–2 information theory influence on molecular genetics 307 Oak Ridge symposium 142–6, 148–9 Royal Society conference 81 Royaumont colloquium 202–3, 205 Information Theory in Biology symposium 84 Information Theory in Health Physics and Radiobiology Symposium 142–9 Informational Macromolecules symposium, 1962 204–5 Ingram, Vernon 125–8, 132, 165 inheritance of acquired characteristics 138, 260 fundamental question of 1 insects as crustacea 239 intelligence, genetic effects 305 5th International Congress of Biochemistry, Moscow, 1961 183, 185–8, 190–2 International Human Genome Sequencing Consortium 232–3 intraspecific variation 236 introns and code universality 226 coinage of the term 222 evolution 222–3 human genome project 232, 238 preventing back translation 301 iso-G and iso-C 278 isochores 296 isotopic labelling 67, 163–4 J Jackson, David 279 Jacob, François ideas on genetic regulation 168–71, 256–7 meeting with Crick and Brenner 165–6 meeting with Monod 155 meeting with Szilárd 152 on messenger RNA 178 on natural selection 215 on ‘night science’ 171, 218 and Nirenberg 175, 185–6, 189 Nobel Prize 215 operon model 169–71, 243, 306 PaJaMo studies 155–6, 158, 160, 166, 178 report of Crick’s protein synthesis lecture 130 repressor action on DNA 158–9, 257 at the Royaumont colloquium 203 see also Monod Jeffreys, Alec 230 Joad, Professor Cyril 83 Johannsen, Wilhelm 3 Johns Hopkins University symposium, ‘The Chemical Basis of Heredity,’ 1956 161–3 Jones, Bill 192 Journal of Molecular Biology 160, 167, 185 Joyce, Gerald 275 Joyce, James 268 Jukes, Thomas 201, 226 ‘junk DNA’ 247–9, 299 K Kalmus, Hans 86–7 κ and Π base pairs 278 Kawaoka, Yoshihiro 280 Kay, Lily 88, 180, 181f, 185n keratin 84, 94–5, 105 Khorana, Gorind 208–9, 212, 214 Kilburn, Tom 74 Kimura, Mitoo 148 King, Martin Luther 272 King’s College, London 89–90, 92–5, 98–9, 101–8, 165 Kolmogoroff, Andrei 77 Koltsov, Nikolai 6–7, 12, 15, 17 L lactose, and enzyme induction 152–3, 156, 243 Lamarck, Jean-Baptiste 72, 138, 260–1 Landy, Art 187–8 Lane, Nick 287 Large Hadron Collider 272 Lazarsfeld, Paul 29 Leder, Phil 209 Lederberg, Joshua correspondence with von Neumann 146 enthusiasm for nucleic acids 58–9, 63 Nobel Prize 51, 215 Quastler’s symposium and 84 rejects Nirenberg 175 views on terminology 87, 161, 244 Lengyel, Peter 190–1, 203 Leopold, Urs 87 leucine, alternative codons 294–5 Levene, Phoebus, tetranucleotide hypothesis 7, 42–3, 51, 54, 62, 90 life, alien forms 275 life, origins of 286–9 Life Itself by Francis Crick 287 Linschitz, Henry 85 Lipmann, Fritz 189 Lockyer, Becky 255 Lu, Timothy 272 LUCA (Last Universal Common Ancestor) 227, 290, 293 Luria, Salvador 8, 34, 65–6, 97, 215 Luzzati, Vittorio 116 Lwoff, André 59–60, 155, 202, 215 Lysenko, Trofim Denisovich 260–1 lysine, genetic code for 190 lysozyme 125 M M-9 predictor 24 Maas, Werner 157 MacLeod, Colin 38–41 Macy conference 29 ‘ the magic twenty’ 117, 179 The Major Transitions in Evolution (book) 299 mammals base pair frequencies 295 discovery of ‘split genes’ in 221 genomic imprinting 248 origin of the placenta 245 Manchester 9, 26, 74, 162, 289 Mandelbrot, Benoit 203 Manhattan Project see atomic bomb Manton, Irene 17 Margulis, Lynn 224 Mars, terraforming 279 Martians 268–9 Martin, Bill 287 Martin, Bob 192 ‘maternal effects’ 258 mathematics approaches to the genetic code 115–16, 143, 174–5, 201, 214–15, 301–2 of next-generation sequencing 235 Patterson function 92, 103, 106 readers’ tolerance of equations 73–4 of Schrödinger’s code-script 14 Mathematical problems in the biological sciences symposium 175 Matthaei, Heinrich Cold Spring Harbor 1966 Symposium 214 collaboration with Nirenberg 173–5, 177–87 competitors 189–91 Crick’s reaction to 193–6 genetic code success 174, 181–2 not awarded the Nobel Prize 215 Maxwell’s Demon (James Clerk Maxwell) 27, 30, 76 May, Lord (Robert May) 281 Maynard Smith, John 299–300 Mazia, Daniel 61–2 McCarty, Maclyn 41, 43, 46–7, 49, 55, 62, 66, 189n McClintock, Barbara 245 McCulloch, Warren 24, 82, 86, 149 Mead, Margaret 22, 24 meaning and information flow 78–9, 144 meiosis 12 Mello, Craig 283 Mendel, Gregor 2–3, 128 Meselson, Matthew 163–5, 167, 186–8 messages see communication; information theory messenger molecule, PaJaMo group 156, 165 messenger RNA (mRNA) cross-species transfer 271 discovery 166–7, 169 function 317 Nirenberg’s work with 178, 180, 184–5, 208 PaJaMo group and 166, 178 potential manipulation 284 pre-mRNA processing to 222 switch of code investigations to 198 untranslated regions 297 use of possible codons 208, 211 metaphors information as 112, 147–9, 159, 203, 298, 300 risks associated with 313 methionine/start codon 213 methylation of cytosine 256–8 microsomal particles (ribosomes) 134 Miescher, Fritz 14–15 Miller, Stanley 286 Mirsky, Alfred E. 41–3, 55–9, 62, 64, 90–1 MIT (Massachusetts Institute of Technology) Broad Institute CRISPR patents 284 David Baltimore at 251 Elias at 147 Farzadfard and Lu at 272 Phillip Sharp at 223 Shannon at 25, 27 Wiener’s group at 21, 24–5 mitochondria maternal effects 258 and the origin of eukaryotes 239 mitochondrial DNA 224–5 mitosis 12 ‘Models in Biology’ symposium 147 models of DNA Astbury on 54 early attempts 99–100, 103 triple helix models 99–100, 104, 106 Watson and Crick’s final model 106–7, 107f molecular biology coinage of the term 21 Ed Tatum on development of 204 funding and coordination 217, 312 Journal of Molecular Biology 160, 167, 185 Molecular Biology of the Gene, by James Watson 140, 251 molecular geneticists 130, 267 molecular genetics Benzer’s role in creating 162 changes in the practice of 310 colinearity assumption 213 contribution of Jacob and Monod 170 Darwinian framework 220 influence of cybernetics and information theory 148, 298–9, 307–8 reverse transcriptase role 252 universality assumption 250 validity of the word ‘code’ 301 see also central dogma Monod, Jacques Chance and Necessity book 306 on cybernetics 407 ‘derepression of repression’ 257 on dogma 137 enzymatic adaptation/induction 152–3 Essays in Enzyme Cybernetics project 159 ideas on genetic regulation 168–71, 220, 226, 243 on negative feedback 153–4 PaJaMo studies 155–6, 158, 160, 166, 178 see also Jacob Morgan, Thomas Hunt 3–6, 9 Moscow, 5th International Congress of Biochemistry, 1961 183, 185–8, 190–2 mRNA see messenger RNA Mueller, Howard 51 Muller, Hermann on Avery’s work 50–1, 56 crystal-growth model 7, 15 inducing mutations with X-rays 5 Nobel Prize 33 reaction to What is life?

What We Cannot Know: Explorations at the Edge of Knowledge by Marcus Du Sautoy

Albert Michelson, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, banking crisis, bet made by Stephen Hawking and Kip Thorne, Black Swan, Brownian motion, clockwork universe, cosmic microwave background, cosmological constant, dark matter, Dmitri Mendeleev, Eddington experiment, Edmond Halley, Edward Lorenz: Chaos theory, Ernest Rutherford, Georg Cantor, Hans Lippershey, Harvard Computers: women astronomers, heat death of the universe, Henri Poincaré, Higgs boson, invention of the telescope, Isaac Newton, Johannes Kepler, Large Hadron Collider, Magellanic Cloud, mandelbrot fractal, MITM: man-in-the-middle, Murray Gell-Mann, music of the spheres, Necker cube, Paul Erdős, Pierre-Simon Laplace, quantum entanglement, Richard Feynman, seminal paper, Skype, Slavoj Žižek, stem cell, Stephen Hawking, technological singularity, Thales of Miletus, Turing test, wikimedia commons

They have revealed the amazing fact that three-quarters of the way into the lifetime of our universe the expansion of the universe started to accelerate. I remember reading as a kid that we were in for a big crunch, but now it seems that we have a completely different future waiting for us. The particle colliders like the Large Hadron Collider at CERN (the European Organization for Nuclear Research in Switzerland) have allowed us to penetrate the inner workings of matter itself, revealing new particles – like the top quark discovered in 1994 and the Higgs boson discovered in 2012 – that were bits of speculative mathematics when I was reading my New Scientist at school.

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The positively charged part of the atom, which was more massive than the negative electron, formed the pudding making up the bulk of the atom, while the electrons were the tiny fruit inside. Then the age of the bombardment of the atom began which would eventually lead to the ultimate atom smasher: the Large Hadron Collider at CERN. The New Zealand-born British physicist Ernest Rutherford is generally credited with the discovery of the proton, the particle that was the building block for all these positive particles that Thomson had investigated. Rutherford became fascinated by the new subject of radioactivity.

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242–4; definitions of 412; desire to know 2; Gödel’s incompleteness theorem and 377, 383–8, 402–3, 413; humanities as best language for what it means to be human 419; justified true belief and 412–13; the know-it-all professorship 4–6; knowing when you can’t know 48–51; known unknowns 7–9; paradox of unknowability 413–14; science as narrative that only appears to describe reality 418; success rate of science and production of true knowledge 416; unknowability of ‘things in themselves’ 416, 418; what we cannot know 407–14, 418–20; what we don’t know 7–9; what we know 3–4; what we will never know 9–13 see also proof and under individual area of knowledge Koch, Christof 321–3, 324–5, 328, 347–51, 352, 353–5, 359–60 Kronecker, Leopold 398–9 Kurzwell, Ray 8; The Singularity is Near 281 Lakatos, Imre: Proofs and Refutations 415 Lamb, Willis 106 Lambda baryons 107, 119 Lambert, Johann Heinrich 85 language: consciousness and 305, 308, 310, 311, 315, 338–9, 352, 356–8; limits of knowledge and 408–9; linguistic competence and linguistic performance, distinction between 388; origin of 382; paradoxical/slippery nature of 364, 381, 384 Laplace, Pierre-Simon 34, 36, 64, 71, 72, 133, 156, 275; Philosophical Essay on Probabilities 34–5 Large Hadron Collider (LHC) at CERN 3–4, 98, 103, 115, 119, 120, 121, 124 Lascaux caves, France 20, 249–51 Laskar, Jacques 63 law of octaves 90 laws of motion, Newton’s 32–7, 67, 72, 87–8, 97 laws of nature, search for ultimate 9, 36, 238 Leavitt, Henrietta 202–3, 204 Leibniz, Gottfried 5, 71, 252, 253 Lemaître, Georges 215, 219, 235 Leonardo da Vinci 307 Leverrier, Urbain 196–7 light: aeon theory and 291; Big Bang and 220–1, 282; black holes and 275–6, 277, 282, 285, 288; cathode rays and 95–6; curvature of space and 275–6; Doppler effect and 214–15; electromagnetic force and 108; expanding universe and 214–16, 222, 224, 408; infinite universe and 207, 208–11, 220; measuring distance to planets and 216; measuring galaxies from 214–15; Newton’s theory of 88, 134; particle nature of 88, 134–49; red and blue wavelengths of 214–18, 220, 222, 224; special theory of relativity and 253–8, 259, 260–1, 262–3, 264, 268, 269–72, 281–2; speed of 72, 105, 176, 198–200, 217, 224, 228, 253–8, 259, 260–1, 262–3, 264 268, 269–72, 275, 281–2, 291; star emission and analysis of 10, 202, 203, 204 see also photons Lightman, Alan: Einstein’s Dreams 273 Linde, Andrei 229 Lippershey, Hans 193 Lloyd, Seth: ‘Computational Capacity of the Universe’ 377 Lorenz, Edward 44–5, 46; ‘Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?’

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

A spaceship would require at least a few tons of this fuel to get up to the kind of speeds needed for any meaningful interstellar travel. And antimatter is not easy to make. It is perfectly possible. As is mentioned in Dan Brown’s book Angels & Demons, antimatter is produced at the same CERN laboratory in Europe as hosts the Large Hadron Collider, though in a totally different experiment (about the only “fact” in Brown’s book that is actually true). But production is slow. At the moment, the whole world’s annual production of antimatter is less than a millionth of a gram, so we aren’t going to be building antimatter spaceship filling stations any time soon.

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Moreau jumping stilts Jupiter Jurassic Park dinosaur portrayal in reality of Jurassic Park (Crichton) Kaas, Jon Kepler, Johannes Kline, Nathan S. Klingons (fictional characters) Knowledge Navigator Kornbluth, Cyril Kratzenstein, C. G. Kubrick, Stanley Kurzweil, Ray “The Land Ironclads” (Wells) Lang, Fritz Large Hadron Collider laser-light shows lasers. See also phaser common uses of development of holograms and military applications of mirrors in as phaser inspiration ship-based tractor beams with visibility of Le Guin, Ursula K. learning. See also sleep learning; virtual learning AI and mistakes in with memory transfer Leith, Emmett Lensman series (Smith) lenticular printing Levin, Ira LGM-1 A Life for the Stars (Blish) light.

The Alps: A Human History From Hannibal to Heidi and Beyond by Stephen O'Shea

car-free, clockwork universe, Edward Snowden, Isaac Newton, Johann Wolfgang von Goethe, Large Hadron Collider, plutocrats, Snapchat, trade route

Yet Geneva, the most boring interesting city on the Continent, the spot Fyodor Dostoyevsky dismissed as a “dull, gloomy, Protestant, stupid town,” midwife to the Calvinist Reformation, home to do-gooderism past and present—the League of Nations, the Red Cross, the United Nations High Commissioner for Refugees—Geneva must be where my journey begins. For it was along the shores of Lake Geneva that an aesthetic revolution occurred more than two centuries ago, a revolution in thought that altered how humanity viewed nature. And, more to our purpose, the mountains. What Geneva’s worldwide web and its Large Hadron Collider have done to reality, the bygone artists and thinkers and scientists of Lake Geneva did to taste, which is, arguably, reality’s stepsister. On the waterfront, a statue of a woman commands attention through the kinks of scorching air rising from the surrounding cobbles. The regal figure portrayed in bronze is angular, and pretty, although her Scottish creator, sculptor Philip Jackson, has her trying to hide her beauty behind a fan.

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See Hernstadt, Edward edelweiss, 82, 83, 255 Edelweissspitze (Bikers’ Point), 235 Eggishorn, 124–27 Eichmann, Adolf, 226, 270 Eiger ascent by Darbellay, 107, 166 climber deaths, 167–68, 169–70, 172 cog railways, 166, 172, 174–75 contest to climb, 168–69 Eigerwand station, 172–73 Eismeer (Ice Sea) station, 173 Hôtel Bellevue des Alpes, 168 Jungfraubahn, 172 Kleine Scheidegg (Little Watershed) pass, 167, 168, 169, 171 north face (Norwand), 45, 107, 167, 168, 257 rail tunnel, 168 The Eiger Sanction (movie), 174 Eigerwand station, 172–73 Eigruber, August, 227 Eisack Valley, 260 Eismeer (Ice Sea) station, 173 Eksteins, Modris, 191 Eleanor of Provence, 52 “Elegy Written in a Country Churchyard” (Gray), 73 Elisabeth of Austria (Sisi) (empress) about, 5, 220 and Bad Ischl, Austria, 216–18 Kaiservilla, 219, 220, 222 and King Ludwig II, 182, 218 marriage to Franz Josef, 216, 218 and Merano, Italy, 261 murder, 5, 6, 182, 216–17, 229–30 statue near Lake Geneva, 5–6, 34, 216 Ellis, Bret Easton, 42 Emile (Rousseau), 93–94 Les Enfants Terribles (Megève), 54 Engadine, 267–68, 270, 271 Enlightment, 8, 10, 242 Enola Gay controversy, 207 Ernst. see Herb, Ernst Escoffier, Auguste, 53 Espace Killy, 62 Espace Vertical, 43 Evian-les-Bains, 24 Fanes, 256 Farewell to Arms (Hemingway), 287 Fell, John Barraclough, 84 Fendant de Sion, 111, 113 Fénis, 96 Fern Pass, 180, 181 Fernstein Castle, 180 Fiat, 95 Fiesch, Switzerland, 124, 127–28 Filiberto, Emanuele, 59 “The Final Problem” (Conan Doyle), 161–62, 164–65 Finnegan’s Wake (Joyce), 111, 292 First on the Rope (Frison-Roche), 48–49 Flaubert, Gustave, 76 Die Fledermaus (Strauss), 215 Fleming, Ian, 229, 263 Fort Bard, 96–97, 108 Fortey, Richard, 66, 137–39, 141 For Your Eyes Only (movie), 256 Franche-Comté, 3–4 Frank, Anne, 270 Frank, Bernhard, 205 Frankenstein, or The Modern Prometheus (Mary Shelley), 20–21 Franz Ferdinand (archduke), 219, 291 Franz Josef (emperor) chamois hunting, 219, 221, 222 declaration of war in 1914, 220–21 Kaiservilla, 218–22 and Katharina Schratt, 218 marriage to Elisabeth of Austria (Sisi), 216, 218 Frederick Barbarossa (Holy Roman Emperor), 204, 259 Freud, Sigmund, 223 Friedrich, Caspar David, 92 Frison-Roche, Roger, 48 Friuli, Italy, 274–75, 279, 286, 287 Friulian language, 274, 279 Friuli-Venezia Giulia, Italy, 274 Furka Pass ascent, 128–30, 133 descent, 131–32 elevation, 131 Goldfinger (movie), 130 Mediterranean–North Sea watershed boundary, 133, 134 rösti ditch (Röstigraben), 134 Fusch, Austria, 234–39 Füssen, Germany, 181–82 Gailberg Saddle, 275, 277 Gailtaler Alps, 275 Gall, 147 Garibaldi, Giuseppe (Joseph Marie), 58 Garmisch-Partenkirchen, Germany, 55, 185–87, 189, 200–201 Gellert Grindelwald, 175 Geneva, Switzerland arrival in, 4 description, 4–5 Large Hadron Collider, 5 statue of Empress Elisabeth of Austria, 5–6, 34, 216 view of Lake Geneva, 6 see also Lake Geneva and surroundings Geneva Conventions, 79 gentian, 82–83 George of Liechtenstein (bishop-prince), 242–43, 245, 246 Gibbon, Edward, 12 Gibson, Mel, 242 Gletsch, Switzerland, 128–29 Gletscherstrasse (Road of the Glaciers), 237 Gmund, Germany, 193–94 Goebbels, Joseph, 187, 189 Goethe, Johann Wolfgang von, 7, 21 Goldfinger (movie), 130 Les Gorges du Pont-du-Diable (The Gorges of Devil’s Bridge), 25–26 Göring, Hermann, 201 Gotthard of Hildesheim, 134 Gotthard Pass ascent, 133–34 descent, 136 as gate for invading armies, 70 Museo Nazionale San Gottardo, 134–35 rösti ditch (Röstigraben), 133 Graian Alps, 97, 98 The Grand Budapest Hotel (movie), 129 Grand Combin, 108 Le Grand Dru, 48 Grande Motte glacier, 62 La grande peur dans la montagne (Terror on the Mountain) (Ramuz), 111–12 Grandes Jorasses, 45, 48, 167 Grand Tour, 7–8, 40, 72 Gran Paradiso Park, Italy, 97, 236 Graubünden, Switzerland (Grisons), 264–65 Gray, Thomas, 73 Great Alpine Road, 23, 25, 33 The Great Escape (movie), 182 Great St.

Calling Bullshit: The Art of Scepticism in a Data-Driven World by Jevin D. West, Carl T. Bergstrom

airport security, algorithmic bias, AlphaGo, Amazon Mechanical Turk, Andrew Wiles, Anthropocene, autism spectrum disorder, bitcoin, Charles Babbage, cloud computing, computer vision, content marketing, correlation coefficient, correlation does not imply causation, crowdsourcing, cryptocurrency, data science, deep learning, deepfake, delayed gratification, disinformation, Dmitri Mendeleev, Donald Trump, Elon Musk, epigenetics, Estimating the Reproducibility of Psychological Science, experimental economics, fake news, Ford Model T, Goodhart's law, Helicobacter pylori, Higgs boson, invention of the printing press, John Markoff, Large Hadron Collider, longitudinal study, Lyft, machine translation, meta-analysis, new economy, nowcasting, opioid epidemic / opioid crisis, p-value, Pluto: dwarf planet, publication bias, RAND corporation, randomized controlled trial, replication crisis, ride hailing / ride sharing, Ronald Reagan, selection bias, self-driving car, Silicon Valley, Silicon Valley startup, social graph, Socratic dialogue, Stanford marshmallow experiment, statistical model, stem cell, superintelligent machines, systematic bias, tech bro, TED Talk, the long tail, the scientific method, theory of mind, Tim Cook: Apple, twin studies, Uber and Lyft, Uber for X, uber lyft, When a measure becomes a target

For example, in 2012 scientists using the Large Hadron Collider in Geneva reported exciting results that supported the existence of the Higgs boson, an elementary particle that had long been predicted but never observed directly. Reporting on the story, National Geographic wrote that scientists “are more than 99 percent certain they’ve discovered the Higgs boson, aka the God particle—or at least a brand-new particle exactly where they expected the Higgs to be.” What National Geographic should have reported is that the p-value for the experiment was 0.01. The results obtained with the Large Hadron Collider would have had a 1 percent probability of appearing by chance even if there had been such a thing as a Higgs boson.

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!

Its organizers plan on setting up a massive radio telescope made up of more than half a million antennas spread out across vast swaths of Australia and southern Africa. When it’s completed in 2024 or so, astronomers will be able to analyze the data to better comprehend the history of the universe and the nature of matter. The SKA is a scientific sibling to the Large Hadron Collider in Switzerland. There, scientists are studying the tiniest elemental particles for answers to some of the fundamental riddles of existence. In contrast, “Our laboratory is the whole universe,” says Marco de Vos, managing director of ASTRON, the Netherlands Institute for Radio Astronomy, which, along with IBM, is proposing an information-technology system to manage the SKA’s data.11 The SKA is an iconic example of the need in the coming era for what we call radical collaboration.

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

It took until the 1980s, decades after the pioneering work, for people to realize that including even one or two hidden layers could vastly enhance the capabilities of their neural networks. Nowadays such multilayer networks are used, for example, to distill patterns from the explosions of particles that emerge from high-energy collisions at the Large Hadron Collider. They do it much faster and more reliably than humans possibly could. David Hubel and Torsten Wiesel were awarded a 1981 Nobel Prize for figuring out what neurons in the visual cortex are doing. They showed that successive hidden layers first extract features likely to be meaningful in visual scenes (for example, sharp changes in brightness or color, indicating the boundaries of objects) and then assemble them into meaningful wholes (the underlying objects).

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., 167–69 Krause, Kai, 324–27 Krauss, Lawrence, 53–54 Krebs, Hans, 170 Krebs cycle, 170 Krieger, Nancy, 59 Kuhn, Thomas, 242 Kuo, Zing-Yang, 63 Kurzban, Rob, 124–26 Kutcher, Stan, 251 labeling and naming, 62–64, 190–91 Lamarck, Jean-Baptiste, 88 language, 154, 155–56, 158, 257, 395 path dependence and, 286–88 thinking and, 242 see also words Lanier, Jaron, 177–79 Laplace, Pierre-Simon, 9 Large Hadron Collider, 189 large numbers, law of, 107, 122 lateral inhibition, 130 law, 260 learning, 154, 160 instinct for, 154–56 Lehrer, Jonah, 46–48 Leibniz, Gottfried Wilhelm, 109 Leonardo da Vinci, 34 Levin, Harry, 31 liberal hyperrationality, 347 life, 157, 158, 172, 291 diversity of, 359 on Earth, 3–5, 10, 15 holism and, 81 intelligent, 4, 5 in universe, 3–5, 13–14, 292 life code, 165–66 linearity, 184–85 Lisi, Garrett, 68–71 Listing, Johann Benedict, 109 literacy, 259 risk, 259–61 “Little Gidding” (T.

Lonely Planet Switzerland by Lonely Planet

"World Economic Forum" Davos, Albert Einstein, bike sharing, car-free, carbon footprint, Eyjafjallajökull, Frank Gehry, G4S, Guggenheim Bilbao, Higgs boson, Kickstarter, Large Hadron Collider, low cost airline, messenger bag, Nelson Mandela, New Urbanism, offshore financial centre, smart cities, starchitect, trade route

oCERNRESEARCH CENTRE ( GOOGLE MAP ; %022 767 84 84; www.cern.ch; Meyrin; hguided tours in English 11am & 1pm Mon-Sat)F Founded in 1954, the European Organisation for Nuclear Research, 8km west of Geneva, is a laboratory for research into particle physics. It accelerates protons down a 27km circular tube (the Large Hadron Collider, the world's biggest machine) and the resulting collisions create new matter. Come anytime to see the permanent exhibitions shedding light on its work, but for two-hour guided tours in English reserve online up to 15 days ahead and bring photo ID. Tours often fill up months ahead – access the online booking portal here: http://visit.cern/tours/guided-tours-individuals.

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In 1523, the city adopts his reform proposals. 1590–1600 Some 300 women in Vaud are captured, tortured and burned alive on charges of witchcraft, even as Protestants in other Swiss cantons strive to end witch hunts. 1847 ‘Hare shoot’ civil war between Protestants and Catholics lasts just 26 days, leaving 86 dead and 500 wounded, and paving the way for the 1848 federal constitution. 1863 After witnessing slaughter and untended wounded at the Battle of Solferino in 1859 in northern Italy, businessman and pacifist Henri Dunant co-founds the International Red Cross in Geneva. 1918 With a sixth of the population living below the poverty line and 20,000 dead of a flu epidemic, workers strike; the 48-hour week is among the long-term results. 1940 General Guisan’s army warns off WWII invaders; 430,000 troops are placed on borders but most are put in Alpine fortresses to carry out partisan war in case of German invasion. 1979 Five years after a first vote in favour in 1974, the Jura (majority French-speaking Catholics), absorbed by Bern in 1815, leaves Bern (German-speaking Protestants), becoming an independent canton. 1990 The internet is ‘born’ at Geneva’s CERN, where Tim Berners-Lee develops HTML, the language used to prepare pages for the World Wide Web and link text to graphics. 2001 National airline Swissair collapses, a gun massacre in Zug parliament kills 14 politicians, 21 people perish in a canyoning accident and 11 die in a fire in the St Gotthard Tunnel. 2008 The world financial crisis affects Switzerland’s two biggest banks, UBS and Credit Suisse. The government bails out UBS with a US$60-billion package, while Credit Suisse seeks funds elsewhere. 2009 The first experiments in the world’s largest particle accelerator are successfully conducted with the Large Hadron Collider at CERN, the European Centre for Nuclear Research in Geneva. 2011 A soaring, over-valued Swiss franc prompts the Swiss National Bank to peg it to the euro. 2014 A popular initiative to set immigration quotas is successful at the Swiss polls. 2016 Solar Impulse 2, the solar plane of Lausanne adventurer Bertrand Piccard, successfully completes its fuel-free 40,000km circumnavigation of the globe. 2016 The Gotthard Base Tunnel, the world's longest at 57km, opens for operation in December, speeding up connections between the Alps and Italy. 2017 The Swiss vote in favour of phasing out nuclear energy and switching to renewables.

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The genius behind the global information-sharing tool was Oxford graduate Tim Berners-Lee, a software consultant for CERN who started out creating a program for the research centre to help its hundreds of scientists share their experiments, data and discoveries. Two years on it had become a dramatically larger and more powerful beast than anyone could have imagined. Equally dramatic, large and powerful is CERN’s Large Hadron Collider, where Geneva scientists play God with Big Bang experiments. A guided tour of the world’s biggest physics experiment, quietly conducted in a Geneva suburb, is phenomenal. Other great Swiss science forays include the ground-breaking glacial research carried out by courageous 19th-century scientists on the extraordinary 23km-long Aletsch Glacier in the Upper Valais, and a chemist in Basel called Albert Hofmann inadvertently embarking on the world’s first acid trip – ingesting lysergic acid diethylamide (LSD) – in 1943.

Geek Wisdom by Stephen H. Segal

Ada Lovelace, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Apollo 13, battle of ideas, biofilm, Charles Babbage, fear of failure, Henri Poincaré, Jacquard loom, Large Hadron Collider, lolcat, Mark Zuckerberg, mutually assured destruction, Neal Stephenson, nuclear paranoia, Saturday Night Live, Snow Crash, Vernor Vinge, W. E. B. Du Bois

Early nuclear weapons testing, which irradiated locations like Bikini Atoll and afflicted the inhabitants with death, miscarriages, and deformities. Early pseudosciences like phrenology and eugenics, which did more to advance bigotry than understanding. Science is a tool like any other, and it can be subverted to serve even the basest human aims. The Large Hadron Collider, however, was not one of these perversions. Much of the concern over its activation was the result of media sensationalism and wild speculation by amateurs: Could it create a black hole that will consume the entire planet??? Well … no. And though many knowledgeable geeks found it hilarious, the public’s reaction was both predictable and preventable, given science’s history of keeping horrors on the down-low.

A Short History of Nearly Everything by Bill Bryson

Albert Einstein, Albert Michelson, Alfred Russel Wallace, All science is either physics or stamp collecting, Apollo 11, Arthur Eddington, Barry Marshall: ulcers, Brownian motion, California gold rush, Cepheid variable, clean water, Copley Medal, cosmological constant, dark matter, Dava Sobel, David Attenborough, double helix, Drosophila, Eddington experiment, Edmond Halley, Ernest Rutherford, Fellow of the Royal Society, flying shuttle, Gregor Mendel, Harvard Computers: women astronomers, Helicobacter pylori, Higgs boson, Isaac Newton, it's over 9,000, James Watt: steam engine, John Harrison: Longitude, Kevin Kelly, Kuiper Belt, Large Hadron Collider, Louis Pasteur, luminiferous ether, Magellanic Cloud, Menlo Park, Murray Gell-Mann, out of africa, Richard Feynman, Stephen Hawking, supervolcano, Thomas Malthus, Wilhelm Olbers

“Young man,” Enrico Fermi replied when a student asked him the name of a particular particle, “if I could remember the names of these particles, I would have been a botanist.” Today accelerators have names that sound like something Flash Gordon would use in battle: the Super Proton Synchrotron, the Large Electron-Positron Collider, the Large Hadron Collider, the Relativistic Heavy Ion Collider. Using huge amounts of energy (some operate only at night so that people in neighboring towns don't have to witness their lights fading when the apparatus is fired up), they can whip particles into such a state of liveliness that a single electron can do forty-seven thousand laps around a four-mile tunnel in a second.

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Breaking up atomic nuclei, however, requires quite a lot of money and a generous supply of electricity. Getting down to the level of quarks—the particles that make up particles—requires still more: trillions of volts of electricity and the budget of a small Central American nation. CERN's new Large Hadron Collider, scheduled to begin operations in 2005, will achieve fourteen trillion volts of energy and cost something over $1.5 billion to construct.*25 But these numbers are as nothing compared with what could have been achieved by, and spent upon, the vast and now unfortunately never-to-be Superconducting Supercollider, which began being constructed near Waxahachie, Texas, in the 1980s, before experiencing a supercollision of its own with the United States Congress.

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Guth, p. 121. 5 “In 1998, Japanese observers reported . . .” Economist, “Heavy Stuff,” June 13, 1998, p. 82; and National Geographic, “Unveiling the Universe, October 1999, p. 36. 6 “Breaking up atoms . . .” Trefil, 101 Things You Don't Know About Science and No One Else Does Either, p. 48. 7 “CERN's new Large Hadron Collider . . .” Economist, “Cause for ConCERN,” October 28, 2000, p. 75. 8 “dotted along the circumference . . .” Letter from Jeff Guinn. 9 “A proposed neutrino observatory at the old Homestake Mine . . .” Science, “U.S. Researchers Go for Scientific Gold Mine,” June 15, 2001, p. 1979. 10 “A particle accelerator at Fermilab in Illinois . . .”

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

But various calculations that physicists have performed indicate that the partner particles corresponding to the particles we observe ought to be a thousand times as massive as a proton, if not even heavier. That is too heavy for such particles to have been seen in any experiments to date, but there is hope that such particles will eventually be created in the Large Hadron Collider in Geneva. The idea of supersymmetry was the key to the creation of supergravity, but the concept had actually originated years earlier with theorists studying a fledgling theory called string theory. According to string theory, particles are not points, but patterns of vibration that have length but no height or width—like infinitely thin pieces of string.

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

As Feynman once observed, that’s like calculating the distance from Los Angeles to New York to within a hairbreadth. The standard model was hammered out by the mid-1970s and has not had to be seriously revised since. (A crowning confirmation came in 2012 when the Higgs boson, the last missing piece, was discovered thanks to the Large Hadron Collider at CERN, the European center for experimental physics.) The standard model tells how nature behaves on the scale of molecules, atoms, electrons, and on down, where the force of gravity is weak enough to be overlooked. General relativity tells how nature behaves on the scale of apples, planets, galaxies, and on up, where quantum uncertainties average out and can be ignored.

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Klein, Felix Kluge (Marcus) Kol’man, Ernst Kolmogorov, Andrei Krauss, Lawrence Kripke, Saul Kronecker, Leopold Kruger, Justin “Kubla Khan” (Coleridge) Kuhn, Thomas Kun, Béla Laforgue, Jules Lagrange, Joseph-Louis Lakatos, Imre Lambertz, Ghislaine Langlands program language, philosophy of Language and Time (Smith) Laplace, Pierre-Simon Large Hadron Collider Laski, Harold laughter law of eponymy least action, law of least time, principle of Leavitt, David Lebensborn Lebesgue, Henri Lebowitz, Fran Leeuwenhoek, Antonie van Leibniz, Gottfried Leigh, Augusta Lenin, Vladimir Lesch-Nyhan syndrome Leslie, John Let’s Make a Deal (TV game show) Letterman, David Lévi-Strauss, Claude Lewis, C.

What We Owe the Future: A Million-Year View by William MacAskill

Ada Lovelace, agricultural Revolution, Albert Einstein, Alignment Problem, AlphaGo, artificial general intelligence, Bartolomé de las Casas, Bletchley Park, British Empire, Brownian motion, carbon footprint, carbon tax, charter city, clean tech, coronavirus, COVID-19, cuban missile crisis, decarbonisation, deep learning, DeepMind, Deng Xiaoping, different worldview, effective altruism, endogenous growth, European colonialism, experimental subject, feminist movement, framing effect, friendly AI, global pandemic, GPT-3, hedonic treadmill, Higgs boson, income inequality, income per capita, Indoor air pollution, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, Islamic Golden Age, iterative process, Jeff Bezos, job satisfaction, lab leak, Lao Tzu, Large Hadron Collider, life extension, lockdown, long peace, low skilled workers, machine translation, Mars Rover, negative emissions, Nick Bostrom, nuclear winter, OpenAI, Peter Singer: altruism, Peter Thiel, QWERTY keyboard, Robert Gordon, Rutger Bregman, Sam Altman, seminal paper, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, special economic zone, speech recognition, Stanislav Petrov, stem cell, Steven Pinker, strong AI, synthetic biology, total factor productivity, transatlantic slave trade, Tyler Cowen, William MacAskill, women in the workforce, working-age population, World Values Survey, Y Combinator

In 1905, his “miracle year,” Albert Einstein revolutionized physics, describing the photoelectric effect, Brownian motion, the theory of special relativity, and his famous equation, E=mc2. He was twenty-six at the time and did all this while working as a patent clerk. Compared to Einstein’s day, progress in physics is now much harder to achieve. The Large Hadron Collider cost about $5 billion, and thousands of people were involved in its design, construction, and operation.21 It enabled us to discover the Higgs boson—a worthy discovery for sure, but a small and incremental one compared to Einstein’s contributions.22 In a recent article called “Are Ideas Getting Harder to Find?

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., 37, 128 Khmer Rouge, 60 Kim Il-sung: life extension efforts, 84–85 Korea, division of, 40–41 Kremer, Michael, 152 labour force countering the slowing rate of technological progress, 155–156 economic stagnation, 150 increasing scientific research efforts, 152 women’s participation, 53, 61–62 See also slavery Large Hadron Collider, 151 Lay, Benjamin, 49–51, 72 Learn How to Increase Your Chances of Winning the Lottery (Lustig), 203 learning more, to positively influence the future, 226–227, 235–237 Legalism (China), 76–78 Levy, David, 106 Lewis, Joshua, 199 LGBTQ+ individuals moral views on the status of, 53 transmission of cultural traits, 95 life, evolution of, 117–119 life expectancy among hunter-gatherer societies, 207 changes over time, 205(fig.)

Elon Musk: A Mission to Save the World by Anna Crowley Redding

Albert Einstein, artificial general intelligence, Burning Man, California high-speed rail, Colonization of Mars, El Camino Real, Elon Musk, energy security, Ford Model T, gigafactory, high-speed rail, Hyperloop, Internet Archive, Jeff Bezos, Khan Academy, Kim Stanley Robinson, Kwajalein Atoll, Large Hadron Collider, low earth orbit, Mars Society, Max Levchin, Menlo Park, OpenAI, orbital mechanics / astrodynamics, Peter Thiel, Silicon Valley, Silicon Valley startup, Solyndra, SpaceX Starlink, Stephen Hawking, Steve Jurvetson, TED Talk, Tesla Model S, Wayback Machine

We aren’t creating massive sonic booms because we evacuated the air,”161 Elon said. “We built a Hyperloop test track adjacent to SpaceX, just for a student competition, to encourage innovative ideas in transport. And it actually ends up being the biggest vacuum chamber in the world after the Large Hadron Collider, by volume.”162 Students are designing potential pods? Yes. That first year, 2015, over a thousand universities worldwide entered the competition. The proposals were narrowed down to twenty, and the students tested their designs at SpaceX. The fastest pod that can stop without crashing wins.

Fool Me Twice: Fighting the Assault on Science in America by Shawn Lawrence Otto

affirmative action, Albert Einstein, An Inconvenient Truth, anthropic principle, Apollo 11, Berlin Wall, biodiversity loss, Brownian motion, carbon footprint, carbon tax, Cepheid variable, clean water, Climategate, Climatic Research Unit, cognitive dissonance, Columbine, commoditize, cosmological constant, crowdsourcing, cuban missile crisis, Dean Kamen, desegregation, different worldview, disinformation, double helix, Dr. Strangelove, energy security, Exxon Valdez, fudge factor, Garrett Hardin, ghettoisation, global pandemic, Great Leap Forward, Gregor Mendel, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, informal economy, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Large Hadron Collider, Louis Pasteur, luminiferous ether, military-industrial complex, mutually assured destruction, Neil Armstrong, ocean acidification, Richard Feynman, Ronald Reagan, Saturday Night Live, shareholder value, sharing economy, smart grid, stem cell, synthetic biology, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Tragedy of the Commons, transaction costs, University of East Anglia, War on Poverty, white flight, Winter of Discontent, working poor, yellow journalism, zero-sum game

I felt that just as a theory is beautiful, so, too, is a scientific instrument—or that it should be.” The futuristic superconducting technologies Wilson pushed for helped keep the accelerator vital under the leadership of his successor, the physicist, Nobel laureate, and great science humanitarian Leon Lederman, and it remained the world’s most powerful until 2006, when the Large Hadron Collider opened at CERN (European Organization for Nuclear Research) in Geneva. TO AWAKEN, PERCHANCE TO WONDER As Wilson noted, science, like art, is a cultural expression that makes a nation worth defending. Like great art and great music, its true value lies in exploring the unknown. Today, the opposite argument, the commoditization of science, is virtually the only one heard.

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., 100 Kitzmiller, Tammy, 173 Knowledge belief versus, 49 current, 300–301 deductive reasoning and, 43 democracy and, 3–4, 90, 219 demonstrative, 50 denial of, 296 Earth’s age and, 27–28 ethics and, 25 freedom and, 74 inductive reasoning and, 44, 67 intuitive, 50, 53 life’s beginning and, 28–30 Lock’s view of, 49–50, 117, 123, 145, 169, 174 Nazi party and, 74 new, 158–59 observation and, 30, 169 power and, 22–23, 219–21 propaganda strategy and, 197 science and, 4, 25, 74 scientific method and, 30 sensitive/sensory, 50, 117 separation from individual and, 126, 128 suppression of, 220–21 truth and, 49–50 Kotlyakov, V. M., 211–12 Krauss, Lawrence, 133–34 Kuhn, Thomas, 115–17, 119–21, 138 Kyoto Protocol, 189, 191 L Lapp, Ralph, 96–97 Large Hadron Collider, 311 Laud, William, 45–46 Laurence, William, 77 Laverty, Lyle, 197 Lawrence, Ernest, 75 Leadership, 267–69, 301–4 Leavitt, Henrietta, 66 Leavitt, Norman, 129 Lederman, Leon, 311 Left Wing, political, 30–31, 31 Legates, David, 193–94 Lemaître, Georges, 69–70 Lenard, Philipp, 63 Leshner, Alan, 157–58, 182–83 Levin, Simon, 54–55, 181–82, 255–56, 259–60 Levitt, Steven, 229–32 Lewis and Clark expedition, 48, 57 Liberalism, 64 Liberty.

Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth by Stuart Ritchie

Albert Einstein, anesthesia awareness, autism spectrum disorder, Bayesian statistics, Black Lives Matter, Carmen Reinhart, Cass Sunstein, Charles Babbage, citation needed, Climatic Research Unit, cognitive dissonance, complexity theory, coronavirus, correlation does not imply causation, COVID-19, crowdsourcing, data science, deindustrialization, Donald Trump, double helix, en.wikipedia.org, epigenetics, Estimating the Reproducibility of Psychological Science, fake news, Goodhart's law, Growth in a Time of Debt, Helicobacter pylori, Higgs boson, hype cycle, Kenneth Rogoff, l'esprit de l'escalier, Large Hadron Collider, meta-analysis, microbiome, Milgram experiment, mouse model, New Journalism, ocean acidification, p-value, phenotype, placebo effect, profit motive, publication bias, publish or perish, quantum entanglement, race to the bottom, randomized controlled trial, recommendation engine, rent-seeking, replication crisis, Richard Thaler, risk tolerance, Ronald Reagan, Scientific racism, selection bias, Silicon Valley, Silicon Valley startup, social distancing, Stanford prison experiment, statistical model, stem cell, Steven Pinker, TED Talk, Thomas Bayes, twin studies, Tyler Cowen, University of East Anglia, Wayback Machine

Along the same lines, Fisher later noted that some researchers might like to set their significance criterion differently depending on what they were testing.23 The ‘5 sigma evidence’ that CERN physicists famously discussed after the discovery of the Higgs Boson in 2012, for example, was just a fancy-sounding way of talking about the extremely stringent p-value threshold they used for such a crucial result: ‘5 sigmas’ corresponds to a p-value threshold of about 0.0000003.24 Having poured vast resources into constructing the Large Hadron Collider, the physicists really didn’t want to be hoodwinked by noise in their data, so they set a very high standard for the evidence to pass. Outside of exceptions such as the Higgs Boson, though, the 0.05 threshold remains, through conformity, tradition and inertia, the most widely used criterion today.

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ABC News abortion Abu Ghraib prison abuse (2003) accidental discoveries Acta Crystallographica Section E acupuncture Afghan hounds Agence France-Presse AIDS (acquired immune deficiency syndrome) Alchemist, The (Bega) Alexander, Benita Alexander, Scott algorithms allergies Alzheimer, Aloysius Alzheimer’s Disease Amazon American Journal of Potato Research Amgen amygdala amyloid cascade hypothesis anaesthesia awareness Fujii affair (2012) outcome switching Anaesthesia & Analgesia animal studies antidepressants antipsychotics archaeology Arnold, Frances arsenic artificial tracheas asthma austerity Australia Austria autism aviation Babbage, Charles Bacon, Francis bacteria Bargh, John Bayer Bayes, Thomas Bayesian statistics BDNF gene Before You Know It (Bargh) Bega, Cornelis Begley, Sharon Belgium Bell Labs Bem, Daryl benzodiazepines bias blinding and conflict of interest De Vries’ study (2018) funding and groupthink and meaning well bias Morton’s skull studies p-hacking politics and publication bias randomisation and sexism and Bik, Elisabeth Bill & Melinda Gates Foundation Biomaterials biology amyloid cascade hypothesis Bik’s fake images study (2016) Boldt affair (2010) cell lines China, misconduct in Hwang affair (2005–6) Macchiarini affair (2015–16) meta-scientific research microbiome studies Morton’s skull studies Obokata affair (2014) outcome switching preprints publication bias replication crisis Reuben affair (2009) spin and statistical power and Summerlin affair (1974) Wakefield affair (1998–2010) biomedical papers bird flu bispectral index monitor black holes Black Lives Matter blinding blotting BMJ, The Boldt, Joachim books Borges, Jorge Luis Boulez, Pierre Boyle, Robert brain imaging Brass Eye vii British Medical Journal Brock, Jon bronchoscopy Broockman, David Brown, Nick Bush, George Walker business studies BuzzFeed News California Walnut Commission California wildfires (2017) Canada cancer cell lines collaborative projects faecal transplants food and publication bias and replication crisis and sleep and spin and candidate genes carbon-based transistors Cardiff University cardiovascular disease Carlisle, John Carlsmith, James Carney, Dana cash-for-publication schemes cataracts Cell cell lines Cell Transplantation Center for Open Science CERN (Conseil Européen pour la Recherche Nucléaire) chi-squared tests childbirth China cash-for-publication schemes cell line mix-ups in Great Famine (1959–1961) misconduct cases in randomisation fraud in chrysalis effect Churchill, Winston churnalism Cifu, Adam citations clickbait climate change cloning Clostridium difficile cochlear implants Cochrane Collaboration coercive citation coffee cognitive dissonance cognitive psychology cognitive tests coin flipping Colbert Report, The Cold War collaborative projects colonic irrigation communality COMPare Trials COMT gene confidence interval conflict of interest Conservative Party conspicuous consumption Cooperative Campaign Analysis Project (CCAP) ‘Coping with Chaos’ (Stapel) Cornell University coronavirus (COVID-19) Corps of Engineers correlation versus causation corticosteroids Cotton, Charles Caleb creationism Crowe, Russell Csiszar, Alex Cuddy, Amy CV (curriculum vitae) cyber-bullying cystic fibrosis Daily Mail Daily Telegraph Darwin Memorial, The’ (Huxley) Darwin, Charles Das, Dipak datasets fraudulent Observational publication bias Davies, Phil Dawkins, Richard De Niro, Robert De Vries, Ymkje Anna debt-to-GDP ratio Deer, Brian democratic peace theory Denmark Department of Agriculture, US depression desk rejections Deutsche Bank disabilities discontinuous mind disinterestedness DNA (deoxyribonucleic acid) domestication syndrome doveryai, no proveryai Duarte, José Duke University duloxetine Dutch Golden Age Dutch Organisation for Scientific Research Dweck, Carol economics austerity preprints statistical power and effect size Einstein, Albert Elmo Elsevier engineering epigenetics euthanasia evolutionary biology exaggeration exercise Experiment, The exploratory analyses extrasensory perception faecal transplants false-positive errors Fanelli, Daniele Festinger, Leon file-drawer problem financial crisis (2007–8) Fine, Cordelia Fisher, Ronald 5 sigma evidence 5-HT2a gene 5-HTTLPR gene fixed mindset Food and Drug Administration (FDA) Food Frequency Questionnaires food psychology Formosus, Pope foxes France Francis, Pope Franco, Annie fraud images investigation of motives for numbers Open Science and peer review randomisation Freedom of Information Acts French, Chris Fryer, Roland Fujii, Yoshitaka funding bias and fraud and hype and long-term funding perverse incentive and replication crisis and statistical power and taxpayer money funnel plots Future of Science, The (Nielsen) gay marriage Gelman, Andrew genetically modified crops genetics autocorrect errors candidate genes collaborative projects gene therapy genome-wide association studies (GWASs) hype in salami-slicing in Geneva, Switzerland geoscience Germany Getty Center GFAJ-1 Giner-Sorolla, Roger Glasgow Effect Goldacre, Ben Goldsmiths, University of London Golgi Apparatus good bacteria Good Morning America good scientific citizenship Goodhart’s Law Goodstein, David Google Scholar Górecki, Henryk Gould, Stephen Jay Gran Sasso, Italy grants, see funding Granularity-Related Inconsistency of Means (GRIM) grapes Great Recession (2007–9) Great Red Spot of Jupiter Green, Donald Gross Domestic Product (GDP) Gross, Charles ground-breaking results groupthink ‘Growth in a Time of Debt’ (Reinhart and Rogoff) growth mindset Guzey, Alexey gynaecology h-index H5N1 Haldane, John Burdon Sanderson Hankins, Matthew HARKing Harris, Sidney Harvard University headache pills heart attacks heart disease Heathers, James height Heilongjiang University Heino, Matti Henry IV (Shakespeare) Higgs Boson Hirsch, Jorge HIV (human immunodeficiency viruses) homosexuality Hong Kong Hooke, Robert Hossenfelder, Sabine Houston, Texas Hume, David Huxley, Thomas Henry Hwang, Woo-Suk hydroxyethyl starch hype arsenic life affair (2010) books correlation versus causation cross-species leap language and microbiome studies news stories nutrition and press releases spin unwarranted advice hypotheses Ig Nobel Prize images, fraudulent impact factor India insomnia International Journal of Advanced Computer Technology Ioannidis, John IQ tests Iraq War (2003–11) Italy Japan John, Elton Journal of Cognitive Education and Psychology Journal of Environmental Quality Journal of Negative Results in Biomedicine Journal of Personality and Social Psychology journals conflict of interest disclosure fraud and hype and impact factor language in mega-journals negligence and Open Science and peer review, see peer review predatory journals preprints publication bias rent-seeking replication studies retraction salami slicing subscription fees Jupiter Kahneman, Daniel Kalla, Joshua Karolinska Institute Krasnodar, Russia Krugman, Paul Lacon, or Many Things in Few Words (Cotton) LaCour, Michael Lancet Fine’s ‘feminist science’ article (2018) Macchiarini affair (2015–16) Wakefield affair (1998–2010) language Large Hadron Collider Le Texier, Thibault Lewis, Jason Lexington Herald-Leader Leyser, Ottoline Lilienfeld, Scott Loken, Eric Lost in Math (Hossenfelder) low-fat diet low-powered studies Lumley, Thomas Lysenko, Trofim Macbeth (Shakespeare) Macbeth effect Macchiarini, Paolo MacDonald, Norman machine learning Macleod, Malcolm Macroeconomics major depressive disorder Malaysia Mao Zedong MARCH1 Marcus, Adam marine biology Markowetz, Florian Matthew Effect Maxims and Moral Reflections (MacDonald) McCartney, Gerry McCloskey, Deirdre McElreath, Richard meaning well bias Measles, Mumps & Rubella (MMR) measurement errors Medawar, Peter medical research amyloid cascade hypothesis Boldt affair (2010) cell lines China, misconduct in collaborative projects Fujii affair (2012) Hwang affair (2005–6) Macchiarini affair (2015–16) meta-scientific research Obokata affair (2014) outcome switching pharmaceutical companies preprints pre-registration publication bias replication crisis Reuben affair (2009) spin and statistical power and Summerlin affair (1974) Wakefield affair (1998–2010) medical reversal Medical Science Monitor Mediterranean Diet Merton, Robert Mertonian Norms communality disinterestedness organised scepticism universalism meta-science Boldt affair (2010) chrysalis effect De Vries’ study (2018) Fanelli’s study (2010) Ioannidis’ article (2005) Macleod’s studies mindset studies (2018) saturated fats studies spin and stereotype threat studies mice microbiome Microsoft Excel Milgram, Stanley Mill, John Stuart Mindset (Dweck) mindset concept Mismeasure of Man, The (Gould) Modi, Narendra money priming Mono Lake, California Moon, Hyung-In Morton, Samuel Motyl, Matt multiverse analysis nanotechnology National Academy of Sciences National Aeronautics and Space Administration (NASA) National Institutes of Health National Science Foundation Nature cash-for-publication and cell line editorial (1981) impact factor language in Obokata affair (2014) Open Access and open letter on statistical significance (2019) replication research Schön affair (2002) Stapel affair (2011) Nature Neuroscience Nature Reviews Cancer NBC negligence cell line mix-ups numerical errors statistical power typos Netflix Netherlands replication studies in Stapel’s racism studies statcheck research neuroscience amyloid cascade hypothesis collaborative projects Macleod’s animal research studies replication crisis sexism and statistical significance and Walker’s sleep studies neutrinos New England Journal of Medicine New York Times New Zealand news media Newton, Isaac Nielsen, Michael Nimoy, Leonard No Country for Old Men Nobel Prize northern blots Nosek, Brian Novella, Steven novelty Novum Organum (Bacon) Nuijten, Michèle nullius in verba, numerical errors nutrition Obama, Barack obesity Obokata, Haruko observational datasets obstetrics ocean 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Science perverse incentive cash for publications competition CVs and evolutionary analogy funding impact factor predatory journals salami slicing self-plagiarism Pett, Joel pharmaceutical companies PhDs Philosophical Transactions phlogiston phosphorus Photoshop Physical Review physics placebos plagiarism Plan S Planck, Max plane crashes PLOS ONE pluripotency Poehlman, Eric politics polygenes polyunsaturated fatty acids Popper, Karl populism pornography positive feedback loops positive versus null results, see publication bias post-traumatic stress disorder (PTSD) power posing Prasad, Vinay pre-registration preclinical studies predatory journals preprints Presence (Cuddy) press releases Prevención con Dieta Mediterránea (PREDIMED) priming Princeton University Private Eye probiotics Proceedings of the National Academy of Sciences prosthetic limbs Przybylski, Andrew psychic precognition Psychological Medicine psychology Bargh’s priming study (1996) Bem’s precognition studies books Carney and Cuddy’s power posing studies collaborative projects data sharing study (2006) Dweck’s mindset concept Festinger and Carlsmith’s cognitive dissonance studies Kahneman’s priming studies LaCour’s gay marriage experiment politics and preprints publication bias in Shanks’ priming studies Stanford Prison Experiment Stapel’s racism studies statistical power and Wansink’s food studies publication bias publish or perish Pubpeer Pythagoras’s theorem Qatar quantum entanglement racism Bargh’s priming studies Morton’s skull studies Stapel’s environmental studies randomisation Randy Schekman Reagan, Ronald recommendation algorithms red grapes Redfield, Rosemary Reflections on the Decline of Science in England (Babbage) Reinhart, Carmen Rennie, Drummond rent-seeking replication; replication crisis Bargh’s priming study Bem’s precognition studies biology and Carney and Cuddy’s power posing studies chemistry and economics and engineering and geoscience and journals and Kahneman’s priming studies marine biology and medical research and neuroscience and physics and Schön’s carbon-based transistor Stanford Prison Experiment Stapel’s racism studies Wolfe-Simon’s arsenic life study reproducibility Republican Party research grants research parasites resveratrol retraction Arnold Boldt Fujii LaCour Macchiarini Moon Obokata Reuben Schön Stapel Wakefield Wansink Retraction Watch Reuben, Scott Reuters RIKEN Rogoff, Kenneth romantic priming Royal Society Rundgren, Todd Russia doveryai, no proveryai foxes, domestication of Macchiarini affair (2015–16) plagiarism in salami slicing same-sex marriage sample size sampling errors Sanna, Lawrence Sasai, Yoshiki saturated fats Saturn Saudi Arabia schizophrenia Schoenfeld, Jonathan Schön, Jan Hendrik School Psychology International Schopenhauer, Arthur Science acceptance rate Arnold affair (2020) arsenic life affair (2010) cash-for-publication and Hwang affair (2005) impact factor LaCour affair (2014–15) language in Macbeth effect study (2006) Open Access and pre-registration investigation (2020) replication research Schön affair (2002) Stapel affair (2011) toxoplasma gondii scandal (1961) Science Europe Science Media Centre scientific journals, see journals scientific papers, see papers Scientific World Journal, The Scotland Scottish Socialist Party screen time self-citation self-correction self-plagiarism self-sustaining systems Seoul National University SEPT2 Sesame Street sexism sexual selection Shakespeare, William Shanks, David Shansky, Rebecca Simmons, Joseph Simonsohn, Uri Simpsons, The skin grafts Slate Star Codex Sloan-Kettering Cancer Institute Smaldino, Paul Smeesters, Dirk Smith, Richard Snuppy social media South Korea Southern blot Southern, Edwin Soviet Union space science special relativity specification-curve analysis speed-accuracy trade-off Spies, Jeffrey spin Springer Srivastava, Sanjay Stalin, Joseph Stanford University Dweck’s mindset concept file-drawer project (2014) Prison Experiment (1971) Schön affair (2002) STAP (Stimulus-Triggered Acquisition of Pluripotency) Stapel, Diederik statcheck statistical flukes statistical power statistical significance statistical tests Status Quo stem cells Stephen VI, Pope stereotype threat Sternberg, Robert strokes subscription fees Summerlin, William Sweden Swift, Jonathan Swiss Federal Institute of Technology Sydney Morning Herald Symphony of Sorrowful Songs (Górecki) t-tests Taiwan taps-aff.co.uk tax policies team science TED (Technology, Entertainment, and Design) Texas sharpshooter analogy Thatcher, Margaret theory of special relativity Thinking, Fast and Slow (Kahneman) Thomson Reuters Tilburg University Titan totalitarianism toxoplasma gondii trachea translational research transparency Tribeca Film Festival triplepay system Trump, Donald trust in science ‘trust, but verify’ Tumor Biology Turkey Tuulik, Julia Twitter typos UK Reproducibility Network Ulysses pact United Kingdom austerity cash-for-publication schemes image duplication in multiverse analysis study (2019) National Institute for Health Research pre-registration in Royal Society submarines trust in science university ranks in Wakefield affair (1998–2010) United States Arnold affair (2020) arsenic life affair (2010) austerity Bargh’s priming study (1996) Bem’s precognition studies California wildfires (2017) Carney and Cuddy’s power posing studies Center for Nutrition Policy and Promotion climate science in creationism in Das affair (2012) De Vries’ drug study (2018) Department of Agriculture Dweck’s mindset concept Fryer’s police brutality study (2016) image duplication in Kahneman’s priming studies LaCour affair (2014–15) Morton’s skull studies Office for Research Integrity Poehlman affair (2006) pre-registration in public domain laws Reuben affair (2009) Stanford Prison Experiment Summerlin affair (1974) tenure Walker’s sleep studies Wansink affair (2016) universalism universities cash-for-publication schemes fraud and subscription fees and team science University College London University of British Columbia University of California Berkeley Los Angeles University of Connecticut University of East Anglia University of Edinburgh University of Hertfordshire University of London University of Pennsylvania unsaturated fats unwarranted advice vaccines Vamplew, Peter Vanity Fair Vatican Vaxxed Viagra vibration-of-effects analysis virology Wakefield, Andrew Walker, Matthew Wansink, Brian Washington Post weasel wording Weisberg, Michael Wellcome Trust western blots Westfall, Jake ‘Why Most Published Research Findings Are False’ (Ioannidis) Why We Sleep (Walker) Wiley Wiseman, Richard Wolfe-Simon, Felisa World as Will and Presentation, The (Schopenhauer) World Health Organisation (WHO) Yale University Yarkoni, Tal Yes Men Yezhov, Nikolai Z-tests Ziliak, Stephen Zimbardo, Philip Zola, Émile About the Author Stuart Ritchie is a lecturer in the Social, Genetic and Developmental Psychiatry Centre at King’s College London.

Letters From an Astrophysicist by Neil Degrasse Tyson

dark matter, do what you love, Isaac Newton, Johannes Kepler, Large Hadron Collider, microaggression, Pluto: dwarf planet, The Wealth of Nations by Adam Smith, unbiased observer

So to imply that I have somehow misrepresented the state of American science is simply false. 2.The back story here, known well to people who follow my writings, is that we began construction of the Superconducting Supercollider in the 1980s. That machine was designed with 3x the power of the Large Hadron Collider in Switzerland today, which is garnering all the physics headlines. Congress cut the project entirely in the early 1990s, crippling particle physics in America. That’s why we are bystanders and not leaders in these international headlines. And all this feeds the potency of the Tweet itself. 3.Your note implies that the Tweet may have somehow done a disservice to science or science education or to AMNH itself.

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

His strips have a heavy science/technology bent (the comic’s strapline is “A webcomic of romance, sarcasm, math, and language”), and you see them posted on office doors in every university’s math, science, and computer science departments. They’re also liberally posted around research institutes like CERN, home of the Large Hadron Collider, and the Wellcome Trust Sanger Institute, one of the homes of the Human Genome Project. But Randall can’t eat the adulation of nerds. Instead, he sells swag. A lot of swag. Randy lives with his wife in a house whose living room has been converted into a ball pit. He and his friends sit in the ball pit and play video games all day.

Blockchain: Blueprint for a New Economy by Melanie Swan

23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, basic income, bioinformatics, bitcoin, blockchain, capital controls, cellular automata, central bank independence, clean water, cloud computing, collaborative editing, Conway's Game of Life, crowdsourcing, cryptocurrency, data science, digital divide, disintermediation, Dogecoin, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, information security, intangible asset, Internet Archive, Internet of things, Khan Academy, Kickstarter, Large Hadron Collider, lifelogging, litecoin, Lyft, M-Pesa, microbiome, Neal Stephenson, Network effects, new economy, operational security, peer-to-peer, peer-to-peer lending, peer-to-peer model, personalized medicine, post scarcity, power law, prediction markets, QR code, ride hailing / ride sharing, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Skype, smart cities, smart contracts, smart grid, Snow Crash, software as a service, synthetic biology, technological singularity, the long tail, Turing complete, uber lyft, unbanked and underbanked, underbanked, Vitalik Buterin, Wayback Machine, web application, WikiLeaks

The media presents estimates of power consumption such as “the Eiffel Tower could stay lit for 260 years with the energy used to mine Bitcoins since 2009,”128 and that in 2013 Bitcoin mining was consuming about 982 megawatt hours a day (enough to power 31,000 homes in the United States, or half a Large Hadron Collider),129 at a cost of $15 million a day.130 However, the comparison metric is unclear; should these figures be regarded as a little or a lot (and what are the direct economic benefits of the Eiffel Tower and the LHC, for that matter)? Bitcoin proponents counter that the blockchain model is vastly cheaper when you consider the fully loaded cost of the current financial system, which includes the entire infrastructure of physical plant bank branch offices and personnel.

The Greatest Show on Earth: The Evidence for Evolution by Richard Dawkins

Alfred Russel Wallace, Andrew Wiles, Arthur Eddington, back-to-the-land, Claude Shannon: information theory, correlation does not imply causation, Craig Reynolds: boids flock, Danny Hillis, David Attenborough, discovery of DNA, Dmitri Mendeleev, domesticated silver fox, double helix, en.wikipedia.org, epigenetics, experimental subject, Gregor Mendel, heat death of the universe, if you see hoof prints, think horses—not zebras, invisible hand, Large Hadron Collider, Louis Pasteur, out of africa, phenotype, precautionary principle, Thomas Malthus

The gorilla film, or something like it, should perhaps be shown to all juries before they retire to consider their verdicts. All judges too. Admittedly, inference has to be based ultimately on observation by our sense organs. For example, we use our eyes to observe the printout from a DNA sequencing machine, or from the Large Hadron Collider. But – all intuition to the contrary – direct observation of an alleged event (such as a murder) as it actually happens is not necessarily more reliable than indirect observation of its consequences (such as DNA in a bloodstain) fed into a well-constructed inference engine. Mistaken identity is more likely to arise from direct eye-witness testimony than from indirect inference derived from DNA evidence.

…

The Human Genome Project took about ten years, representing many person-centuries. Although it would now be possible to achieve the same result in a fraction of the time, it would still be a large and expensive undertaking, as would the hedgehog genome project. Like the Apollo moon landings, and like the Large Hadron Collider (which has just been switched on in Geneva as I write – the gigantic scale of this international endeavour moved me to tears when I visited), the complete deciphering of the human genome is one of those achievements that makes me proud to be human. I am delighted that the chimpanzee genome project has now been successfully accomplished, and the equivalent for various other species.

Them And Us: Politics, Greed And Inequality - Why We Need A Fair Society by Will Hutton

Abraham Maslow, Alan Greenspan, Andrei Shleifer, asset-backed security, bank run, banking crisis, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Blythe Masters, Boris Johnson, bread and circuses, Bretton Woods, business cycle, capital controls, carbon footprint, Carmen Reinhart, Cass Sunstein, centre right, choice architecture, cloud computing, collective bargaining, conceptual framework, Corn Laws, Cornelius Vanderbilt, corporate governance, creative destruction, credit crunch, Credit Default Swap, debt deflation, decarbonisation, Deng Xiaoping, discovery of DNA, discovery of the americas, discrete time, disinformation, diversification, double helix, Edward Glaeser, financial deregulation, financial engineering, financial innovation, financial intermediation, first-past-the-post, floating exchange rates, Francis Fukuyama: the end of history, Frank Levy and Richard Murnane: The New Division of Labor, full employment, general purpose technology, George Akerlof, Gini coefficient, Glass-Steagall Act, global supply chain, Growth in a Time of Debt, Hyman Minsky, I think there is a world market for maybe five computers, income inequality, inflation targeting, interest rate swap, invisible hand, Isaac Newton, James Dyson, James Watt: steam engine, Japanese asset price bubble, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, knowledge economy, knowledge worker, labour market flexibility, language acquisition, Large Hadron Collider, liberal capitalism, light touch regulation, Long Term Capital Management, long term incentive plan, Louis Pasteur, low cost airline, low interest rates, low-wage service sector, mandelbrot fractal, margin call, market fundamentalism, Martin Wolf, mass immigration, means of production, meritocracy, Mikhail Gorbachev, millennium bug, Money creation, money market fund, moral hazard, moral panic, mortgage debt, Myron Scholes, Neil Kinnock, new economy, Northern Rock, offshore financial centre, open economy, plutocrats, power law, price discrimination, private sector deleveraging, proprietary trading, purchasing power parity, quantitative easing, race to the bottom, railway mania, random walk, rent-seeking, reserve currency, Richard Thaler, Right to Buy, rising living standards, Robert Shiller, Ronald Reagan, Rory Sutherland, Satyajit Das, Savings and loan crisis, shareholder value, short selling, Silicon Valley, Skype, South Sea Bubble, Steve Jobs, systems thinking, tail risk, The Market for Lemons, the market place, The Myth of the Rational Market, the payments system, the scientific method, The Wealth of Nations by Adam Smith, three-masted sailing ship, too big to fail, unpaid internship, value at risk, Vilfredo Pareto, Washington Consensus, wealth creators, work culture , working poor, world market for maybe five computers, zero-sum game, éminence grise

This ‘dual-support’ funding system has allowed the UK to get far more bang for every pound of funding than other countries by channelling resources towards excellence and innovation. It has a string of achievements to its name – Bristol University’s BlueCrystal hyper-fast computer, Aberdeen’s work on Alzheimer’s, Durham’s Institute for Particle Physics Phenomenology (IPPP), which drives the analysis behind the Large Hadron Collider in Geneva, and York’s Neuroimaging Centre (YNiC), to name but a few.50 Meanwhile, private R & D laboratories disproportionately cluster where there is university research excellence. One study showed that chemistry departments rated 5 or 5* by the RAE are likely to have around twice as many labs doing R & D in pharmaceuticals and around three times as many foreign-owned R & D pharmaceuticals labs.51 However, it is not an unalloyed success.

…

., 17, 36, 135, 177 Cabinet Office, 218–19, 336, 337 Cable, Vincent, 220 Cambridge University, 9, 363 Cameron, David, 20, 179, 233–4, 235, 318, 338, 342; ‘Big Society’ policy, 19–20, 234, 271, 280 Campbell, Alastair, 141, 142, 224, 312 Canada, 121, 354, 358–9, 383 capital controls, abolition of, 32, 161 capitalism: see also entrepreneurs; innovation; amorality of, 16–19; ‘arms race’ effects, 105; boom and bust cycle, 181–7, 392; deregulation (from 1970s), 159–63, 388; fairness and, ix, x, 23–7, 41, 106, 122–3, 206–7, 210, 249, 385, 386, 394; as immutable force of nature, ix, 23, 40–2; incumbent firms, 29–30, 31, 105, 106, 110, 111–12, 253–5, 257, 297; interconnectedness of markets, 200–2, 204; knowledge-entrepreneurship dynamic, 27–8, 31, 103, 110–11, 112–13; liquidity as totemic, 199, 200, 202, 240, 243; need for ‘circuit breakers’, 197, 199, 202, 203; network theory and, 199–204, 206; required reforms of, 205–9, 215–16; stakeholder, x, 148–9; undue influence of, 32–3 Carlaw, Kenneth, 108, 263 Carnegie, Andrew, 195, 303 cars, motor, 91, 108, 109, 134, 269 Castells, Manuel, 317 Cayne, Jimmy, 173–4 CCTV cameras, 10 celebrity culture, 282, 314 central banks, 154, 157, 158, 160, 182, 185, 187, 208; see also Bank of England; Federal Reserve, 169–70, 176, 177, 183 Cerberus Capital Management, 177 Cervantes, Miguel de, 274 Channel 4, 330, 350 Charles I, King of England, 124–5 Charter One Financial, 150 chavs, mockery of, 25, 83, 272, 286–8 child poverty, 12, 21, 74–5, 83, 278, 279, 288–90, 291 China, x, 101, 112, 140, 144, 160, 226, 230, 354–5, 385; consumption levels, 375–6, 379, 380, 381; economic conflict with USA, 376–7, 378–80, 381, 382, 383; export led growth, 36, 169, 208, 226, 355–6, 375–7, 379–81, 382–3; rigged exchange rates, 36, 169, 355, 377, 378–9; surpluses of capital and, 149, 154, 169, 171, 208, 226, 375; unfairness of world system and, 383, 385 Christianity, 53, 54, 352, 353 Church of England, 128 Churchill, Winston, 138, 273, 313 Churchill Insurance, 150 Cisco, 253 Citigroup, 152, 158, 172, 177, 184, 202, 203, 242, 247 city academies, 278, 307 City of London, 34, 137, 138, 178–9, 252, 359; as incumbent elite, 14, 26, 31, 32–3, 210, 249, 355; in late nineteenth-century, 128–30; light-touch regulation of, 5, 32, 138, 145, 146–7, 151, 162, 187, 198–9; New Labour and, x–xi, 5, 19, 22, 142, 144–5, 355; remuneration levels see pay of executives and bankers civic engagement, 86, 313 civil service, 13, 221, 273, 312, 343 Clasper, Mike, 178 Clayton Act (USA, 1914), 133 Clegg, Nick, 22, 218, 318, 327–8, 342, 391 Clifton, Pete, 321 Clinton, Bill, 140, 177, 183 coalition government (from May 2010), 14, 20, 22, 37, 307, 311, 343, 346, 390–2; abolition of child trust fund, 302; capital spending cuts, 370–1; deficit reduction programme, xi, 19, 34, 214, 227, 357, 360–1, 364, 369–71, 373, 390–2; emergency budget (June 2010), 369–70; market fundamentalism and, 370; political reform commitment, 35, 341, 343–4, 346, 350, 390, 391; proposed financial reforms, 208, 209, 245, 252, 371; repudiation of Keynesian economics, xi, 390–1 Cohan, William, 158–9 Cohen, Ronald, 12, 245 collapse/crash of financial system, x, xi, 4, 9, 41, 144, 146, 152–4, 158–9, 168; costs of, 7, 19, 138, 152–3, 172, 214–15; errors responsible for, 136, 187–96, 197–204; global interconnectedness, 375, 382–3; lessening of internationalism following, 376–83; need to learn from/understand, 36–7; predictions/warnings of, 148, 153, 180, 182–5; recommended policy responses, 215–16; results of previous credit crunches, 358, 359–60, 361–2 collateralised debt obligations (CDOs), 155, 167–8, 174 colonialism, 109, 124 Commodity Future Trading Commission, 182–3 communism, collapse of in Eastern Europe, 16, 19, 135, 140, 163 competition, 29, 30, 33, 51, 156, 185, 186, 207–8, 251; see also ‘open-access societies’; City of London and, 160, 178, 179, 198–9; deregulated banking and, 160, 161, 163, 164, 178, 179, 181; European Union and, 251, 258, 259; fairness and, 89–90, 99, 272; incumbent elites/oligarchs and, 104, 114, 129–30, 131–4, 257; innovation and, 40, 114, 257–60; national authorities/regimes, 201–2, 257–60, 316, 318; state facilitation of, 31 Competition Commission, 257–8 computer games, 233 Confederation of British Industry (CBI), 4, 6–7 Conservative Party, xi, 5, 11, 14, 97–8, 220, 343, 378; broken Britain claims, 16, 227, 271; budget deficit and, 19, 224, 357, 360–1, 368, 379; City/private sector funding of, 179, 257, 344; decline of class-based politics, 341; deregulation and, 32, 160, 161; fairness and, 83, 302, 374, 390; general election (1992) and, 140–1; general election (2010) and, 20, 97, 227, 234, 271, 357, 374, 379, 390; Conservative Party – continued government policies (1979-97), 32, 81, 275–6, 290; inheritance/wealth taxes and, 74, 302–3; market fundamentalism and, 5, 17, 138, 147, 160, 161; poverty and, 21, 279; reduced/small state policy, 20, 22, 233–4, 235 construction industry, 5, 33, 268 consumer goods, types of, 266–7 Continental Illinois collapse, 152, 162 Convention on Modern Liberty, 340 Cook, Robin, 142 Cootner, Paul, 194–5 Copenhagen climate change talks (2009), 226, 231, 385 Corporate Leadership Council, US, 93 Corzine, Jon, 177 county markets, pre-twentieth-century, 90 Coutts, Ken, 363 Cowell, Simon, 314, 315 ‘creative destruction’ process, 111, 112, 134 creative industries, 11, 71, 355 credit cards, 64, 354 credit crunch: see collapse/crash of financial system credit default swaps, 151, 152, 166–8, 170, 171, 175, 176, 191, 203, 207 Crédit Lyonnais collapse, 152 credit-rating agencies, 151, 165, 175, 196, 197, 248, 269, 362, 388; funding of, 151, 196, 207 criminal activity/allegations, 7, 101, 103, 104–5, 138, 167–8 Crosby, James, 178 Cuba, 61 culture, British, 12, 187, 282, 314 Dacre, Paul, 324, 326, 329 Daily Mail, 218, 286, 288, 315, 324, 325–7, 339, 342 Daily Telegraph, 288, 317, 319, 327 Darling, Alistair, 149, 204, 252 Darwin, Charles, 31 Data Monitor, 186 Davies, Howard, 198 Davies, Nick, Flat Earth News, 319, 321, 323–4, 326, 331–2 de Gaulle, Charles, 65 debt, 33, 155, 209, 351–63; corporate/commercial, 8, 29, 181, 245, 248, 352, 354, 359, 363, 374; moral attitudes towards, 351–4, 357, 360–1; necessity of, 155, 351, 353, 354; private, 5, 186, 187, 210, 226, 279–80, 354–7, 359, 363, 373; public, 9, 34, 164, 166, 167, 182, 203, 214, 224–6, 356–7, 362–3, 375, 388, 393; sustainable level of, 356–7, 368–9 Defence Advanced Research Projects Agency (DARPA), 265 defence and armed forces, 34, 372 deficit, public, 4, 34, 213, 224–6, 335, 364–74; coalition’s reduction programme, xi, 19, 34, 214, 227, 357, 360–1, 364, 369–71, 373, 390–2, 393; need for fiscal policy, 224–5, 226, 357–8, 364, 365–9, 370, 374; speed of reduction of, 213, 224–5, 360–1, 368, 371 Delingpole, James, 287 Delong, Brad, 27, 106 democracy, 13–15, 235, 310–16, 333–48; centralisation of power and, 14–15, 35, 217, 313, 334, 337, 342; fair process and, 86, 89, 96–9; incumbent elites and, 35, 99; industrial revolution and, 128; media undermining of, 315–16, 317–18, 321–9, 333, 350; ‘open-access societies’ and, 136, 314 Democratic Party, US, 18, 140, 183, 379 Demos, 289 Deng Xiao Ping, 140 Denham, John, 21 deprivation and disadvantage, 10, 34, 288–93, 307–8, 393; low-earning households, 11–12, 13, 291, 361; weight of babies and, 13; young children and, 74–5, 83, 288–90 derivatives, 140, 145, 150–1, 164–8, 171, 175, 188, 207, 209; City of London and, 32, 137, 150–1, 157, 199; mathematical models (‘quants’) and, 188, 191; regulation and, 183, 197–8, 199 desert, due, concept of, 4, 24, 38–43, 45–7, 50–63, 64–8, 73–7, 80–2, 223, 395; see also effort, discretionary; proportionality; big finance and, 40–2, 82, 167, 174, 176, 210; debt and, 351–2; diplomacy/international relations and, 385–6; Enlightenment notions of, 53–6, 58–9, 112; luck and, 70, 73–7, 273; poverty relief systems and, 80–2, 277–8; productive entrepreneurship and, 102–3, 105–6, 112, 222, 392–3; taxation and, 40, 220, 266 Deutsche Bank, 170 developing countries, 71–2, 160, 354–5, 375, 376, 385 Diamond, Bob, 24 Dickens, Charles, 353 digitalisation, 34, 231, 320, 349, 350 Doepke, Matthias, 115–16 dot.com bubble, 9, 193 Drugs Advisory Panel, 11 Duffy, Gillian, 394 Durham University, 263 Dworkin, Ronald, 70 Dyson, James, 28, 33 East India Company, 130 Easyjet, 28, 233 eBay, 136 economic theory, 43–4, 188–9, 366; see also Keynesian economics; market fundamentalism economies of scale, 130–1, 254–5, 258 The Economist, 326, 330, 349 economy, British: see also capitalism; financial system, British; annual consumption levels, 375; balance of payments, 363–4; as ‘big firm’ economy, 254; change in landscape of trading partners, 230–1; coalition capital spending cuts, 370–1; collapse of tax base, 224, 368; cumulative loss of output caused by crash, 138, 153, 172, 214–15; desired level of state involvement, 234–5; domination of market fundamentalism, 16–17; economic boom, 3–4, 5–6, 12, 143, 173, 181–7, 244–5; fall in volatility, 365; fiscal deficit, 368; fiscal policy, 208, 224–5, 226, 357–8, 364–9, 370, 374; growth and, 9–10, 214–15, 218–19, 224, 359, 363; inefficient public spending, 335; investment in ‘intangibles’, 232–3; in late nineteenth-century, 128–30; ‘leading-edge’ sectors, 218–19; need for engaged long term ownership, 240–4, 249–51; as non-saver, 36, 354; potential new markets/opportunities, 231–3; public-private sector interdependence and, 219–22, 229–30, 261, 265–6, 391, 392; required reforms of, 20, 239–44, 249–52, 264–6, 371–4 see also national ecosystem of innovation; ‘specialising sectors’, 219; urgent need for reform, 36–7; volatility of, 297–8; vulnerability of after credit crunch, 358–64 economy, world: acute shortfall of demand, 375–6; Asian and/or OPEC capital surpluses and, 149, 153–4, 169, 171, 208, 226, 354, 375; conflicts of interest and, 137, 138; deregulation (from 1970s), 159–63; emerging powers’ attitudes to, 226; entrenched elites and, 137–8, 210; fall in volatility, 365; international institutions as unfair, 383, 385; London/New York axis, 149, 150–1, 157–8, 160, 187, 202; need for international cooperation, 357–8, 379–80, 381–3, 384, 385–6; post-crunch deleverage pressures, 359–60, 374–5; protectionism dangers, 36, 358, 376–7, 378, 379, 382, 386; savers/non-savers imbalance, 36, 169, 208, 222, 355, 356, 375–6, 378–83; shift of wealth from West to East, 36, 383–4; sovereign debt crises, 167, 203, 214; unheeded warnings, 182–5; wrecking of European ERM, 140, 144 Edinburgh University, 145 education, 10, 20–1, 128, 131, 272–4, 276, 278, 292–5, 304–8, 343; Building Schools for the Future programme, 371; cognitive and mental skills, 288–90, 304–6; private, 13, 114, 264–5, 272–3, 276, 283–4, 293–5, 304, 306 effort, discretionary, 50, 53, 54–5, 58–60, 80, 90–1, 114, 134; see also desert, due, concept of; fair process and, 91–4; indispensability and, 65–7; innovation and invention, 62, 65, 102–3, 105–6, 112, 117, 131, 223, 262–3, 392–3; luck and, 26–7, 65, 67, 70, 71, 73–4, 75–7; productive/unproductive, 43, 46–7, 51–2, 62, 64–5, 102–3, 392–3; proportionate reward for, 26, 39–40, 44, 47, 61, 74, 76–7, 84, 122, 272, 273, 2 84 egalitarianism, 27, 53–4, 55–6, 61, 75, 78–80, 144, 341, 343; Enlightenment equal worth concept, 53, 55, 59–60 Ehrenfeld, Rachel, 333 Eisman, Steve, 207 electoral politics: see also general election (6 May 2010); general elections, 97, 138, 277, 315; fair process and, 96–9; franchise, 128; general election (1992), x, 138, 140–1, 144, 148, 277; general election (1997), x, 138, 141 electricity, 134, 228, 256 electronic trading, 105 elites, incumbent, 23, 31–3, 99, 131; City of London, 14, 26, 31, 32–3, 210, 249, 355; competition and, 104, 113, 114, 129–30, 131–4, 257; democracy and, 35, 99; Enlightenment and, 122; history of (from 1880s), 131–4; history of in Britain (to 1900), 124–30; innovation and, 29–30, 110, 111–12, 113, 114, 115, 116; modern big finance and, 135, 137–8, 180, 210, 387–9; in ‘natural states’, 111, 113, 114–15, 116, 123–4, 127; New Labour’s failure to challenge, x–xi, 14, 22, 388, 389–90; world economy and, 137–8, 210 EMI, 28, 247, 248 employment and unemployment, 6, 75, 291–3, 295, 300, 373, 393; employment insurance concept, 298–9, 301, 374; lifelong learning schemes, 300, 301; lifelong savings plans, 300; unemployment benefit, 81, 281 Engels, Friedrich, 121–2 English language as lingua franca, 124 Enlightenment, European, 22, 30–1, 146, 261, 314–15; economics and, 104, 108–9, 116–17, 121–3; notions of fairness/desert, 53–6, 58–9, 112, 122–3, 394; science and technology and, 31, 108–9, 112–13, 116–17, 121, 126–7 Enron affair, 147 entrepreneurs: see also innovation; productive entrepreneurship; capitalist knowledge dynamic, 27–8, 31, 110–11, 112–13; challenges of the status quo, 29–30; Conservative reforms (1979-97) and, 275; private capital and, 241; public-private sector interdependence and, 219–22, 229–30, 261, 265–6, 391, 392; rent-seeking and, 61–2, 63, 78, 84, 101, 105, 112, 113–14, 116, 129, 135, 180; unproductive, 28–9, 33, 61–2, 63, 78, 84, 101–2, 103–5, 180 environmental issues, 35–6, 71–2, 102, 226, 228, 231, 236, 385, 390, 394; due desert and, 68; German Greens and, 269 Erie Railroad Company, 133 Essex County Council, 325, 332 European Commission, 298 European Exchange Rate Mechanism (ERM), 140, 144, 166 European Union (EU), 11, 82, 179, 379–80, 383–4, 385; British media and, 15, 328, 378; Competition Commissioner, 251, 258, 259; scepticism towards, 15, 36, 328, 377, 378, 386 eurozone, 377 Fabian Society, 302–3 factory system, 126 fairness: see also desert, due, concept of; proportionality; abuse/playing of system and, 24–5, 27; asset fairness proposals, 301–3, 304; behavioural psychology and, 44, 47–50, 59–61; Blair’s conservative view of, 143; Britishness and, 15–16, 392–3, 395; capitalism and, ix, x, 23–7, 41, 106, 122–3, 206–7, 210, 249, 385, 386, 394; challenges to political left, 78–83; coalition government (from May 2010) and, 22, 37; commonly held attitudes, 44, 45–7; deficit reduction and, 226, 227, 374; economic and social determinism and, 56–8; Enlightenment notions of, 53–6, 58–9, 112, 122–3, 394; fair process, 84–94, 96, 98–9, 272; as foundation of morality, 24, 26, 45, 50; individual responsibility and, 39, 78–9; inequality in Britain, 78, 80, 275–6, 277–8, 342; international relations and, 226, 385–6; ‘Just World Delusion’, 83; luck and, 72–7; management-employee relationships, 90–2; models/frameworks of, 43–58; need for shared understanding of, 25, 37, 43; partisanship about, 42–3; politicians/political parties and, 22, 83, 271–2, 302–3, 374, 391–2; popular support for NHS and, 75, 77, 283; pre-Enlightenment notions, 52–3; shared capitalism and, 66, 92–3; state facilitation of, ix–x, 391–2, 394–5; welfare benefits to migrants and, 81–2, 282, 283, 284 Farnborough Sixth Form College, 294 Federal Reserve, 169–70, 176, 177, 183 Fees Act (1891), 128 Fertile Crescent, 106 feudalism, European, 53–4, 74, 104, 105 financial instruments, 103, 148, 157, 167–8 Financial Services and Markets Act (2001), 198 Financial Services Authority (FSA), 24, 147, 162, 178, 198–9, 208 financial system, British: see also capitalism; economy, British; Asian and/or OPEC capital surpluses and, 149, 154, 354; big finance as entrenched elite, 136, 137–8, 176, 178–80, 210, 387–9; declining support for entrepreneurship, 241; deregulation (1971), 161; fees and commissions, 33; importance of liquidity, 240, 243; lack of data on, 241; London/New York axis, 149, 150–1, 157–8, 160, 187, 202; massive growth of, 137, 138, 209, 219; need for tax reform, 209–10; regulation and see regulation; required reforms to companies, 249–50; savings institutions’ share holdings, 240–1; short termism of markets, 241, 242–3; unfairness of, 138, 210 Financial Times, 12, 149, 294, 330, 349, 361 Fink, Stanley, 179 fiscal policy, 208, 224–5, 226, 357–8, 364–9, 374; coalition rejection of, 370 fish stocks, conservation of, 394 Fitch (credit-rating agencies), 248 flexicurity social system, 299–301, 304, 374 Forbes’ annual list, 30 Ford, Henry, 195, 302 foreign exchange markets, 32, 161, 164, 165, 168, 363, 367; China’s rigged exchange rate, 36, 169, 355, 377, 378–9; currency options, 166, 191; eurozone, 377 foreign takeovers of British firms, 8, 388 Fortune magazine, 94 Foster, Sir Christopher, 313 foundation schools, 307 France, 51–2, 123–4, 163, 372, 375, 377 free trade, 163, 334, 379 Frey, Bruno, 60, 86 Friedman, Benjamin, 282–3 Fukuyama, Francis, 140 Fuld, Dick, 192 Future Jobs Fund, 373 G20 countries, 209, 358, 368, 374 Galliano, John, 143 Gardner, Howard, 274, 305–6 gated communities, 13 Gates, Bill, 71 Gates, Bill (Senior), 222 Gaussian distribution, 190–1, 194 ‘gearing’, 6 general election (6 May 2010), 97, 142, 179, 214, 217, 227, 234, 271, 314, 318, 327–8, 334, 378; Gillian Duffy incident, 394; result of, xi, 20, 345–6, 390 ‘generalised autoregressive conditional heteroskedasicity’ (GARCH), 194 genetically modified crops, 232 Germany, 36, 63, 244, 262, 269, 375–6, 379, 380; export led growth, 355–6, 375, 381–2; Fraunhofer Institutes, 252, 264; Greek bail-out and, 377; pre-1945 period, 128, 129, 134, 382, 383 Gieve, Sir John, 339–40 Gilligan, Andrew, 329 Gladwell, Malcolm, 76–7 Glasgow University, 323 Glass-Steagall Act, 162, 170, 202–3 Glastonbury festival, 143 globalisation, 32, 98, 140, 143, 144, 153–4, 163, 182, 297, 363, 366, 380 Goldman Sachs, 42, 63, 103, 150, 167–8, 174, 176, 177, 205 Goodwin, Sir Fred, 7, 150, 176, 340 Google, 131, 136, 253, 255, 258, 262 Goolsbee, Austin, 52 Gorbachev, Mikhail, 140 Gough, Ian, 79 Gould, Jay, 133 Gould, Philip, 142 government: see also democracy; political system, British; cabinet government, 312, 334, 337; centralisation of power, 14–15, 35, 217, 313, 334, 337, 341, 342; control of news agenda, 14, 224, 313; disregard of House of Commons, 14–15, 223, 339, 345; Number 10 Downing Street as new royal court, 14, 337, 338, 346, 347; press officers/secretaries, 14, 180, 224, 312; Prime Ministerial power, 337, 344, 345, 346 GPS navigation systems, 233, 265 Gray, Elisha, 221 Great Depression, 159, 162, 205, 362 Greece: classical, 25, 26, 38, 39, 44–5, 52–3, 59, 96, 107, 108; crisis and bail-out (2010), 167, 371, 377, 378 Green, Sir Philip, 12, 29, 33 Green Investment Bank, proposed, 252, 371 Greenhead College, Huddersfield, 294 Greenspan, Alan, 145–6, 165, 177, 183, 184, 197–8 Gregory, James, 277 growth, economic: Britain and, 9–10, 214–15, 219, 221, 359, 364; education and, 305–6; export led growth, 36, 169, 208, 226, 355–6, 375–7, 378–83; social investment and, 280–1 GSK, 219, 254 the Guardian, 319, 330, 349 Gupta, Sanjeev, 367 Gutenberg, Johannes, 110–11 Habsburg Empire, 127 Haines, Joe, 312 Haji-Ioannous, Stelios, 28 Haldane, Andrew, 8, 151, 153, 193, 214, 215 the Halifax, 186, 251 Hamilton, Lewis, 64, 65 Hammersmith and Fulham, Borough of, 167 Hampton, Sir Philip, 173 Hands, Guy, 28, 178, 246–8 Hanley, Lynsey, 291, 293, 302 Hanushek, Eric, 305–6 Hart, Betty, 289 Harvard University, 47, 62, 198 Hashimoto administration in Japan, 362 Hastings, Max, 217–18 Hauser, Marc, 47–50 Hawley, Michael, 65–6 Hayward, Tony, 216–17 HBOS, 157, 158, 178, 251 health and well-being, 9, 75, 77, 106, 232, 233, 290–1; see also National Health Service (NHS) Heckman, James, 290 hedge funds, 6, 21, 103, 157–8, 167–8, 172, 203, 205, 206, 240; collapses of, 152, 173–4, 187, 202; as destabilisers, 166–7, 168; destruction of ERM, 140, 144, 166; near collapse of LTCM, 169–70, 183, 193, 200–1 hedging, 164, 165–6 Heinz, Henry John, 302 Hermes fund management company, 242 Herrman, Edwina, 179 Herstatt Bank collapse, 152 Hetherington, Mark, 84 Hewitt, Patricia, 180 Hewlett-Packard, 30 Hills Report on social housing, 290 Hilton, Paris, 304 Himmelfarb, Gertrude, 146 Hirst, Damien, 12 history, economic, 121–36, 166, 285–6, 353–4 Hobhouse, Leonard, 220, 222, 234, 235, 261, 266 Hobsbawm, Eric, 100 Hoffman, Elizabeth, 60 Holland, 113, 124, 230 Honda, 91, 269 Hong Kong, 168 Hopkins, Harry, 300 Horton, Tim, 277 House of Commons, 14–15, 223, 312–13, 337–9, 345 House of Lords, 15, 128, 129, 312, 334, 344, 346–7 housing, social, 10, 289, 290–1, 292, 308–9 housing cost credits, 308–9 HSBC, 181, 251 Huhne, Chris, 346 Hunt family, sale of cattle herds, 201 Hurka, Thomas, 45–6 Hutton, Will, works of, x; The State We’re In, x, 148–9 IBM, 29, 164, 254 Iceland, 7, 138 ICT industry, 9, 29–30, 109, 134, 135–6, 182, 229 immigration, 11, 143, 326, 328, 342, 343, 386, 394; from Eastern Europe, 82, 281–2, 283; welfare state and, 81–2, 281–2, 283, 284 incapacity benefit, 27 the Independent, 93, 330 Independent Safeguarding Authority, 339 India, 144, 226, 230, 254, 354–5 individual responsibility, 17, 38, 39, 78–9 individualism, 54, 57, 66, 111, 221, 281, 341, 366; capitalism/free market theories and, ix, 17, 19, 27, 40, 145, 221, 234–5 Indonesia, 168 Industrial and Commercial Finance Corporation (now 3i), 250 industrial revolution, 28, 112, 115, 121–3, 124, 126–8, 130, 315 inflation, 6, 32, 355, 364, 365; targets, 163, 165, 208, 359 Ingham, Bernard, 312 innovation: see also entrepreneurs; national ecosystem of innovation; as collective and social, 40, 131, 219–22, 261, 265–6, 388; comparisons between countries, 67; competition and, 40, 114, 257–60; development times, 240, 243; discretionary effort and, 62, 65, 102–3, 105–6, 131, 222, 392–3; dissemination of knowledge and, 110–11, 112–13, 219–22, 265–6; due desert and, 40, 62, 67, 112, 117; ‘financial innovation’, 63–4, 138, 147, 149, 153–4, 182; general-purpose technologies (GPTs), 107–11, 112, 117, 126–7, 134, 228–9, 256, 261, 384; high taxation as deterrent, 104, 105; history of, 107–17, 121–7, 131–4, 221; increased pace of advance, 228–9, 230, 266–7; incremental, 108, 254, 256; incumbent elites and, 29–30, 104, 106, 109, 111–12, 113, 114, 115, 116, 257; large firms and, 251–2, 254–5; as natural to humans, 106–7, 274; need for network of specialist banks, 251–2, 265, 371; in ‘open-access societies’, 109–13, 114, 116–17, 122–3, 126–7, 131, 136, 315; patents and copyright, 102, 103, 105, 110, 260–1, 263; private enterprise and, 100–1; regulation and, 268–70; risk-taking and, 6, 103, 111, 189; short term investment culture and, 33, 242–3, 244; small firms and, 252, 253–4, 255–6; universities and, 261–5 Innovation Fund, 21, 251, 252 Institute of Fiscal Studies, 275–6, 363, 368–9, 372 Institute of Government, 334, 335, 337, 343 insurance, 165–6, 187, 240, 242 Intel, 255, 256 intellectual property, 260–1 interest rates, 164, 191, 352–3, 354, 357, 359, 360, 361, 362, 367, 380 internal combustion engine, 28, 109, 134 International Monetary Fund (IMF), 9, 152–3, 177–8, 187, 207, 226, 383, 384; Asian currency crisis (1997) and, 168–9; proposed bank levy and financial activities tax, 209; support for fiscal policy, 367 internet, 11, 28, 52, 109, 134, 227, 256, 265; news and politics on, 316–17, 321, 349; pay-walls, 316, 349; as threat to print media, 324, 331, 349 iPods, 105, 143 Iraq War, 14–15, 18, 36, 144, 329 Ireland, 138 iron steamships, 126 Islam, 352, 353 Islamic fundamentalism, 283, 384 Israel, 251, 322–3 Italy, 101, 103, 317, 328 ITN, 330, 331 James, Howell, 180 Japan, 36, 67, 140, 163, 168, 244, 369, 375, 376, 385, 386; credit crunch (1989-92), 359–60, 361–2, 382; debt levels, 356, 362, 363; incumbent elites in early twentieth-century, 134; Tokyo Bay, 254; Top Runner programme, 269 Jenkins, Roger, 296 Jobcentre Plus, 300 Jobs, Steve, 29–30, 65–6, 71 John Lewis Group, 66, 67, 93, 246 Johnson, Boris, 179 Johnson, Simon, 177 Jones, Tom, 242 Joseph Rowntree Foundation, 21, 278–9 journalism, 318–21, 323–4, 326–7 Jovanovic, Boyan, 256 JP Morgan, 169, 191–2, 195–6 judges, 15 justice systems, 30–1, 44–5, 49; symbolised by pair of scales, 4, 40 Kahneman, Daniel, 94–5 Kant, Immanuel, 73, 112, 274 Kay, John, 175 Kennedy, Helena, 340 Keynesian economics, x, xi, 184, 190, 196–7, 354, 362, 390–1 Kindleberger, Charles, 184 King, Mervyn, 213 Kinnock, Neil, 142 kitemarking, need for, 267 Klenow, Peter, 52 Knetsch, Jack, 94–5 Knight, Frank, Risk, Uncertainty and Profit (1921), 189, 191, 196–7 knowledge: capitalist advance of, 27–8, 31, 110–11, 112–13; public investment in learning, 28, 31, 40, 131, 220, 235, 261, 265 knowledge economy, 8, 11–12, 34, 135–6, 229–33, 258, 273–4, 341, 366; credit growth and, 355; graduate entry to, 295; large firms and, 251–2, 254–5; small firms and, 252, 253–4, 255–6, 261; state facilitation of, 219–22, 229–30 Koizumi administration in Japan, 362 Koo, Richard, 360, 361–2 Kuper, Simon, 352 Kwak, James, 64, 177 labour market, 52, 62, 83, 95; flexibility, 5, 275, 276, 299, 364–5, 387 laissez-faire ideology, 153, 198–9, 259 Laker, Freddie, 30 Lambert, Richard, 6–7 language acquisition and cognitive development, 288, 289 Large Hadron Collider, 263 Latin American debt crisis, 164 Lavoisier, Antoine, 31 Lazarus, Edmund, 179 Leahy, Sir Terry, 295 Learning and Skills Council, 282, 300 left wing politics, modern, 17, 38, 78–83 Lehman Brothers, 150, 152, 165, 170, 181, 192, 204 lender-of-last-resort function, 155, 158, 160, 187 Lerner, Melvin, 83 leverage, 6, 29, 154–6, 157, 158, 172, 179, 180, 198, 204, 209–10, 254, 363; disguised on balance sheet, 181, 195; effect on of credit crunches, 358, 359, 360, 361, 374–5; excess/massive levels, 7, 147–8, 149, 150–1, 158, 168, 170, 187, 192, 197, 203; need for reform of, 206, 207, 208; private equity and, 245–6, 247 Lewis, Jemima, 282, 287 Lewis, Joe, 12 libel laws, 332–3, 348–9 Liberal Democrats, xi, 11, 98, 141, 343, 360–1, 368; general election (2010) and, 97, 142, 179, 271, 390 libertarianism, 234 Likierman, Sir Andrew, 180 limited liability (introduced 1855), 353–4, 363 Lind, Allan, 85 Lindert, Peter, 280–1 Lipsey, Richard, 108, 263 Lisbon earthquake (1755), 54 Lisbon Treaty Constitution, 328 literacy and numeracy, 20–1 livestock fairs, pre-twentieth-century, 90 Lloyds Bank, 176, 178, 186, 202, 204, 251, 259 Lo, Andrew, 195 loan sharks, illegal, 291 local government, 307, 347–8 Locke, John, 54–5, 59 London School of Economics (LSE), 246 London Stock Exchange, 90, 162 London Underground, financing of, 336, 389 lone parent families, 292 Long Term Capital Management (LTCM), 169–70, 183, 193, 194, 200–1 long-term incentive plans (LTIPs), 6 Loomes, Graham, 59 luck, 23, 26–7, 38, 39, 40, 41, 67, 68, 69–77, 222, 273, 393–4; diplomacy/international relations and, 385–6; disadvantaged children and, 74–5, 83, 288–90; executive pay and, 138; taxation and, 73–4, 75, 78, 303 Luxembourg, 138 MacDonald, Ramsey, 315 Machiavelli, Niccolo, 62 Machin, Steve, 283–4 Macmillan Committee into City (1931), 179 Madoff, Bernie, 7 mafia, Italian, 101, 104–5 Major, John, 138, 180, 279, 334 Malaysia, 168 malls, out-of-town, 143 Mandelbrot, Benoit, 194, 195 Mandelson, Peter, 21, 24, 142, 148, 220 manufacturing sector, decline of, 5, 8, 219, 272, 292, 341, 363 Manza, Jeff, 281, 282 Marconi, 142–3 market fundamentalism, 9–19, 32–3, 40–2, 366; belief in efficiency of markets, 188–9, 190, 193, 194, 235–9, 366; coalition government (from May 2010) and, 370; collapse of, 3–4, 7–9, 19, 20, 219–20, 235, 392; Conservative Party and, 5, 17, 138, 147, 160, 161; domination of, 5–6, 14, 16–17, 163, 364–5, 387–90; likely resurgence of, 5, 8; New Labour and, x–xi, 5, 19, 144–9, 388, 389–90; post-communist fiasco in Russia, 135; rejection of fiscal policy, 224–5, 364–5, 367 mark-to-market accounting convention, 175 Marland, Lord Jonathan, 179 Marquand, David, 328 Marsh, Jodie, 64, 65 Marx, Karl, 56–8, 121–2 Maslow’s hierarchy of needs, 232, 274–5 mass production, 109, 134, 182 Masters, Blythe, 196 mathematical models (‘quants’), 105, 149, 151, 152, 165, 169, 188, 190–6, 203; extensions and elaborations, 194; Gaussian distribution, 190–1, 194; JP Morgan and, 195–6 Matthewson, Sir George (former chair of RBS), 25 Maude, Francis, 180 Mayhew, Henry, 285–6 McCartney, Paul, 247 McGoldrick, Mark, 174 McKinsey Global Institute, 253, 358–9, 360, 363 McQueen, Alexander, 143 media, mainstream, 6, 35, 312, 315–20, 321–32, 348–50; commoditisation of information, 318–20, 321; communications technology and, 316, 320, 349; domination of state by, 14, 16, 223–4, 338, 339, 343; fanatical anti-Europeanism, 15, 328, 378; foreign/tax exile ownership of, 218; hysterical tabloid campaigns, 10–11, 298, 319–20; ‘info-capitalism’, 317–18, 327, 328, 342; lauding of celebrity, 281, 314; modern 24/7 news agenda, 13, 224, 321, 343; regional newspapers, 331; as setter of agenda/narrative, 327–31, 342; television news, 330–1; undermining of democracy, 315–16, 317–18, 321–9, 333, 350; urgent need for reform, 35, 218, 344, 348–50, 391; view of poverty as deserved, 25, 53, 83, 281, 286; weakness of foreign coverage, 322, 323, 330 Mencken, H.L., 311 mergers and takeovers, 8, 21, 33, 92, 245, 251, 258, 259, 388 Merkel, Angela, 381–2 Merrill Lynch, 150, 170, 175, 192 Merton, Robert, 169, 191 Meucci, Antonnio, 221 Mexico, 30, 385 Meyer, Christopher, 332 Michalek, Richard, 175 Microsoft, 71, 114, 136, 253, 254, 258–9 Milburn, Alan, 273 Miles, David, 186–7 Milgram, Stanley, 200 millennium bug, 319 Miller, David, 70, 76, 77 minimum wage, 142, 278 Minsky, Hyman, 183, 185 Mirror newspapers, 319, 329 Mlodinow, Leonard, 72–3 MMR vaccine, 327 mobile phones, 30, 134, 143, 229, 349 modernity, 54–5, 104 Mokyr, Joel, 112 monarchy, 15, 312, 336 Mondragon, 94 monetary policy, 154, 182, 184, 185, 208, 362, 367 monopolies, 74, 102, 103, 160, 314; history of, 104, 113, 124, 125–6, 130–4; in the media, 30, 317, 318, 331, 350; modern new wave of, 35, 135–6, 137–8, 201–2, 258–9; ‘oligarchs’, 30, 65, 104 Monopolies and Mergers Commission, 258, 318 Moody’s (credit-ratings agency), 151, 175 morality, 16–27, 37, 44–54, 70, 73; see also desert, due, concept of; fairness; proportionality; debt and, 351–4, 357, 360–1 Morgan, JP, 67 Morgan, Piers, 329 Morgan Stanley, 150 Mulas-Granados, Carlos, 367 Murdoch, James, 389 Murdoch, Rupert, 317–18, 320, 327 Murphy, Kevin, 62, 63 Murray, Jim ‘Mad Dog’, 321 Myners, Paul, 340 Nash bargaining solution, 60 National Audit Office, 340 National Child Development Study, 289–90 national ecosystem of innovation, 33–4, 65, 103, 206, 218, 221, 239–44, 255–9, 374; state facilitation of, 102, 219–22, 229–30, 233, 251–2, 258–66, 269–70, 392 National Health Service (NHS), 21, 27, 34, 92, 265, 277, 336, 371–2; popular support for, 75, 77, 283 national insurance system, 81, 277, 302 national strategy for neighbourhood renewal, 278 Navigation Acts, abolition of, 126 Neiman, Susan, 18–19 neo-conservatism, 17–18, 144–9, 387–90 network theory, 199–201, 202–4, 206; Pareto curve and, 201–2 New Economics Foundation, 62 New Industry New Jobs strategy, 21 New Labour: budget deficit and, 224, 335, 360, 368, 369; business friendly/promarket policies, x–xi, 139–40, 142, 145, 146–7, 162, 198–9, 382; City of London and, x–xi, 5, 19, 22, 142–3, 144–5, 355; decline of class-based politics, 341; failure to challenge elites, x–xi, 14, 22, 388, 389–90; general election (1992) and, 138, 140–1, 144, 148, 277; general election (2005) and, 97; general election (2010) and, 20, 271, 334, 374, 378; light-touch regulation and, 138, 145, 146–7, 162, 198–9; New Industry New Jobs strategy, 21; one-off tax on bank bonuses, 26, 179, 249; record in government, 10–11, 19, 20–2, 220, 276–80, 302, 306, 334–6, 366–7, 389–90; reforms to by ‘modernisers’, 141; responses to newspaper campaigns, 11 New York markets, 140, 152, 162; Asian and/or OPEC capital surpluses and, 169, 171, 354; London/New York axis, 149, 150–1, 157–8, 160, 188, 202 Newsweek, 174 Newton, Isaac, 31, 127, 190 NHS Direct, 372 Nicoli, Eric, 13 non-executive directors (NEDs), 249–50 Nordhaus, William, 260 Nordic countries, 262; Iceland, 7, 138; Norway, 281; Sweden, 264, 281 North, Douglas, 113, 116, 129–30 Northern Rock, 9, 156, 157, 158, 186, 187–8, 202, 204, 251, 340–1 Norton Publishing, 93 Nozick, Robert, 234, 235 nuclear non-proliferation, 226, 384, 394 Nussbaum, Martha, 79 Obama, Barack, 18, 183, 380, 382–3, 394–5 the Observer, 141, 294, 327 Office for Budget Responsibility, 360 Office of Fair Trading (OFT), 257, 258 OFSTED, 276 oil production, 322; BP Gulf of Mexico disaster (2010), 216–17, 392; finite stocks and, 230, 384; OPEC, 149, 161, 171; price increase (early 1970s), 161; in USA, 130, 131, 132 Olsen, Ken, 29 Olympics (2012), 114 open markets, 29, 30, 31, 40, 89, 92, 100–1, 366, 377, 379, 382, 384; see also ‘open-access societies’; as determinants of value, 51–2, 62; fairness and, 60–1, 89–91, 94–6; ‘reference prices’ and, 94–6 ‘open-access societies’, 134, 135, 258, 272, 273, 275, 276, 280–1, 394; Britain as ‘open-access society’ (to 1850), 124, 126–7; democracy and, 136, 314; Enlightenment and, 30–1, 314–15, 394; innovation and invention in, 109–13, 114, 116–17, 122–3, 126–7, 131, 136, 315; partial political opening in, 129–30; US New Freedom programme, 132–3 opium production, 102 options, 166, 188, 191 Orange County derivatives losses, 167 Organisation for Economic Co-operation and Development (OECD), 180, 337, 373 Orwell, George, 37 Osborne, George, 147, 208, 224, 245, 302, 338 Overend, Gurney and Co., 156–7 Oxbridge/top university entry, 293–4, 306 Oxford University, 261 Page, Scott, 204 Paine, Tom, 347 Pareto, Vilfredo, 201–2 Paribas, 152, 187 Parkinson, Lance-Bombardier Ben, 13 participation, political, 35, 86, 96, 99 Paulson, Henry, 177 Paulson, John, 103, 167–8 pay of executives and bankers, 3–4, 5, 6–7, 22, 66–7, 138, 387; bonuses, 6, 25–6, 41, 174–5, 176, 179, 208, 242, 249, 388; high levels/rises of, 6–7, 13, 25, 82–3, 94, 172–6, 216, 296, 387, 393; Peter Mandelson on, 24; post-crash/bail-outs, 176, 216; in private equity houses, 248; remuneration committees, 6, 82, 83, 176; shared capitalism and, 66, 93; spurious justifications for, 42, 78, 82–3, 94, 176, 216 pension, state, 81, 372, 373 pension funds, 240, 242 Pettis, Michael, 379–80 pharmaceutical industry, 219, 255, 263, 265, 267–8 Phelps, Edmund, 275 philanthropy and charitable giving, 13, 25, 280 Philippines, 168 Philippon, Thomas, 172–3 Philips Electronics, Royal, 256 Pimco, 177 piracy, 101–2 Plato, 39, 44 Player, Gary, 76 pluralist state/society, x, 35, 99, 113, 233, 331, 350, 394 Poland, 67, 254 political parties, 13–14, 340, 341, 345, 390; see also under entries for individual parties political system, British: see also democracy; centralised constitution, 14–15, 35, 217, 334; coalitions as a good thing, 345–6; decline of class-based politics, 341; devolving of power to Cardiff and Edinburgh, 15, 334; expenses scandal, 3, 14, 217, 313, 341; history of (to late nineteenth-century), 124–30; lack of departmental coordination, 335, 336, 337; long-term policy making and, 217; monarchy and, 15, 312, 336; politicians’ lack of experience outside politics, 338; required reforms of, 344–8; select committee system, 339–40; settlement (of 1689), 125; sovereignty and, 223, 346, 347, 378; urgent need for reform, 35, 36–7, 218, 344; voter-politician disengagement, 217–18, 310, 311, 313–14, 340 Pommerehne, Werner, 60 population levels, world, 36 Portsmouth Football Club, 352 Portugal, 108, 109, 121, 377 poverty, 278–9; child development and, 288–90; circumstantial causes of, 26, 283–4; Conservative Party and, 279; ‘deserving’/’undeserving’ poor, 276, 277–8, 280, 284, 297, 301; Enlightenment views on, 53, 55–6; need for asset ownership, 301–3, 304; political left and, 78–83; the poor viewed as a race apart, 285–7; as relative not absolute, 55, 84; Adam Smith on, 55, 84; structure of market economy and, 78–9, 83; view that the poor deserve to be poor, 25, 52–3, 80, 83, 281, 285–8, 297, 301, 387; worldwide, 383, 384 Power2010 website, 340–1 PR companies and media, 322, 323 Press Complaints Commission (PCC), 325, 327, 331–2, 348 preventative medicine, 371 Price, Lance, 328, 340 Price, Mark, 93 Prince, Chuck, 184 printing press, 109, 110–11 prisoners, early release of, 11 private-equity firms, 6, 28–9, 158, 172, 177, 179, 205, 244–9, 374 Procter & Gamble, 167, 255 productive entrepreneurship, 6, 22–3, 28, 29–30, 33, 61–2, 63, 78, 84, 136, 298; in British history (to 1850), 28, 124, 126–7, 129; due desert/fairness and, 102–3, 105–6, 112, 223, 272, 393; general-purpose technologies (GPTs) and, 107–11, 112, 117, 126–7, 134, 228–9, 256, 261, 384 property market: baby boomer generation and, 372–3; Barker Review, 185; boom in, 5, 143, 161, 183–4, 185–7, 221; bust (1989-91), 161, 163; buy-to-let market, 186; commercial property, 7, 356, 359, 363; demutualisation of building societies, 156, 186; deregulation (1971) and, 161; Japanese crunch (1989-92) and, 361–2; need for tax on profits from home ownership, 308–9, 373–4; property as national obsession, 187; residential mortgages, 7, 183–4, 186, 356, 359, 363; securitised loans based mortgages, 171, 186, 188; shadow banking system and, 171, 172; ‘subprime’ mortgages, 64, 152, 161, 186, 203 proportionality, 4, 24, 26, 35, 38, 39–40, 44–6, 51, 84, 218; see also desert, due, concept of; contributory/discretionary benefits and, 63; diplomacy/ international relations and, 385–6; job seeker’s allowance as transgression of, 81; left wing politics and, 80; luck and, 73–7, 273; policy responses to crash and, 215–16; poverty relief systems and, 80–1; profit and, 40, 388; types of entrepreneurship and, 61–2, 63 protectionism, 36, 358, 376–7, 378, 379, 382, 386 Prussia, 128 Public Accounts Committee, 340 Purnell, James, 338 quantitative easing, 176 Quayle, Dan, 177 race, disadvantage and, 290 railways, 9, 28, 105, 109–10, 126 Rand, Ayn, 145, 234 Rawls, John, 57, 58, 63, 73, 78 Reagan, Ronald, 135, 163 recession, xi, 3, 8, 9, 138, 153, 210, 223, 335; of 1979-81 period, 161; efficacy of fiscal policy, 367–8; VAT decrease (2009) and, 366–7 reciprocity, 43, 45, 82, 86, 90, 143, 271, 304, 382; see also desert, due, concept of; proportionality Reckitt Benckiser, 82–3 Regional Development Agencies, 21 regulation: see also Bank of England; Financial Services Authority (FSA); Bank of International Settlements (BIS), 169, 182; Basel system, 158, 160, 163, 169, 170–1, 196, 385; big as beautiful in global banking, 201–2; Big Bang (1986), 90, 162; by-passing of, 137, 187; capital requirements/ratios, 162–3, 170–1, 208; dismantling of post-war system, 149, 158, 159–63; economists’ doubts over deregulation, 163; example of China, 160; failure to prevent crash, 154, 197, 198–9; Glass-Steagall abolition (1999), 170, 202–3; light-touch, 5, 32, 138, 151, 162, 198–9; New Deal rules (1930s), 159, 162; in pharmaceutical industry, 267–8; as pro-business tool, 268–70; proposed Financial Policy Committee, 208; required reforms of, 267, 269–70, 376, 377, 384, 392; reserve requirements scrapped (1979), 208; task of banking authorities, 157; Top Runner programme in Japan, 269 Reinhart, Carmen, 214, 356 Repo 105 technique, 181 Reshef, Ariell, 172–3 Reuters, 322, 331 riches and wealth, 11–13, 272–3, 283–4, 387–8; see also pay of executives and bankers; the rich as deserving of their wealth, 25–6, 52, 278, 296–7 Rickards, James, 194 risk, 149, 158, 165, 298–302, 352–3; credit default swaps and, 151, 152, 166–8, 170, 171, 175, 176, 191, 203, 207; derivatives and see derivatives; distinction between uncertainty and, 189–90, 191, 192–3, 196–7; employment insurance concept, 298–9, 301, 374; management, 165, 170, 171, 189, 191–2, 193–4, 195–6, 202, 203, 210, 354; securitisation and, 32, 147, 165, 169, 171, 186, 188, 196; structured investment vehicles and, 151, 165, 169, 171, 188; value at risk (VaR), 171, 192, 195, 196 Risley, Todd, 289 Ritchie, Andrew, 103 Ritter, Scott, 329 Robinson, Sir Gerry, 295 Rogoff, Ken, 214, 356 rogue states, 36 Rolling Stones, 247 Rolls-Royce, 219, 231 Rome, classical, 45, 74, 108, 116 Roosevelt, Franklin D., 133, 300 Rothermere, Viscount, 327 Rousseau, Jean-Jacques, 56, 58, 112 Rousseau, Peter, 256 Rowling, J.K., 64, 65 Rowthorn, Robert, 292, 363 Royal Bank of Scotland (RBS), 25, 150, 152, 157, 173, 181, 199, 251, 259; collapse of, 7, 137, 150, 158, 175–6, 202, 203, 204; Sir Fred Goodwin and, 7, 150, 176, 340 Rubin, Robert, 174, 177, 183 rule of law, x, 4, 220, 235 Russell, Bertrand, 189 Russia, 127, 134–5, 169, 201, 354–5, 385; fall of communism, 135, 140; oligarchs, 30, 65, 135 Rwandan genocide, 71 Ryanair, 233 sailing ships, three-masted, 108 Sandbrook, Dominic, 22 Sands, Peter (CEO of Standard Chartered Bank), 26 Sarkozy, Nicolas, 51, 377 Sassoon, Sir James, 178 Scholes, Myron, 169, 191, 193 Schumpeter, Joseph, 62, 67, 111 science and technology: capitalist dynamism and, 27–8, 31, 112–13; digitalisation, 34, 231, 320, 349, 350; the Enlightenment and, 31, 108–9, 112–13, 116–17, 121, 126–7; general-purpose technologies (GPTs), 107–11, 112, 117, 126–7, 134, 228–9, 256, 261, 384; increased pace of advance, 228–9, 253, 297; nanotechnology, 232; New Labour improvements, 21; new opportunities and, 33–4, 228–9, 231–3; new technologies, 232, 233, 240; universities and, 261–5 Scotland, devolving of power to, 15, 334 Scott, James, 114–15 Scott Bader, 93 Scott Trust, 327 Second World War, 134, 313 Securities and Exchanges Commission, 151, 167–8 securitisation, 32, 147, 165, 169, 171, 186, 187, 196 self-determination, 85–6 self-employment, 86 self-interest, 59, 60, 78 Sen, Amartya, 51, 232, 275 service sector, 8, 291, 341, 355 shadow banking system, 148, 153, 157–8, 170, 171, 172, 187 Shakespeare, William, 39, 274, 351 shareholders, 156, 197, 216–17, 240–4, 250 Sher, George, 46, 50, 51 Sherman Act (USA, 1890), 133 Sherraden, Michael, 301 Shiller, Robert, 43, 298, 299 Shimer, Robert, 299 Shleifer, Andrei, 62, 63, 92 short selling, 103 Sicilian mafia, 101, 105 Simon, Herbert, 222 Simpson, George, 142–3 single mothers, 17, 53, 287 sixth form education, 306 Sky (broadcasting company), 30, 318, 330, 389 Skype, 253 Slim, Carlos, 30 Sloan School of Management, 195 Slumdog Millionaire, 283 Smith, Adam, 55, 84, 104, 112, 121, 122, 126, 145–6 Smith, John, 148 Snoddy, Ray, 322 Snow, John, 177 social capital, 88–9, 92 social class, 78, 130, 230, 304, 343, 388; childcare and, 278, 288–90; continued importance of, 271, 283–96; decline of class-based politics, 341; education and, 13, 17, 223, 264–5, 272–3, 274, 276, 292–5, 304, 308; historical development of, 56–8, 109, 115–16, 122, 123–5, 127–8, 199; New Labour and, 271, 277–9; working-class opinion, 16, 143 social investment, 10, 19, 20–1, 279, 280–1 social polarisation, 9–16, 34–5, 223, 271–4, 282–5, 286–97, 342; Conservative reforms (1979-97) and, 275–6; New Labour and, 277–9; private education and, 13, 223, 264–5, 272–3, 276, 283–4, 293–5, 304; required reforms for reduction of, 297–309 social security benefits, 277, 278, 299–301, 328; contributory, 63, 81, 283; flexicurity social system, 299–301, 304, 374; to immigrants, 81–2, 282, 283, 284; job seeker’s allowance, 81, 281, 298, 301; New Labour and ‘undeserving’ claimants, 143, 277–8; non-contributory, 63, 79, 81, 82; targeting of/two-tier system, 277, 281 socialism, 22, 32, 38, 75, 138, 144, 145, 394 Soham murder case, 10, 339 Solomon Brothers, 173 Sony, 254–5 Soros, George, 166 Sorrell, Martin, 349 Soskice, David, 342–3 South Korea, 168, 358–9 South Sea Bubble, 125–6 Spain, 123–4, 207, 358–9, 371, 377 Spamann, Holger, 198 special purpose vehicles, 181 Spitzer, Matthew, 60 sport, cheating in, 23 stakeholder capitalism, x, 148–9 Standard Oil, 130–1, 132 state, British: anti-statism, 20, 22, 233–4, 235, 311; big finance’s penetration of, 176, 178–80; ‘choice architecture’ and, 238, 252; desired level of involvement, 234–5; domination of by media, 14, 16, 221, 338, 339, 343; facilitation of fairness, ix–x, 391–2, 394–5; investment in knowledge, 28, 31, 40, 220, 235, 261, 265; need for government as employer of last resort, 300; need for hybrid financial system, 244, 249–52; need for intervention in markets, 219–22, 229–30, 235–9, 252, 392; need for reshaping of, 34; pluralism, x, 35, 99, 113, 233, 331, 350, 394; public ownership, 32, 240; target-setting in, 91–2; threats to civil liberty and, 340 steam engine, 110, 126 Steinmueller, W.

Breaking News: The Remaking of Journalism and Why It Matters Now by Alan Rusbridger

"World Economic Forum" Davos, accounting loophole / creative accounting, Airbnb, Andy Carvin, banking crisis, Bellingcat, Bernie Sanders, Bletchley Park, Boris Johnson, Brexit referendum, Cambridge Analytica, centre right, Chelsea Manning, citizen journalism, country house hotel, cross-subsidies, crowdsourcing, data science, David Attenborough, David Brooks, death of newspapers, Donald Trump, Doomsday Book, Double Irish / Dutch Sandwich, Downton Abbey, Edward Snowden, Etonian, Evgeny Morozov, fake news, Filter Bubble, folksonomy, forensic accounting, Frank Gehry, future of journalism, G4S, high net worth, information security, invention of movable type, invention of the printing press, Jeff Bezos, jimmy wales, Julian Assange, Large Hadron Collider, Laura Poitras, Mark Zuckerberg, Mary Meeker, Menlo Park, natural language processing, New Journalism, offshore financial centre, oil shale / tar sands, open borders, packet switching, Panopticon Jeremy Bentham, post-truth, pre–internet, ransomware, recommendation engine, Ruby on Rails, sexual politics, Silicon Valley, Skype, Snapchat, social web, Socratic dialogue, sovereign wealth fund, speech recognition, Steve Bannon, Steve Jobs, the long tail, The Wisdom of Crowds, Tim Cook: Apple, traveling salesman, upwardly mobile, WikiLeaks, Yochai Benkler

Around the turn of the century it was hard not to feel an immense sense of excitement at what was soon to be possible, and soon to be discovered – from microscope technology; gene sequencing tools; image sensors on telescopes; ways to tag cells in living organisms; superconducting magnet technology; computing power and tools for handling massive datasets. The Human Genome Project had laid the foundations for a genuine understanding of how humans work on the molecular scale. The Large Hadron Collider was under construction at CERN. We were seeing for the first time the afterglow of the big bang, that relic radiation from the birth of the universe, imprinted on the sky. All this was on the cards at the start of the twenty-first century: we knew it was coming. There was an awful lot to tell people about.

…

Joseph ref1 Canary Wharf ref1, ref2, ref3 Canonbury ref1 Carlson, Tucker ref1 Carman, George (QC) ref1, ref2, ref3, ref4n Carney, Mark ref1 Carter, Graydon ref1 Carter-Ruck lawyers ref1 Carvin, Andy ref1 Catch Me If You Can (film) ref1 Caulfield, Mr Justice ref1 Cecil, Lord Robert ref1 censorship ref1, ref2, ref3 CERN ref1 challenge ref1, ref2, ref3, ref4 Champaign News Gazette (newspaper) ref1, ref2 Channel 4 (TV) ref1, ref2 Chaos Monkeys (Martínez) ref1, ref2 Chapman, Jessica ref1 charity ref1 Charles, Prince ref1 Chartbeat ref1 Chehadé, Fadi ref1 Chernin, Peter ref1 Chicago Online ref1 Chicago Sun-Times (news-paper) ref1 Chicago Tribune (newspaper) ref1, ref2 China ref1, ref2, ref3, ref4 Chippendale, Peter ref1 Chomsky, Noam ref1, ref2 Churchill, Prime Minister Sir Winston ref1, ref2, ref3 ‘churnalism’ ref1, ref2 CIA ref1 CiF (Comment is Free) ref1, ref2 CiF Belief ref1, ref2n circulation ref1, ref2, ref3 passim, ref1, ref2, ref3, ref4n bulk sales ref1, ref2, ref3, ref4, ref5, ref6, ref7n, ref8n decline ref1, ref2, ref3, ref4, ref5 gains ref1, ref2, ref3, ref4 international ref1, ref2, ref3, ref4, ref5 citizen journalists (stringers) ref1, ref2 Citizen Kane (film) ref1 City of London ref1 City University of New York (CUNY) ref1 Clapper, James ref1, ref2 Claridge’s hotel ref1, ref2 classified material ref1, ref2, ref3 Clegg, Nick (MP) ref1, ref2, ref3, ref4 Clerkenwell ref1 ‘click-through rate’ (CTR) ref1 clickbait ref1, ref2 climate change ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10n Clinton, President Bill ref1, ref2, ref3, ref4 Clinton, Hillary ref1, ref2, ref3, ref4, ref5 Clooney, George ref1 Cobain, Ian ref1 Cobbet, William ref1 Code of Practice ref1 Coile, Peter ref1 Colao, Vittori ref1 colour ref1, ref2, ref3, ref4, ref5, ref6n Colvin, Marie ref1 Comey, James ref1 Committee of Imperial Defence (UK) ref1 Committee to Protect Journalists (CPJ) ref1, ref2n ‘commodity news’ ref1 Common Purpose ref1 complexity ref1, ref2, ref3, ref4 composing room ref1, ref2 ComScore ref1, ref2n concentration camps ref1 Conn, David ref1 consent ref1 Conservative Party ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12, ref13 content management system ref1, ref2 convergence ref1 Coogan, Steve ref1 Cook, Tim ref1 Corn, David ref1 correction ref1, ref2 corruption ref1, ref2, ref3, ref4, ref5, ref6, ref7 Coulson, Andy ref1, ref2, ref3, ref4 Cox, Jo (MP) ref1 Craigslist ref1, ref2 The Creation of the Media (Starr) ref1 cricket ref1 Crossman, Richard ref1 crowdfunding ref1 crowdsourcing ref1, ref2, ref3, ref4, ref5, ref6 Crown Prosecution Service ref1, ref2 Crowther, Geoffrey ref1 Culture Media & Sports committee (UK) ref1 CUNY ref1 CVs ref1, ref2 cybercrime ref1 cyberspace ref1 Dacre, Paul ref1, ref2, ref3n, ref4n Dagens Nyheter (newspaper) ref1, ref2 Daily Dish ref1 Daily (iPad newspaper) ref1 Daily Mail & General Trust ref1 Daily News (newspaper) ref1 Daily Sketch (newspaper) ref1 Dangerous Estate (Williams) ref1 Danks, Melanie ref1, ref2 Danny (IT expert) ref1 data ref1, ref2, ref3, ref4, ref5 Davies, Nick ref1, ref2, ref3, ref4, ref5, ref6 passim, ref1, ref2, ref3, ref4n, ref5n Davis, David (MP) ref1, ref2 Dayton Ohio peace accord ref1 De Correspondent ref1, ref2 de Tocqueville, Alexis ref1 ‘dead-tree journalism’ ref1, ref2 Deadline (film) ref1 deadlines ref1 Dean, Malcolm ref1n ‘death knock’ ref1 Deedes, Lord Bill ref1, ref2 Deedes, Jeremy ref1 Deepwater Horizon ref1 defamation ref1, ref2 Defence Advisory (DA) Notice system ref1, ref2, ref3 deference ref1 Defoe, Daniel ref1, ref2 Delane, John ref1, ref2 Delaunay hotel ref1, ref2 Delingpole, James ref1, ref2 Deller, Jeremy ref1 democracy ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12, ref13 Democratic National Committee (DNC) ref1, ref2 Department of Justice (US) ref1 Der Spiegel (magazine) ref1, ref2, ref3 Desmond, Richard ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8n Despicable Me (film) ref1 Dewey, John ref1, ref2, ref3, ref4n Diamond, Bob ref1 Diana, Princess ref1 Diawara, Fatoumata ref1 Dickens, Charles ref1, ref2 Die Zeit (newspaper) ref1 Digg ref1 ‘Digital News Report’ (RISJ) ref1 Dixon, Hugo ref1 Dixon, Jeremy ref1, ref2n docu-tainment ref1, ref2 donations ref1, ref2 doorstep reporting ref1, ref2, ref3 Dorsey, Jack ref1 dot.com bubble ref1 Dowler, Milly ref1, ref2n Downie, Len ref1n Downing Street ref1, ref2 drinks culture ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10 Drudge ref1 drugs ref1, ref2, ref3, ref4 duty ref1, ref2, ref3, ref4, ref5, ref6 DVDs ref1 Dworkin, Ronald ref1, ref2 eBay ref1, ref2, ref3 Economist (magazine) ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Edelman Trust Barometer ref1n Edison, Thomas ref1 editorials ref1, ref2, ref3 Edmondson, Ian ref1 education ref1, ref2 Eisenstein, Elizabeth L. ref1 El País (newspaper) ref1, ref2, ref3, ref4 election (US 2016) ref1, ref2, ref3, ref4 Electoral Commission ref1 electric cars ref1 Electronic Information Service ref1 The Elements of Journalism (Kovach/Rosenstiel) ref1 Elizabeth II, Queen ref1 Ellingham Hall (Suffolk) ref1 Ellis, Michael (MP) ref1 Ellison, Sarah ref1 Ellsberg, Daniel ref1 Emap ref1 eMarketer ref1 Enders Analysis ref1, ref2, ref3, ref4 endowment ref1, ref2, ref3, ref4, ref5, ref6, ref7n Engelberg, Steve ref1 The Enlightenment ref1, ref2 Enron ref1 environment ref1, ref2, ref3, ref4, ref5 Enzensberger, Hans-Magnus ref1 Ernst & Young ref1 Espionage Act (1917) ref1 EternalBlue ref1n Euromyth ref1 Europe ref1, ref2, ref3, ref4, ref5 European Commission (EC) ref1 European Convention on Human Rights ref1, ref2 European Court of Human Rights (ECHR) ref1 European Court of Justice (ECJ) ref1, ref2, ref3 European (newspaper) ref1, ref2 European Union (EU) ref1, ref2, ref3, ref4, ref5 Euston Project ref1 Evans, Sir Harold ref1, ref2, ref3 Evans, Rob ref1, ref2 Evans, Timothy ref1, ref2n experimentation ref1, ref2, ref3, ref4, ref5 Facebook ref1, ref2, ref3, ref4 passim, ref1, ref2, ref3 passim, ref1, ref2 passim, ref1 passim, ref1 facts ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12, ref13, ref14 Fahrenthold, David ref1 Fairfax Media ref1, ref2, ref3 fake news see under falsehood Falconer, Lord ref1 Falkirk Herald (newspaper) ref1, ref2 falsehood ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11 fake news ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12 passim lies ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Farage, Nigel ref1, ref2 Farrar, Jeremy ref1 Farringdon Road ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10 FBI ref1, ref2, ref3, ref4 FedEx conditions of carriage ref1 Fedorcio, Dick ref1 Feinstein, Senator Diane ref1 female genital mutilation ref1, ref2 Ferguson, Niall ref1 Ferrer, Albert ref1 Fidler, Roger ref1 The Fifth Estate (film) ref1, ref2n Filloux, Frederic ref1 filter bubbles ref1, ref2, ref3, ref4, ref5, ref6 First Amendment (US) ref1, ref2, ref3, ref4n Fish4jobs ref1 Fitzsimons, Sheila ref1n, ref2n Flat Earth News (Davies) ref1 Fleet Street ref1, ref2, ref3, ref4, ref5 Flickr ref1, ref2, ref3 Folwell, Steve ref1 food production ref1, ref2 Forbes (magazine) ref1 Ford, John ref1, ref2 foreign correspondents ref1, ref2, ref3, ref4, ref5, ref6 Foreign Corrupt Practices Act (US 1977) ref1 Foreign Intelligence Surveillance Act (FISA) courts ref1 Foreign Office ref1 Forgan, Liz ref1, ref2 fossil fuels ref1 Fourth Estate ref1 Fox TV ref1, ref2, ref3, ref4, ref5, ref6, ref6 Frankel, Max ref1 Frankfurter Allgemeine Zeitung (newspaper) ref1 free newspapers ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 free press ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 free speech ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 freebies ref1, ref2, ref3 Freedland, Jonathan ref1, ref2 Freedom Act (2015) ref1 Friedman, Thomas ref1 Friendly, Fred ref1 G4S security guards ref1, ref2n G-20 protests (2009) ref1 Gaddafi, Muammar ref1 GAFAT companies ref1, ref2 Gallagher, Tony ref1 Gaskell, John ref1 Gates, Bill ref1 GCHQ ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8n Geary, Joanna ref1 Gehry, Frank ref1 Gellman, Barton ref1 Gentleman, Amelia ref1 George III, King ref1 germ (virus) ref1 Germany ref1, ref2 Gibson, Janine ref1, ref2, ref3, ref4, ref5, ref6, ref7 Gillespie, Fulton ref1 Gillmor, Dan ref1, ref2, ref3n Glaxo Smith Kline (GSK) ref1 Gledhill, Ruth ref1 Glocer, Tom ref1 Glover, Stephen ref1, ref2, ref3n, ref4n Goldacre, Ben ref1, ref2n Goldman, William ref1, ref2 Goldman Sachs ref1, ref2 Good, Jennifer ref1 Goodale, James ref1 Goodman, Clive ref1, ref2 Goodman, Elinor ref1 Google ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12 passim, ref1, ref2 Goranzon, Anders ref1 Gordon, David ref1, ref2, ref3n Gordon, Michael ref1 Gore, Vice President Al ref1 Gorwa, Robert ref1 Gove, Michael ref1 Gowers, Andrew ref1 Graham, Don ref1, ref2 Graham, James ref1 Graham, Katherine (Kay) ref1, ref2, ref3 Granada TV ref1, ref2 Grant, Hugh ref1 Gray, Charles (QC) ref1, ref2, ref3n Great Barrier Reef ref1 Great Integration ref1 Greenslade, Roy ref1, ref2, ref3n Greenwald, Glenn ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Greer, Ian ref1 Guardian Australia ref1 Guardian Cities ref1 Guardian Media Group (GMG) ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11n, ref12n Board ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8n, ref9n Guardian News and Media (GNM) ref1, ref2n Guardian Unlimited ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10n Gulliver, Stuart ref1, ref2 gun control ref1 Gurfein, Judge Murray ref1 GUS retail group ref1 Gutenberg, Johannes ref1, ref2, ref3, ref4 Haaretz (newspaper) ref1 Hack Attack (Davies) ref1, ref2 Hacked Off ref1 Hagel, John ref1 Haig, General Al ref1, ref2 Hamilton, Neil (MP) ref1, ref2, ref3n Hankey, Sir Maurice ref1 Hanks, Tom ref1 Hansard ref1, ref2 hard knocks, school of ref1, ref2 Harding, James ref1 Harford, Tim ref1 Harlow Technical College ref1 Harris, Wendy ref1 Hartwell, Lord ref1 Hastings, Max ref1, ref2, ref3n Hayden, Michael V. ref1 Hayden, Teresa Nielsen ref1 Hayley, Sir William ref1 Hazlitt, William ref1, ref2 Hearst, William Randolph ref1, ref2 Henry, Georgina ref1, ref2 Henry Jackson Society ref1 Herald Sun (newspaper) ref1 Here Comes Everybody (Shirky) ref1 Hetherington, Alistair ref1, ref2 Hewlett, Steve ref1 Heywood, Jeremy ref1, ref2 Higgins, Eliot ref1 High Court ref1, ref2, ref3, ref4 Hillsborough disaster (1989) ref1, ref2, ref3n Hinton, Les ref1, ref2, ref3, ref4 Hirsch, Fred ref1, ref2, ref3n Hislop, Ian ref1 HMRC ref1 Hoare, Sean ref1, ref2 Hodgson, Godfrey ref1 Hoffman, Dustin ref1, ref2 Hoffman, Reid ref1, ref2 Holder, Eric ref1 Hollywood ref1 Home Affairs committee (UK) ref1 Home Office ref1 The Home Organist (magazine) ref1 Hong Kong ref1 Hooper, David ref1 Hopkins, Nick ref1 Horowitz, Ami ref1 Horrie, Chris ref1 Hotel Bristol (Villars) ref1, ref2 HotWired ref1 House of Commons ref1, ref2, ref3, ref4 House of Lords ref1, ref2 Houston, Robin ref1 How to Spend It (magazine) ref1 HSBC ref1, ref2, ref3 Huffington, Arianna ref1, ref2n Huffington, Michael ref1 Huffington Post ref1, ref2, ref3, ref4, ref5n Human Genome Project ref1 Human Rights Act (1998) ref1, ref2, ref3, ref4n Humanity United ref1 Hunt, Henry ref1 Hutton report (2004) ref1 ‘idea agora’ ref1 i-escape ref1 Iliffe of Yattendon, Lord ref1 Imanuelsen, Peter ref1 immigration ref1, ref2, ref3, ref4, ref5, ref6n Independent Press Standards Organisation (IPSO) ref1, ref2, ref3, ref4 Independent on Sunday (newspaper) ref1 Indonesia ref1 InFacts ref1 ‘influence model’ ref1 Infomediary ref1 information chaos ref1, ref2, ref3, ref4, ref5, ref6 Information Commissioner’s Office (ICO) ref1 ‘information superhighway’ ref1, ref2, ref3 Ingrams, Richard ref1 injunctions ref1, ref2, ref3, ref4, ref5 Ink (Graham) ref1 Inkster, Nigel ref1 ‘innovation blindness’ ref1 Instagram ref1 integrated model ref1 integrity ref1 Intelligence Community programmes (US) ref1 ‘intelligence porn’ ref1 Intelligence and Security committee (UK) ref1, ref2 Intercept ref1 The Internet for Dummies (series) ref1 Internet Explorer ref1 intrusion ref1 investigative journalism ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10n Investigatory Powers Act (2016) (UK) ref1 Investigatory Powers Tribunal (IPT) (UK) ref1, ref2 ‘invisible mending’ ref1 iPad ref1, ref2, ref3, ref4 iPhone ref1, ref2 iPlayer ref1 IRA ref1, ref2 Iran ref1, ref2 Iraq wars ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Ireland ref1 Irish Independent (newspaper) ref1, ref2 Irish Times (newspaper) ref1 Irons, Jeremy ref1 Isaacson, Walter ref1 iTunes ref1 ITV ref1, ref2 James, Clive ref1 James, Erwin ref1 Jarvis, Jeff ref1, ref2, ref3 Jay, Peter ref1 Jenkins, Simon ref1, ref2 Jersey ref1 Jobs, Steve ref1 Johnson, Boris (MP) ref1, ref2 Johnson, Graham ref1 Johnston Press Ltd ref1n Jonathan of Arabia (TV) ref1 Jones, George ref1 Joseph Rowntree Foundation ref1 journalism accountability ref1, ref2 dead-tree ref1, ref2 investigative ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10n seven deadly sins ref1n traditional ref1, ref2, ref3, ref4, ref5 training ref1, ref2, ref3, ref4 Jowell, Tessa ref1 Judicial Redress Act (2016) ref1 Junius ref1 ‘junk news’ ref1 Jupiter Research ref1 Kaplan Educational publishing ref1 Katine (Uganda) ref1 Katz, Ian ref1, ref2, ref3, ref4, ref5, ref6n Kaufer, Stephen ref1 Keller, Bill ref1, ref2, ref3 Kelner, Simon ref1, ref2, ref3, ref4, ref5n Kenya ref1, ref2 ‘keyword pages’ ref1 Khatchadourian, Raffi ref1 King, Dave ref1, ref2 King’s College, London ref1 Kings Place offices ref1, ref2, ref3, ref4, ref5 Kinsley, Michael ref1 Kirwan, Peter ref1 Knight Ridder ref1, ref2 Knopfler, Mark ref1 Kovach, Bill ref1 Krauze, Andre ref1 Kushner, Jared ref1 La Repubblica (newspaper) ref1 Laborde, Jean-Paul ref1 Labour Party ref1, ref2, ref3, ref4, ref5, ref6, ref7 Lamb, Larry ref1 Lambert, Richard ref1 Lanchester, John ref1, ref2 Large Hadron Collider ref1 Larson, Jeff ref1 Law Commission (UK) ref1 Lawrence, Felicity ref1 Lawson, Dominic ref1 lawyers ref1n Le Monde (newspaper) ref1, ref2 Leave campaign group ref1 Lebedev, Alexander ref1, ref2n Lebedev, Evgeny ref1n legacy media ref1 legality ref1 Lehman Brothers ref1, ref2 Leigh, David ref1, ref2 Leipzig, mayor of ref1 Lelyveld, Joseph ref1 Leonard, Joe ref1 letters ref1, ref2, ref3, ref4, ref5 newsletters ref1, ref2, ref3 readers’ ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 Leveson, Lord Justice Brian ref1, ref2, ref3n Leveson Inquiry ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8n Levin, Bernard ref1, ref2n Lewinsky, Monica ref1 Lewis, Paul ref1, ref2, ref3 Lewis, Will ref1 libel actions ref1, ref2, ref3, ref4, ref5, ref6, ref7n, ref8n, ref9n libel laws ref1, ref2 Liberal Democrat party ref1, ref2 Liberty ref1 Liberty and Security in a Changing World (2013 report) ref1 lies see under falsehood lighthouse model ref1, ref2 LinkedIn ref1, ref2, ref3 links ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10n Linotype machine ref1, ref2, ref3 Linux ref1 Lippmann, Walter ref1 Littlewoods ref1 Lloyd, John ref1 Lloyds Bank ref1 Local Government Act (1972) ref1 Local World Ltd ref1, ref2, ref3n London Daily News (newspaper) ref1 London Evening Standard (newspaper) ref1 London Review of Books ref1, ref2 London School of Economics ref1n Lonely Planet ref1 ‘long tail’, theory of ref1 Los Angeles Times (newspaper) ref1, ref2, ref3, ref4 Lowry, L.S. ref1, ref2n loyalty scheme ref1 Ludgate Circus ref1 Ludlow machine ref1, ref2 Luxx (magazine) ref1 Luyendijk, Joris ref1 MacAskill, Ewen ref1, ref2, ref3 McCabe, Douglas ref1 McCabe, Eamonn ref1 McCain, John ref1 McCall, Carolyn ref1, ref2, ref3 Macedonia ref1 MacKenzie, Kelvin ref1 McKibben, Bill ref1, ref2 McKillen, Paddy ref1 McKinsey & Co ref1, ref2, ref3, ref4 MacLennan, Murdoch ref1, ref2, ref3, ref4, ref5, ref6n Macron, President Emmanuel ref1 MacroWikinomics (Tapscott) ref1 MacTaggart lecture (2009) ref1 Mail Online ref1, ref2, ref3 Mainstream Media (MSM) ref1, ref2, ref3 Major, Prime Minister John ref1 The Making of the English Working Class (Thompson) ref1 Malmo ref1 Manchester Evening News (MEN) (newspaper) ref1, ref2, ref3, ref4n Manchester Guardian (newspaper) ref1, ref2, ref3, ref4 Mandelson, Peter (MP) ref1 Manning, Chelsea ref1, ref2, ref3 Marks, Vic ref1 Marland, Caroline ref1 ‘marmalade dropper’ ref1, ref2n Martínez, Antonio García ref1, ref2 Mashable ref1, ref2 ‘The Masque of Anarchy’ (poem) ref1 Massachusetts Institute of Technology ref1 Match.com ref1 Mauro, Ezio ref1 Maxwell, Robert ref1, ref2, ref3, ref4, ref5, ref6n May Corporation Ltd ref1 May, Prime Minister Theresa ref1, ref2, ref3 Mayes, Ian ref1, ref2 Mead/Lexis ref1 Medejski, John ref1 Media Guardian ref1 media law ref1 media section ref1 Media Show (radio) ref1 Media Standards Trust (MST) ref1 Meeker, Mary ref1 Melbourne, Florida ref1, ref2 Merkel, Chancellor Angela ref1 Metcalfe, Jane ref1 metrics ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Metro (newspaper) ref1, ref2, ref3n Meyer, Philip ref1, ref2 MI5 ref1, ref2, ref3, ref4, ref5, ref6n MI6 ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8n Miami Herald (newspaper) ref1 Michelin tyres ref1 Microsoft ref1, ref2, ref3, ref4 Middle East ref1, ref2, ref3, ref4, ref5, ref6, ref7 ‘middle market’ ref1 Middleton, Julia ref1 migrant workers ref1, ref2, ref3, ref4 Miliband, Ed (MP) ref1 Miliband, Ralph ref1, ref2 Mill, John Stuart ref1 Miller, Andrew ref1n, ref2n Miller, Sienna ref1 Milton, John ref1, ref2, ref3 Miranda, David ref1, ref2 Mirror Group Newspapers ref1, ref2, ref3, ref4, ref5 mobile devices ref1, ref2, ref3, ref4, ref5, ref6, ref7 moderation ref1, ref2, ref3, ref4, ref5 Monaco ref1 Monbiot, George ref1 monitoring ref1 Monsanto ref1 Moore, Charles ref1, ref2, ref3 Moore, Michael ref1 Moran, Chris ref1 Morgan, Daniel ref1 Morgan, Piers ref1 Morgan Stanley ref1 morning conference ref1, ref2, ref3, ref4, ref5, ref6n Morozov, Evgeny ref1 Moses, Sir Alan ref1 Mossberg, Walt ref1 Mother Jones (magazine) ref1 Movable Type ref1 Mowatt, Roger ref1 Mowlam, Mo (MP) ref1, ref2n MPs ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 MSN ref1 Mubenga, Jimmy ref1, ref2 Mugabe, President Robert ref1 Mulcaire, Glenn ref1, ref2, ref3 Mumsnet ref1 Murdoch, James ref1, ref2, ref3, ref4, ref5 Murdoch, Rupert ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11 passim, ref1, ref2, ref3, ref4, ref5, ref6n Murdoch, Wendi ref1 Murdoch empire ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12, ref13, ref14, ref15, ref16n Murray, Douglas ref1 Murray, Scott ref1, ref2 Murrow, Edward R. ref1 Muslims ref1, ref2, ref3, ref4 Mutter, Alan ref1 mutualisation ref1, ref2, ref3 Myners, Paul ref1, ref2 MySpace ref1, ref2, ref3, ref4 National Security Agency (NSA) ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10 National Theatre ref1 National Union of Journalists ref1, ref2 Naughton, John ref1 NCND policy (never confirm nor deny) ref1 Negroponte, Nicholas ref1 Netherlands, Queen of the ref1 netiquette ref1 Netscape ref1, ref2 Neuberger, Lord ref1 Nevin, Charles ref1 New Republic (magazine) ref1 New Statesman (magazine) ref1, ref2, ref3, ref4, ref5 New York Observer (newspaper) ref1 New York offices ref1, ref2, ref3 New York Post (newspaper) ref1 New York Times v.

Global Catastrophic Risks by Nick Bostrom, Milan M. Cirkovic

affirmative action, agricultural Revolution, Albert Einstein, American Society of Civil Engineers: Report Card, anthropic principle, artificial general intelligence, Asilomar, availability heuristic, backpropagation, behavioural economics, Bill Joy: nanobots, Black Swan, carbon tax, carbon-based life, Charles Babbage, classic study, cognitive bias, complexity theory, computer age, coronavirus, corporate governance, cosmic microwave background, cosmological constant, cosmological principle, cuban missile crisis, dark matter, death of newspapers, demographic transition, Deng Xiaoping, distributed generation, Doomsday Clock, Drosophila, endogenous growth, Ernest Rutherford, failed state, false flag, feminist movement, framing effect, friendly AI, Georg Cantor, global pandemic, global village, Great Leap Forward, Gödel, Escher, Bach, Hans Moravec, heat death of the universe, hindsight bias, information security, Intergovernmental Panel on Climate Change (IPCC), invention of agriculture, Kevin Kelly, Kuiper Belt, Large Hadron Collider, launch on warning, Law of Accelerating Returns, life extension, means of production, meta-analysis, Mikhail Gorbachev, millennium bug, mutually assured destruction, Nick Bostrom, nuclear winter, ocean acidification, off-the-grid, Oklahoma City bombing, P = NP, peak oil, phenotype, planetary scale, Ponzi scheme, power law, precautionary principle, prediction markets, RAND corporation, Ray Kurzweil, Recombinant DNA, reversible computing, Richard Feynman, Ronald Reagan, scientific worldview, Singularitarianism, social intelligence, South China Sea, strong AI, superintelligent machines, supervolcano, synthetic biology, technological singularity, technoutopianism, The Coming Technological Singularity, the long tail, The Turner Diaries, Tunguska event, twin studies, Tyler Cowen, uranium enrichment, Vernor Vinge, War on Poverty, Westphalian system, Y2K

Chapter 16 discusses the possibility that the experiments that physicists carry out in particle accelerators might pose an existential risk. Concerns about such risks prompted the director of the Brookhaven Relativistic H eavy Ion Collider to commission an official report in 2000. Concerns have since resurfaced with the construction of more powerful accelerators such as CERN's Large Hadron Collider. Following the Brookhaven report, Frank Wilczek distinguishes three catastrophe scenarios: 1 . Formation of tiny black holes that could start accreting surrounding matter, eventually swallowing up the entire planet. 2. Formation of negatively charged stable strangelets which could catalyse the conversion ofall the ordinary matter on our planet into strange matter. 3.

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Such engineering is not foolproof - bridges do collapse, astronauts do perish - but at least we foresee the scope of potential problems. In contrast, the whole point of great accelerator projects like the Brookhaven Relativistic Heavy Ion Collider (RHIC) or the Counseil Europeen pour la Recherche Nucleaire (CERN) Large Hadron Collider (LHC) is to produce Global catastrophic risks 348 extreme conditions that take us beyond what is well understood. In that context, safety engineering enters the domain of theoretical physics. In discussing possible dangers associated with frontier research accelerators, the first thing to say is that while these machines are designed to produce unprecedented density ofenergy, that density is packed within such a miniscule volume of space that the total energy is, by most standards, tiny.

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., Dynamics of Populations of Planetary Systems 235 Krepon, M . 393 Kunda, Z. 99 Kurchatov Institute 419 Kurzweil, R., The Singularity is Near 79, 80, 82, 361 Kyoto Protocol 190- 1 , 193, 277, 5 1 3 laboratory safety, pathogenic organisms 460 La Garita Caldera 270-1 Index Landauer, R. 1 3 9 Landauer-Brillouin's limit 3 3 1 language, evolution 5 7 Larcher, W . and Bauer, H . 2 1 0 Large Hadron Collider (LHC), CERN 347-8 probability of strangelet production 3 5 3 see also particle collider experiments laser enrichment of uranium 425 Latane, B . and Darley, ). 109-10 The Late Great Planet Earth, H . Lindsey 74-5 latency of risks 168 launch status, nuclear weapons 383-4 Lederberg, J ., Biological Weapons: Limiting the Threat 475 Left Behind novels, Jenkins, ] . and LaHaye, T. 75 legitimization of terrorism 408 Leitenberg, M . , Assessing the Biological Weapons and Bioterrorism Threat 452, 475 Lenin 505 Leslie, j. 1 29 The End ofthe World: The Science and Ethics of Human Extinction 86 'level 2 risk' 176 Leventhal, P. and Alexander, Y. 405 Levi, M . , On Nuclear Terrorism 442 Levitt, S .

The Most Good You Can Do: How Effective Altruism Is Changing Ideas About Living Ethically by Peter Singer

Albert Einstein, clean water, cognitive load, corporate social responsibility, correlation does not imply causation, David Brooks, effective altruism, en.wikipedia.org, Flynn Effect, hedonic treadmill, Large Hadron Collider, Nick Bostrom, Peter Singer: altruism, purchasing power parity, randomized controlled trial, stem cell, Steven Pinker, TED Talk, trolley problem, William MacAskill, young professional

•Nanotech accident: This scenario involves tiny self-replicating robots multiplying until the entire planet is covered in them. It’s also known as the “gray goo” scenario. Let’s hope it stays in the realm of science fiction. •Physics research producing hyperdense “strange matter”: There has been some speculation that the development of devices like the Large Hadron Collider could produce matter so dense that it would attract nearby nuclei until the entire planet becomes a hyperdense sphere about one hundred meters in diameter. •Superintelligent unfriendly artificial intelligence: Some computer scientists believe that at some point during the present century, artificial intelligence will surpass human intelligence and will then be independent of human control.

Future Politics: Living Together in a World Transformed by Tech by Jamie Susskind

3D printing, additive manufacturing, affirmative action, agricultural Revolution, Airbnb, airport security, algorithmic bias, AlphaGo, Amazon Robotics, Andrew Keen, Apollo Guidance Computer, artificial general intelligence, augmented reality, automated trading system, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, Big Tech, bitcoin, Bletchley Park, blockchain, Boeing 747, brain emulation, Brexit referendum, British Empire, business process, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, cashless society, Cass Sunstein, cellular automata, Citizen Lab, cloud computing, commons-based peer production, computer age, computer vision, continuation of politics by other means, correlation does not imply causation, CRISPR, crowdsourcing, cryptocurrency, data science, deep learning, DeepMind, digital divide, digital map, disinformation, distributed ledger, Donald Trump, driverless car, easy for humans, difficult for computers, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, Erik Brynjolfsson, Ethereum, ethereum blockchain, Evgeny Morozov, fake news, Filter Bubble, future of work, Future Shock, Gabriella Coleman, Google bus, Google X / Alphabet X, Googley, industrial robot, informal economy, intangible asset, Internet of things, invention of the printing press, invention of writing, Isaac Newton, Jaron Lanier, John Markoff, Joseph Schumpeter, Kevin Kelly, knowledge economy, Large Hadron Collider, Lewis Mumford, lifelogging, machine translation, Metcalfe’s law, mittelstand, more computing power than Apollo, move fast and break things, natural language processing, Neil Armstrong, Network effects, new economy, Nick Bostrom, night-watchman state, Oculus Rift, Panopticon Jeremy Bentham, pattern recognition, payday loans, Philippa Foot, post-truth, power law, price discrimination, price mechanism, RAND corporation, ransomware, Ray Kurzweil, Richard Stallman, ride hailing / ride sharing, road to serfdom, Robert Mercer, Satoshi Nakamoto, Second Machine Age, selection bias, self-driving car, sexual politics, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart contracts, Snapchat, speech recognition, Steve Bannon, Steve Jobs, Steve Wozniak, Steven Levy, tech bro, technological determinism, technological singularity, technological solutionism, the built environment, the Cathedral and the Bazaar, The Structural Transformation of the Public Sphere, The Wisdom of Crowds, Thomas L Friedman, Tragedy of the Commons, trolley problem, universal basic income, urban planning, Watson beat the top human players on Jeopardy!, work culture , working-age population, Yochai Benkler

Even this cache was probably incomplete: it excluded, for OUP CORRECTED PROOF – FINAL, 29/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS Increasingly Quantified Societ y 65 instance, facial recognition data and information about his website usage.21 Mr Schrems was just one of (then nearly, now more than) 2 billion active users, from whom Facebook has built an extraor­ dinary rich profile of human life. Finally, data is increasingly generated by machines. Some are juggernauts belching out large amounts of data. When firing, the Large Hadron Collider at CERN generates 40 terabytes of data every second.22 In its first few weeks of operation in 2000, the Sloan Digital Sky Survey telescope harvested more data than had been previously been gathered in the history of astronomy.23 In the future, the largest data-contributors will be pervasive devices distributed around the planet.

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32 OUP CORRECTED PROOF – FINAL, 28/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS Index Jie, Ke 32 job applicants 266–7, 268 Jobs, Steve 314 Johnson, Bobby 399 Johnson, Steve 427 Jones, Steve 388 Jøsang, Audun 423 Jouppi, Norm 375 judicial system 102 Jury Theorem 224 justice algorithmic injustice 279–94 civil 259 concept 74–5, 76 conceptual analysis 81 criminal 259 as desert 260–1 as dessert 261, 262 distributive 257–70, 274, 278 and equality, difference between 259 fairness principle 353 property 313–41 in recognition 260, 271–8 social see social justice technological unemployment 295–312 Justinian, Emperor 202 Kahane, Guy 434 Kant, Immanuel 186, 272, 406 Karrahalios, Karrie 433 Kasparov, Garry 31, 36, 373 Kassarnig,Valentin 372 Keen, Andrew 376 Kelion, Leo 413 Kellmereit, Daniel 380 Kelly, Kevin 20, 21, 370, 373, 374, 375, 430 Kelly, Rick 384, 385 Kelly III, John E. 386, 388 Kelsen, Hans 103, 392 Kennedy, John F. 164, 188, 347 Kennedy, Robert F. 256 Keurig 116 Khatchadourian, Raffi 52, 382 503 Khomami, Nadia 397 Al-Khw­ār izmī, Abd’Abdallah Muhammad ibn Mūsā 94 Kim, Mark 376 King, Martin Luther 6, 180, 257, 360, 404 Kirchner, Lauren 403 Kirobo Mini 55 Kitchin, Rob 376, 377, 380, 381, 387, 388, 391, 404 Klaas, Brian 408 Kleinman, Zoe 383 Knockel, Jeffrey 399 Koch brothers 230 Kolhatkar, Sheelah 367, 423 Kollanyi, Bence 413 Korea 20 Kotler, Steven 374, 435 Krasodomski-Jones, Alex 412 Kurzweil, Ray 38, 366, 374, 436 Kymlicka, Will 418 labour market 303 Lai, Richard 386 Lampos,Vasileios 393 Landemore, Hélène 408, 411, 416 Laney, Doug 431 Langbort, Cedric 433 language importance to politics 16–17, 19 limits of 10–11 political concepts 76–80 public and private power 157 Lanier, Jaron 367, 374, 384, 400, 416, 419, 428, 431, 435 Data Deal 338 human enhancement 363 network effect 321 Silicon Valley startups 6–7 Wiki Democracy 246 Lant, Karla 376 Laouris,Yiannis 435 Large Hadron Collider 65 Larkin,Yelena 427 Larson, Jeff 403, 422 Larson, Selena 370, 421 OUP CORRECTED PROOF – FINAL, 28/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS 504 Index law adaptive 107–10 AI Democracy 253 AI systems 31 code-ified 110–12, 245 digital 100–14 dissent 179–80 enforcement 101–7 intellectual property 332 justice in recognition 274–5 oral cultures 111–12 rule of 115 self-enforcing 101–3 supercharged state 171–2 wise restraints 185–6 written 111, 112 Lawrence, Neil 374, 388, 427 Leftwich, Adrian 389 Lenin,Vladimir Ilyich 21, 153, 370 Leonardo Da Vinci 28 Lessig, Lawrence 391, 392, 394, 420, 433 code as law 96 cyberspace as a place 97 free software 359 law enforcement through force 104, 105 privatization of force 100, 117 Leta Jones, Meg 138, 397, 432 Levellers 215–16 Levy, Steven 404 Lewis, Michael 428 liberal democracy 216–17, 246, 254 liberal-democratic principle of legitimacy 350 liberalism 77, 350 liberty 3, 10, 23, 346 concept 74–5, 76 conceptual analysis 81 contextual analysis 84 Deliberative Democracy 234 and democracy 207–8, 222, 225, 249 digital 205–7 digital dissent 179–84 digital liberation 168–71 harm principle 195–205 human enhancement 363 nature of politics 74 price mechanism 270 and private power 189–94 supercharged state 171–9 and the tech firm 188–208 transparency regulation 355 types 164–8 wise restraints 184–6 see also freedom Library of Congress 56 life-logs 63 Lincoln, Abraham 89, 210, 231, 323 Linn, Allison 398 Linux 243–4, 245, 333 Lipińska,Veronika 435 lip-reading 30 liquid democracy 242 Lively, J. 409 Livingston, James 425 Livy 216 loans, and distributive justice 267, 268 Locke, John 216, 246, 301, 323, 429 loomio.org 234 Lopatto, Elizabeth 434 lottery, work distribution via 304 Loveluck, Benjamin 378 Luca, Michael 423 luck egalitarianism 262, 307 Luddites 13 Lukes, Steven 390–1, 395, 398 Luxemburg, Rosa 348, 432 Lynch, Jack 384 Machiavelli, Niccolò 188, 217, 406, 409 machine learning 34–7, 266 algorithmic injustice 293 commons 332 data-based injustice 282 Data Democracy 248 data’s economic importance 317 distributive justice 267 future of code 98 group membership fallacy 284 OUP CORRECTED PROOF – FINAL, 28/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS Index increasingly quantified society 61 liberty and private power 191 political campaigning 220 predictions 139, 173, 175 productive technologies 316 rule-based injustice 284 MacKinnon, Rebecca 396 Madison, James 216, 241, 369, 415 MagicLeap 59 Maistre, Joseph de 101 make-work 304 manipulation 93, 122 code 96, 97 digital liberation 170–1 harm principle 200 Mannheim, Karl 78, 390 Manyika, James 424 Mao, Huina 416 Marconi, Guglielmo 21 marginalization 273 Margretts, Helen 410 market system, and distributive justice 264–5 Markoff, John 400, 413 Martinez, Peter 413 Marx, Karl 367, 390, 398, 415, 417, 424, 425, 429, 434, 436 Communist Manifesto 326–7, 362 Direct Democracy 240–1 future of political ideas 86 justice 258 perception-control 144 on philosophers 7 political concepts 78 property 324, 326–7 sorcerer 366 workers 295, 298, 301, 307 Mason, Paul 374 Massachusetts Institute of Technology see MIT Mattu, Surya 403 Maxim, Hiram 20 Mayer-Schönberger,Viktor 387, 388, 395, 397, 427, 433 data 62, 65 forgetting versus remembering 137 505 Mayr, Otto 14, 368 McAfee, Andrew 374, 382, 390, 393, 427, 431 capital 315, 316, 334 McChesney, Robert W. 400, 427 McDermott, Daniel 390 McGinnis, John O. 416 McKinsey 295, 299 Mearian, Lucas 386 MedEthEx 108 medicine 3D printing 56–7 AI systems 31, 32, 108–9, 113 digital law 112–13 increasingly integrated technology 51, 54, 56–7 ransomware 182 robotics 54 technological unemployment 300 Medium 183 memory 136–8 Merchant, Brian 430 merit, and distributive justice 261 Mesthene, Emmanuel G. 368 metadata 63 Metcalfe’s Law 320 Metz, Cade 372, 373, 374, 375, 380 Metz, Rachel 407 Michaely, Roni 427 Microsoft acquisitions 318 chips 40 commons 332 concentration of tech industry 318, 320 Global Internet Forum to Counter Terrorism 191 HoloLens 59 patents 315 speech-recognition AI system 30 Tay 37, 346 might is right 349 military AI systems 31 brain–computer interfaces 48 sensors 50 OUP CORRECTED PROOF – FINAL, 28/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS 506 Index Mill, James 195 Mill, John Stuart 367, 403, 406–7, 411, 414, 415 change, need for 3 Deliberative Democracy 234 democracy 223 freedom of speech, constraints on 237 harm principle 196, 198, 199, 203 liberty 195–6, 201, 203 liquid democracy 242 normative analysis 83 predictions 173 upbringing 195 Miller, David 435 Mills, Laurence 418 Milton, John 124, 167, 395 minstrel accounts 232 Mirani, Leo 396 Miremadi, Mehdi 424 Misra, Tanvi 377 MIT affective computing 53 bomb-detecting spinach 50–1 Senseable City Lab 50 Technology Review Custom 427 temporary tattoos for smartphone control 51 Mitchell, Margaret 403 Mitchell, William J. 183, 376, 405 Mizokami, Kyle 379 Moley 407 Momentum Machines 299 Montesquieu, Charles de Secondat, Baron de 358, 433 Moore, Gordon 39, 374 Moore’s Law 39–40, 41 morality AI Democracy 253 automation of 176–7 Data Democracy 249–50 Direct Democracy 240 fragmented 204, 231 harm principle 200–5 justice in distribution 261 see also ethics Moravec’s paradox 54, 382 More, Max 402, 434 Morgan, J.

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

If such a joint project were sufficiently well resourced, it could have a good chance of being the first to reach the goal, especially if any rival project had to be small and secretive to elude detection. There are precedents of large-scale successful multinational scientific collaborations, such as the International Space Station, the Human Genome Project, and the Large Hadron Collider.29 However, the major motivation for collaboration in those cases was cost-sharing. (In the case of the International Space Station, fostering a collaborative spirit between Russia and the United States was itself an important goal.30) Achieving similar collaboration on a project that has enormous security implications would be more difficult.

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How successful they have been in a broader sense (taking into account cost-effectiveness and so forth) is harder to determine. In the case of the International Space Station, for example, there have been huge cost overruns and delays. For details of the problems encountered by the project, see NASA (2013). The Large Hadron Collider project has had some major setbacks, but this might be due to the inherent difficulty of the task. The Human Genome Project achieved success in the end, but seems to have received a speed boost from being forced to compete with Craig Venter’s private corporate effort. Internationally sponsored projects to achieve controlled fusion energy have failed to deliver on expectations, despite massive investment; but again, this might be attributable to the task turning out to be more difficult than anticipated. 30.

I See You Made an Effort: Compliments, Indignities, and Survival Stories From the Edge of 50 by Annabelle Gurwitch

Alan Greenspan, Large Hadron Collider, McMansion, multilevel marketing, Saturday Night Live, Steve Jobs, urban planning, zero-sum game

Two words that should never be in the same sentence. On my initial visit to a Beverly Hills hormone specialist, the doctor handed me a compendium of supplements she deemed essential for menopausal wellness.* Complete with diagrams, maps, and intersecting circles, it was so complicated, I thought it was a schematic drawing of the Large Hadron Collider. She also suggested a regimen of lasers, lightening and tightening, injectables and fillers. It was so overwhelming, I went home and curled into the fetal position on the chance that the effects of gravity on the aging process might be retarded if I ceased all movement. When inertia was no longer possible (it was time for the afternoon carpool), I slathered on my bioidentical hormone creams and started downing supplements by the fistful.* After a few days, I did feel less homicidal and suicidal.

The Internet Is a Playground by David Thorne

anti-globalists, Dunning–Kruger effect, Large Hadron Collider, late fees, Naomi Klein, peer-to-peer, Silicon Valley, Steve Jobs

To: David Thorne Subject: Re: Snap Hello David, Have you bought any new electrical equipment in the last few months that might account for the additional usage? From: David Thorne Date: Tuesday 17 August 2010 4:24 p.m. To: Allison Hayes Subject: Superconducting quadrupole electromagnets Hello Allison, Nothing that springs to mind. I purchased a Large Hadron Collider a few months back, but it has not seen much use. The one time I did manage to get it working, I ended up at the day before I unpacked it, so this wouldn’t count. Regards, David From: Allison Hayes Date: Tuesday 17 August 2010 4:31 p.m. To: David Thorne Subject: Re: Superconducting quadrupole electromagnets Whats a hadron collider?

Whistleblower: My Journey to Silicon Valley and Fight for Justice at Uber by Susan Fowler

"Susan Fowler" uber, Airbnb, Albert Einstein, Big Tech, Burning Man, cloud computing, data science, deep learning, DevOps, Donald Trump, Elon Musk, end-to-end encryption, fault tolerance, Grace Hopper, Higgs boson, Large Hadron Collider, Lyft, Maui Hawaii, messenger bag, microservices, Mitch Kapor, Richard Feynman, ride hailing / ride sharing, self-driving car, Silicon Valley, TechCrunch disrupt, Travis Kalanick, Uber for X, uber lyft, work culture

With his encouragement, I applied for a research assistant position in the group. I’ll never forget the moment I walked into the basement of the David Rittenhouse Laboratory for my interview. The hallways were lined with gigantic posters, including a picture of the ATLAS detector (an enormous particle detector at the Large Hadron Collider at CERN that particle physicists all around the world were using to search for the Higgs boson and supersymmetric particles), and a large detailed sketch of the ATLAS detector’s cross section, showing all of its electrical components and how they worked together. Taped to the walls were news clippings about famous particle physics discoveries, jokes about bosons and string theory, and photographs of professors and graduate students standing around pieces of the ATLAS detector.

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

In that case, the prospect of making and observing small black holes gets upgraded from “crazy” to “speculative, but not completely crazy.” I’m sure Hawking is rooting for it to happen. Unfortunately, the prospect of microscopic black holes has been seized on by a group of fearmongers to spin scenarios under which the Large Hadron Collider, a new particle accelerator at the CERN laboratory in Geneva, is going to destroy the world. Even if the chances are small, destroying the world is pretty bad, so we should be careful, right? But careful reviews of the possibilities (Ellis et al., 2008) have concluded that there’s nothing the LHC will do that hasn’t occurred many times already elsewhere in the universe; if something disastrous were going to happen, we should have seen signs of it in other astrophysical objects.

…

(Farhi) Jackiw, Roman Johnson, George Johnson, Matthew kaons Kasner, Edward Kelvin, William Thomson, Lord Kelvin scale Kepler, Johannes Kerr, Roy kinetic energy kinetic theory Kleban, Matthew Kolmogorov complexity Landauer, Rolf Lao Tzu Laplace, Pierre-Simon Laplace’s Demon Large Hadron Collider (LHC) Lavoisier, Antoine Lawrence Berkeley National Laboratory laws of nature laws of physics. See also specific forces and bouncing-universe cosmology and consciousness and entropy definition and irreversibility and memory and multiverse hypothesis and patterns and reversibility Lectures on Physics (Feynman) Lee, Tsung-Dao Leibniz, Gottfried Wilhelm Lemaître, Georges length contraction Leucippus life and the Boltzmann-Lucretius scenario and complexity definition of and energy budget of Earth and entropy and free energy and memory and multiverse hypothesis light light cones and the Big Bang and black holes and closed timelike curves described and the horizon problem and Newtonian space and the observable universe and time travel and white holes Linde, Andrei Liouville, Joseph Liouville’s Theorem locality location logarithms longitude Look at the Harlequins!

Mastering Pandas by Femi Anthony

Amazon Web Services, Bayesian statistics, correlation coefficient, correlation does not imply causation, data science, Debian, en.wikipedia.org, Internet of things, Large Hadron Collider, natural language processing, p-value, power law, random walk, side project, sparse data, statistical model, Thomas Bayes

To get a handle of how much data this would be, let me refer to an EMC press release published in 2010, which stated what 1 zettabyte was approximately equal to: "The digital information created by every man, woman and child on Earth 'Tweeting' continuously for 100 years " or "75 billion fully-loaded 16 GB Apple iPads, which would fill the entire area of Wembley Stadium to the brim 41 times, the Mont Blanc Tunnel 84 times, CERN's Large Hadron Collider tunnel 151 times, Beijing National Stadium 15.5 times or the Taipei 101 Tower 23 times..." --EMC study projects 45× data growth by 2020 The growth rate of data has been fuelled largely by a few factors, such as the following: The rapid growth of the Internet. The conversion from analog to digital media coupled with an increased capability to capture and store data, which in turn has been made possible with cheaper and more capable storage technology.

Raw Data Is an Oxymoron by Lisa Gitelman

23andMe, collateralized debt obligation, computer age, continuous integration, crowdsourcing, disruptive innovation, Drosophila, Edmond Halley, Filter Bubble, Firefox, fixed income, folksonomy, Google Earth, Howard Rheingold, index card, informal economy, information security, Isaac Newton, Johann Wolfgang von Goethe, knowledge worker, Large Hadron Collider, liberal capitalism, lifelogging, longitudinal study, Louis Daguerre, Menlo Park, off-the-grid, optical character recognition, Panopticon Jeremy Bentham, peer-to-peer, RFID, Richard Thaler, Silicon Valley, social graph, software studies, statistical model, Stephen Hawking, Steven Pinker, text mining, time value of money, trade route, Turing machine, urban renewal, Vannevar Bush, WikiLeaks

As Cory Doctorow describes in a cover article for Nature, we have created immense industrial data centers to store and process all this scientific information.11 In Welcome to the Petacenter, Doctorow stands in awe of the hundredmillion-dollar computing centers that have been established to store the tens of thousands of terabytes (a terabyte being a thousand gigabytes) of data flowing from dozens of meteorological satellites, hundreds of genomic sequencers, thousands of ecological field sites, and the millions of sensors at the Large Hadron Collider. Just as the Zea Mays species of corn would die out in a couple seasons without our assistance, these computing centers would quickly overheat if not for the multistory cooling centers that control the massive quantity of heat they produce. If the primary, secondary, and tertiary cooling systems fail, it would only take ten minutes for the disk drives to bring their environment to a hazardous 42 °C (108 °F)—any hotter and they would begin to crack and break.

Animals by Emma Jane Unsworth

call centre, dark matter, fear of failure, Google Earth, Higgs boson, Large Hadron Collider, rolodex, unpaid internship

My jeans pockets were heavy with coins, pirate’s pockets: the result of spending notes and forgetting when you got change. As I stood in the queue I read the front page of the paper. Sure enough, there it was, albeit with a caveat (the restraint of scientists struck me as a more glorious thing than usual that morning): the Large Hadron Collider in Geneva had reported ‘a new boson with Higgs-like properties’. I went back to my seat – Excuse me again, sorry – and devoured the story, thankful for the distraction. The text and the thrill of the news evaporated and I was left with guilt again, heightened by the thought of bodies – mine and my dad’s, of care and lack of care.

Vue.js 2 Cookbook by Andrea Passaglia

bitcoin, business logic, cognitive load, functional programming, Kickstarter, Large Hadron Collider, loose coupling, MVC pattern, node package manager, Silicon Valley, single page application, web application, WebSocket

Let's suppose we work for the ACME Research and Development Laboratory, and we are in charge of reproducing some experiment in any field we want. We may choose an experiment from the following list: data: { experiments: [ {name: 'RHIC Ion Collider', cost: 650, field: 'Physics'}, {name: 'Neptune Undersea Observatory', cost: 100, field: 'Biology'}, {name: 'Violinist in the Metro', cost: 3, field: 'Psychology'}, {name: 'Large Hadron Collider', cost: 7700, field: 'Physics'}, {name: 'DIY Particle Detector', cost: 0, field: 'Physics'} ] } Let's print the list right away using a simple <ul> element: <div id="app"> <h3>List of expensive experiments</h3> <ul> <li v-for="exp in experiments"> {{exp.name}} ({{exp.cost}}m ) </li> </ul> </div> If you are not a big fan of physics, you may want to filter out physics experiments from this list.

How Democracy Ends by David Runciman

barriers to entry, basic income, Bernie Sanders, Big Tech, bitcoin, blockchain, Brexit referendum, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, centre right, crowdsourcing, cuban missile crisis, disinformation, Dominic Cummings, Donald Trump, Dr. Strangelove, Edward Snowden, fake news, first-past-the-post, Francis Fukuyama: the end of history, full employment, Internet of things, Jeremy Corbyn, Jon Ronson, Joseph Schumpeter, Kickstarter, Large Hadron Collider, loss aversion, Mahatma Gandhi, Mark Zuckerberg, money: store of value / unit of account / medium of exchange, mutually assured destruction, Network effects, Nick Bostrom, Norman Mailer, opioid epidemic / opioid crisis, Panopticon Jeremy Bentham, Paris climate accords, Peter Thiel, post-truth, power law, precautionary principle, quantitative easing, Russell Brand, self-driving car, Sheryl Sandberg, Silicon Valley, Steve Bannon, Steven Pinker, the long tail, The Wisdom of Crowds, Travis Kalanick, universal basic income, Yogi Berra

Second, even if we get rid of nuclear weapons, there are too many other existential risks that can stymie democracy on their own. As the capacity of human beings to wreak havoc on their habitat increases, nuclear war has lost its special status as the totem of our destructive power. If we couldn’t be trusted with the bomb, we can’t be trusted with AI either; or with bio-engineering; or with the Large Hadron Collider. Nuclear weapons began the age of existential risk but they no longer define it. We might put one genie back in the bottle. We won’t put them all back. Democracy cannot control existential risk. The most it can hope for is to be spared by it. This is how democracy gets treated by the existential risk-management industry: with kid gloves, like some precious object of historic value that might yet turn out to have an incidental use.

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

Yet in the Torah, and in the Bible, we read that the first thing God makes is light. ‘Let there be Light.’ And from this, everything else is made. Making matter out of light is not easy. Photon-photon acceleration was theorised back in 1934, but without the technical capability to prove it. Recently, at the Large Hadron Collider, CERN, Geneva, physicists have made it happen. It’s Einstein’s E = mc2 in reverse. We know that a small amount of matter can release a huge amount of energy (the atomic bomb), but at the LHC they have discovered that a huge amount of energy is needed to create a tiny amount of matter. It can be done – by colliding photons (light particles).

Inferior: How Science Got Women Wrong-And the New Research That's Rewriting the Story by Angela Saini

Albert Einstein, Anthropocene, classic study, demographic transition, Drosophila, feminist movement, gender pay gap, Large Hadron Collider, meta-analysis, mouse model, out of africa, place-making, scientific mainstream, Steven Pinker, the scientific method, women in the workforce

Rippon tells me that in her field it’s impossible not to see the scientific data politicized, especially when it enters the public realm. “Science doesn’t operate in a political vacuum,” she explains. “I think there are some sciences which can be more objective than others. But we are dealing with people, we’re not the Large Hadron Collider.” Unlike particle physics, neuroscience is about humans, and it has profound repercussions for how people see themselves. “It’s not something that people don’t know much about. This is about everybody’s lives. Everybody has a brain, everybody has a gender of some kind,. . .they’ve either been in a mixed-sex school or they have worked in a mixed-sex environment.

Talk on the Wild Side by Lane Greene

Affordable Care Act / Obamacare, Albert Einstein, Boris Johnson, deep learning, Donald Trump, ending welfare as we know it, experimental subject, facts on the ground, fake news, framing effect, Google Chrome, Higgs boson, illegal immigration, invisible hand, language acquisition, Large Hadron Collider, machine translation, meta-analysis, Money creation, moral panic, natural language processing, obamacare, public intellectual, Ronald Reagan, Sapir-Whorf hypothesis, Snapchat, sparse data, speech recognition, Steven Pinker, TED Talk, Turing test, Wall-E

An enlightening thought experiment on what words make possible is Randall Munroe’s book Thing Explainer. Munroe, who once worked for NASA and now writes a comic strip about mathematics, computers, language and logic, explains some of the world’s most complicated technologies using only the most common 1,000 words in the English language. This can be hard to do with the Large Hadron Collider (which he calls the “big little-thing hitter”) but it is fascinating (and hilarious) evidence that thought clearly does not proceed directly from language, as many people seem to think. Physicists invented the word “hadron” because they needed it; they did not find the particle because they had the word in their vocabularies.

How to Speak Money: What the Money People Say--And What It Really Means by John Lanchester

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, asset allocation, Basel III, behavioural economics, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Swan, blood diamond, Bretton Woods, BRICs, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collective bargaining, commoditize, creative destruction, credit crunch, Credit Default Swap, crony capitalism, Dava Sobel, David Graeber, disintermediation, double entry bookkeeping, en.wikipedia.org, estate planning, fear index, financial engineering, financial innovation, Flash crash, forward guidance, Garrett Hardin, Gini coefficient, Glass-Steagall Act, global reserve currency, high net worth, High speed trading, hindsight bias, hype cycle, income inequality, inflation targeting, interest rate swap, inverted yield curve, Isaac Newton, Jaron Lanier, John Perry Barlow, joint-stock company, joint-stock limited liability company, junk bonds, Kodak vs Instagram, Kondratiev cycle, Large Hadron Collider, liquidity trap, London Interbank Offered Rate, London Whale, loss aversion, low interest rates, margin call, McJob, means of production, microcredit, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, negative equity, neoliberal agenda, New Urbanism, Nick Leeson, Nikolai Kondratiev, Nixon shock, Nixon triggered the end of the Bretton Woods system, Northern Rock, offshore financial centre, oil shock, open economy, paradox of thrift, plutocrats, Ponzi scheme, precautionary principle, proprietary trading, purchasing power parity, pushing on a string, quantitative easing, random walk, rent-seeking, reserve currency, Richard Feynman, Right to Buy, road to serfdom, Ronald Reagan, Satoshi Nakamoto, security theater, shareholder value, Silicon Valley, six sigma, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, sovereign wealth fund, Steve Jobs, survivorship bias, The Chicago School, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, trickle-down economics, two and twenty, Two Sigma, Tyler Cowen, Washington Consensus, wealth creators, working poor, yield curve

“Dynamics” concerns movement. So even without knowing anything about it, you can tell quantum chromodynamics is the study of weird modern physics to do with color and movement. (As it happens, the color is metaphorical—it’s a random, whimsical name given to a range of mathematical properties.) The large hadron collider? Well, it’s large and it collides hadrons, whatever they are. Again, you can get the gist. For many concepts in the world of money, that isn’t true. Often, there’s no way to break a term down and work out more or less what it means. “Consumer surplus,” for example, sounds like a surplus of consumers.

Accessory to War: The Unspoken Alliance Between Astrophysics and the Military by Neil Degrasse Tyson, Avis Lang

active measures, Admiral Zheng, airport security, anti-communist, Apollo 11, Arthur Eddington, Benoit Mandelbrot, Berlin Wall, British Empire, Buckminster Fuller, Carrington event, Charles Lindbergh, collapse of Lehman Brothers, Colonization of Mars, commoditize, corporate governance, cosmic microwave background, credit crunch, cuban missile crisis, dark matter, Dava Sobel, disinformation, Donald Trump, Doomsday Clock, Dr. Strangelove, dual-use technology, Eddington experiment, Edward Snowden, energy security, Eratosthenes, European colonialism, fake news, Fellow of the Royal Society, Ford Model T, global value chain, Google Earth, GPS: selective availability, Great Leap Forward, Herman Kahn, Higgs boson, invention of movable type, invention of the printing press, invention of the telescope, Isaac Newton, James Webb Space Telescope, Johannes Kepler, John Harrison: Longitude, Karl Jansky, Kuiper Belt, Large Hadron Collider, Late Heavy Bombardment, Laura Poitras, Lewis Mumford, lone genius, low earth orbit, mandelbrot fractal, Maui Hawaii, Mercator projection, Mikhail Gorbachev, military-industrial complex, mutually assured destruction, Neil Armstrong, New Journalism, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, operation paperclip, pattern recognition, Pierre-Simon Laplace, precision agriculture, prediction markets, profit motive, Project Plowshare, purchasing power parity, quantum entanglement, RAND corporation, Ronald Reagan, Search for Extraterrestrial Intelligence, skunkworks, South China Sea, space junk, Stephen Hawking, Strategic Defense Initiative, subprime mortgage crisis, the long tail, time dilation, trade route, War on Poverty, wikimedia commons, zero-sum game

The US space employment situation looks even grimmer when contrasted to that in Europe and Japan during the same period.44 Today, while private, for-profit US companies perfect a space taxi that may replace the shuttle program, our uneasy partner Russia ferries America’s astronauts to and from the International Space Station for a steep fee: about $71 million per seat for a round trip through 2016, increasing to $82 million under the next contract.45 Since Russia is, for the time being, the only game in town, that price increase is not a shock. Just supply and demand at work. Today, unless they’re lucky enough to have been hired there or to have European collaborators, American particle physicists wistfully gaze across the Atlantic Ocean and over the Alps at the Large Hadron Collider near Geneva, Switzerland—the most powerful accelerator ever built, in which controlled conditions that rival the earliest high-energy moments of the Big Bang have yielded evidence of the long-sought subatomic particle called the Higgs boson. They’re wistful because Europe’s collider is only a fifth as powerful as America’s Superconducting Super Collider would have been, had Congress not cut the entire project in 1993, a few short years after peace broke out between the United States and the Soviet Union.

…

on arms control and cooperation, 284 assassination, 286 Cuban Missile Crisis, 492–93n inaugural address, 497–98n on landing a man on the Moon, 282, 320, 458n leadership theme, 323 Limited Nuclear Test Ban Treaty, 215 on mastery of space, 157 and militarization of space, 273–74, 281–82, 284 missile gap and 1960 election, 281, 496n peace and freedom themes, 282, 283 space budget, 281–82, 283, 320, 510n space power strategy, 319–20 space weapons program, 286 Kepler, Johannes, 49, 93, 110, 424n, 440n KEYHOLE satellites, 204–5, 228, 230, 343, 500n Khrushchev, Nikita, 281, 284, 492n, 496n, 497n, 506n KH-1 CORONA satellites, 204–5, 228, 500n KH-8 GAMBIT satellites, 205 KH-9 HEXAGON satellites, 205, 228–29, 230 KH-11 (Advanced) satellites, 205–6, 343 KH-11 KENNAN satellites, 204, 205, 343, 471n Killkan report, “Meeting the Threat of Surprise Attack,” 493–94n Kinetic Energy Antisatellite (KE-ASAT) interceptor, 258–59 kinetic-energy weapons, 240, 241 King’s College, New York, 112, 113 Kirchhoff, Gustav, 146–47 Kiska, evacuation by Japan, 189 Kitab al-Fawa’id fi usul al-bahr wa-l-qawa’id, 67, 431n Klebesadel, Ray, 217 Knights Templar, 80 Korolev, Sergei, 263–64, 266, 268, 286, 487n, 489n Krafft, Karl Ernst, 59, 60–61, 429n Krepon, Michael, 309, 310, 485n, 507n Kritzinger, H. H., 427–28n Kubrick, Stanley, 494n Kuiper Belt, 344 Kutzscher, Edgar, 476n Lacrosse satellite, 343 LaFeber, Walter, 303 Landsat, 343–44 Langley, Samuel P., 128, 148, 457n Laplace, Pierre-Simon, 456n Large Hadron Collider, Switzerland, 28 Lascaux, France, cave drawings, 420–21n laser-guided bombs, 332, 335, 342 laser guide stars, 154, 155 lasers acronym, 242 in airborne antimissile defense, 156, 253 Curiosity rover’s ChemCam laser, 242, 389–90 as directed-energy weapons, 241–42, 247 fiber laser, 246 geodetic meridian and, 99 invention, 288 spaced-based lasers, challenges of, 245–47, 480–81n Lasser, David, 192 Last Empire, The (Vidal), 35 Late Heavy Bombardment, 384 latitude, 72, 73–74, 83 Lay, James S., Jr., 304–5 leap second, 46 leap year, 422–23n Lebombo bone, 420n Lee, Robert E., 124, 126, 449n Lee, Wen Ho, 375 Lehman Brothers, 5 LeMay, Curtis, 248, 304, 481n, 506n lenses achromatic lens, 130, 132 apochromatic lens, 132 color problem in lens optics, 129–30 combinations used in telescopes, 109, 110, 444n concave lenses, 110, 129, 442n convex lenses, 110, 129 double concave lenses, 129 double convex lenses, 129 plano-concave lenses, 129 plano-convex lenses, 129 problems in large refracting telescopes, 133 spectacle lenses, 102, 442n see also telescopes Leutze, Emanuel, 114–15 Lewis, Jerry, 412n Lewis, Outer Hebrides, Scotland, 72 Lewis, Sinclair, 274, 315 LHS 1140B exoplanet, detection, 399 liangtianchi, 75 Libya, 328, 331 Liebenfels, Lanz von, 421n Liebig, Justus von, 133 LIGO (Laser Interferometer Gravitational-Wave Observatory), 198, 399, 461n Limited Nuclear Test Ban Treaty (1963), 215, 273, 285, 287, 293, 313, 498n Lincoln, Abraham, 269 Lipperhey, Hans, 102, 103, 104, 106, 107, 109 “Little Boy” (Hiroshima), 303, 307, 505n Little Round Top, 126–27 Lockheed Martin campaign contributions, 412n in Colorado Springs, 16 F-117A stealth fighter, 197, 198, 332, 470n, 514n HEXAGON (KH-9) satellites, 205 prosperity after September 11, 2001, 11, 12 Russian rocket joint ventures, 363, 371 Skunk Works unit, 198, 276, 469n weapons manufactured by, 18 Lo Compasso da Navigare, 77 lodestones, 75, 436n long-distance telephone calls, 177–78, 462n longitude differences of latitude and longitude, 73 difficulty in determining, 73, 93, 440n Hipparchus development of, 72, 73 methods of determining, 94–97 need for a system of latitude, 93–94 places used for zero degrees, 87, 89, 94 prime meridian and, 87, 89, 98–99 prizes for solving the longitude problem, 95–96 see also meridians Lord, Lance W., 18, 19 Los Alamos National Laboratory, 216, 217, 390–91 Louis XVI, 121 Lovell, Bernard, 191, 209, 210–12, 268, 468n, 489n low Earth orbit (LEO), 398 Luna (Lunik) probes, 211, 271–72, 473n “lunar cycle effect” in stock market, 56 lunar cycles and lunar months, 39, 420–21n Luther, Martin, 51 Lutwak, Robert, 339 Lydians and Medes, 45, 423n Macbeth (Shakespeare), 173 Madeiras, 80 Mad Men (TV series), 161 Magellan, Ferdinand, 88, 436n magnetic compass development, 75–78 magnetite, 75 Maher, Bill, 392 Making of a Soviet Scientist, The (Sagdeev), 360 Malus, Étienne-Louis, 456n maneuverable satellites, 397, 531n Manhattan Project, 390, 401 Mansfield Amendment, 222–23 Mao Zedong, 318, 351 maps and mapmaking at end of thirteenth century, 78 Eratosthenes, 87 first extant terrestrial globe (“Erdapfel”), 87, 436n first maps of Earth’s inhabited regions, 70–71 as a form of political and social power, 91–92 Geographike Hyphegesis (Ptolemy), 50, 78, 85, 86, 87 meaning of maps, 92 Mercator’s world map, 90, 439n in sixteenth century, 89–90, 439n see also charts, maritime Marat, Jean-Paul, 121 March for Science, 378, 404 Marconi, Guglielmo, 184 Mark I radio telescope (Lovell Telescope), 180–81, 209–12, 472–73n see also Jodrell Bank Observatory Marseille Observatory, 133 Martin Marietta, 363 masers, 242, 245 Maskelyne, Nevil, 94, 96, 441n Massalia (Marseille), 70, 71, 72 Maurice of Nassau (prince), 102, 104, 107, 117 Maya, 40 McCain, John, 53 McDougall, Walter A., 261 MC 14/2 (“Massive Retaliation”), 305–6 McNamara, Robert, 285, 289, 492–93n Medes and Lydians, 45, 423n Medicare and Medicaid legislation, 288 Melvill, Thomas, 145 Mercator, Gerardus, 90, 438n meridians convergence near Poles, 84, 436–37n geodetic meridian, 99 need for, 87–88 places used for zero degrees, 87, 89, 94 prime meridian, 87, 89, 98–99 see also longitude Mesopotamia, 34, 41, 42, 49, 57, 432n meteors, detection with radar, 191 microwave ovens, 189 microwave radar, 188–89 microwaves communication using, 171, 177–78 discovery of, 171 Earth’s atmosphere and, 200–201 nonlethal weapons using, 201, 470–71n water hole, 200–201, 470n MIDAS (Missile Defense Alarm System) satellite, 278 military burden, 452n military, interservice competition, 262, 289, 500nn military satellites CCDs in, 204–7 Defense Support Program, 158, 341 during Eisenhower presidency, 278 film-return types, 204, 205, 228 ISR capabilities, 158–59 military space budget, 321, 510n see also spy satellites military spending after Vietnam War, 8, 409–10n compared to astrophysics spending, 402–3, 533nn global military spending, 403, 404, 533n military space budget, 321, 510n after September 11 attack, 12–13, 412n Strategic Defense Initiative (Star Wars), 12, 250, 411n Milky Way Andromeda galaxy collision predicted, 234 radio waves from center of, 178–79 rapid movement of central stars, 344 vs. other galaxies in universe, 131 width, 399 milspace, 349 Minoans, 68, 69 mirrors in reflecting telescopes, 133 Mir space station (USSR), 359–60, 362, 522n Missile Defense Agency, 12, 252 missile defense technology, see Strategic Defense Initiative Moltz, James Clay, 261, 280, 359 Moluccas (Spice Islands), 88 Molyneux, William, 108 Montgomery, Bernard, 305 Moon albedo, 196 first daguerreotypes of, 143, 144, 456n mountains and craters discovered, 52, 103, 110 plans to detonate a nuclear bomb on, 272, 491–92n radio waves bounced off surface, 191 Moon landings Apollo 11 mission, 353, 369 cost, 320, 510n Kennedy’s plan for, 282, 320, 458n NASA’s mandate, 289 opposition to, 289, 500n reaction to, 381–82 Moore, Francis, 426n Moran, James, 412n Morgan, J.

Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity by Douglas Rushkoff

activist fund / activist shareholder / activist investor, Airbnb, Alan Greenspan, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, benefit corporation, bitcoin, blockchain, Burning Man, business process, buy and hold, buy low sell high, California gold rush, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, centralized clearinghouse, citizen journalism, clean water, cloud computing, collaborative economy, collective bargaining, colonial exploitation, Community Supported Agriculture, corporate personhood, corporate raider, creative destruction, crowdsourcing, cryptocurrency, data science, deep learning, disintermediation, diversified portfolio, Dutch auction, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gamification, Garrett Hardin, gentrification, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, independent contractor, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, Large Hadron Collider, loss aversion, low interest rates, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Mitch Kapor, Naomi Klein, Network effects, new economy, Norbert Wiener, Oculus Rift, passive investing, payday loans, peer-to-peer lending, Peter Thiel, post-industrial society, power law, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Russell Brand, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, stock buybacks, TaskRabbit, the Cathedral and the Bazaar, The Future of Employment, the long tail, trade route, Tragedy of the Commons, transportation-network company, Turing test, Uber and Lyft, Uber for X, uber lyft, unpaid internship, Vitalik Buterin, warehouse robotics, Wayback Machine, Y Combinator, young professional, zero-sum game, Zipcar

In addition to the hardware, miners must invest in a tremendous amount of computer processing and electricity consumption. In 2013, miners expended some 1,000 megawatt-hours per day verifying transactions and mining new bitcoins.37, 38 As Bloomberg writer Mark Gimein noted, that’s half the power needed to run the Large Hadron Collider. Less than one year later, PandoDaily placed the network’s energy usage at 131,019.91 megawatt-hours per day, an increase of over 1,000 percent.39 While specialized computers called “mining rigs” are improving the energy efficiency of bitcoin mining, the shrinking number of unmined bitcoins and increasing length of the blockchain are raising the level of computing power required to perform Bitcoin’s proof-of-work problems.40 So even if Bitcoin did turn out to be economically feasible, it is unlikely to prove environmentally sustainable.

Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement by Eric Redmond, Jim Wilson, Jim R. Wilson

AGPL, Amazon Web Services, business logic, create, read, update, delete, data is the new oil, database schema, Debian, domain-specific language, en.wikipedia.org, fault tolerance, full text search, general-purpose programming language, Kickstarter, Large Hadron Collider, linked data, MVC pattern, natural language processing, node package manager, random walk, recommendation engine, Ruby on Rails, seminal paper, Skype, social graph, sparse data, web application

It enforces no schema (similar to Riak but unlike Postgres), so documents can optionally contain fields or types that no other document in the collection contains. But don’t think that MongoDB’s flexibility makes it a toy. There are some huge production MongoDB (often just called Mongo) deployments out there, like Foursquare, bit.ly, and CERN, for collecting Large Hadron Collider data. 5.1 Hu(mongo)us Mongo hits a sweet spot between the powerful queryability of a relational database and the distributed nature of other datastores like Riak or HBase. Project founder Dwight Merriman has said that MongoDB is the database he wishes he’d had at DoubleClick, where as the CTO he had to house large-scale data while still being able to satisfy ad hoc queries

High-Frequency Trading by David Easley, Marcos López de Prado, Maureen O'Hara

algorithmic trading, asset allocation, backtesting, Bear Stearns, Brownian motion, capital asset pricing model, computer vision, continuous double auction, dark matter, discrete time, finite state, fixed income, Flash crash, High speed trading, index arbitrage, information asymmetry, interest rate swap, Large Hadron Collider, latency arbitrage, margin call, market design, market fragmentation, market fundamentalism, market microstructure, martingale, National best bid and offer, natural language processing, offshore financial centre, pattern recognition, power law, price discovery process, price discrimination, price stability, proprietary trading, quantitative trading / quantitative finance, random walk, Sharpe ratio, statistical arbitrage, statistical model, stochastic process, Tobin tax, transaction costs, two-sided market, yield curve

URL: http://www.sec.gov/ news/speech/2013/spch021913ebw.htm. 230 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 231 — #251 i i Index (page numbers in italic type relate to tables or figures) A B algorithmic execution: and leaking of information, 159–83, 160, 162, 163, 165, 167, 168, 169, 171, 172, 174, 176–7, 178–9; see also AlphaMax; BadMax BadMax approach and data sample, 166–8, 168 and BadMax and gross and net alpha, 168–70 and clustering analysis, 170–4, 171, 172, 174 definition, 160–4 and GSET, 174–5, 176–7 and high alpha of large clusters, 170–4 and trading algorithms, 70–1 algorithms: generations of, 23–7 predatory, 8 tactical liquidity provision 10–11 trading: and algorithmic decision-making, 71–2 and algorithmic execution, 70–1 evolution of, 22–8 generations, 23–7; see also trading algorithms, evolution of and indicator zoology, 27–8 and transaction cost, 28–31 AlphaMax, 160–6 passim see also BadMax; information leakage alternative limit order book, 80–6 agent-based model, 83–5, 86 results and conclusion, 85 and spread/price–time priority, 82–3 BadMax 159–83 passim, 169, 178–9, 180–2 and data sample, 166–8 and gross and net alpha, 168–70 profitability grid, 180–2 see also algorithmic execution: and leaking information; AlphaMax; information leakage Black Wednesday, 8 C clustering analysis, and high alpha of large clusters, 170–4 CME, Nasdaq’s joint project with, xvi cointegration, 44, 53–9 Consolidated Audit Tape (CAT), 216 construction of trading signals, 31–8 and order book imbalance, 36–8 and timescales and weights, 31–3, 33 and trade sign autocorrelations, 34–6 cumulative distribution function, 130–1 D dark pools, smart order routing in, 115–22 E equity markets: execution strategies in, 21–41, 25, 29, 30, 33, 35, 37, 38, 40 and fair value and order protection, 38–41, 40 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 232 — #252 i i HIGH-FREQUENCY TRADING and trading signals, construction of, 31–8; see also trading signals and types of client or market agent, 22 European Exchange Rate Mechanism (ERM), sterling joins, 8 execution shortfall, and information leakage, 164–6, 165; see also information leakage execution strategies: in equity markets, 21–41, 25, 29, 30, 33, 35, 37, 38, 40 and fair value and order protection, 38–41, 40 and trading signals, construction of, 31–8; see also trading signals in fixed-income markets, 43–62, 47, 48, 49, 50, 51, 52, 54, 55, 57, 58, 61 and cointegration, 44, 53–9 and information events, 44, 46–53 and pro rata matching, 44, 59–62 and fixed-income products, 44–6 experimental evaluation, 133–40 F fair value and order protection, 38–41, 40 fixed-income markets: execution strategies in, 43–62, 47, 48, 49, 50, 51, 52, 54, 55, 57, 58, 61 and cointegration, 44, 53–9 and information events, 44, 46–53 and pro rata matching, 44, 59–62 and short-term interest rates, 45–6 and Treasury futures, 46 fixed-income products, 44–6 and short-term interest rates, 45–6 and Treasury futures, 46, 47, 48, 51, 52, 55 see also fixed-income markets flash crash, 2, 77–8, 207, 209–10, 210, 218 see also market stress foreign-exchange markets: and the currency market, 65–73 trading algorithms, 69–72 and trading frequencies, 65–73, 72, 73 venues, 66–9 high-frequency trading in, 65–88, 66, 72, 73, 86 academic literature, 74–80 and alternative limit order book, 80–6; see also main entry Foresight Project, 215, 217, 224 futures markets: microstructural volatility in, 125–41, 133, 134, 136, 137, 138–9 experimental evaluation, 133–40 HDF5 file format, 127 maximum intermediate return, 131–2 parallelisation, 132–3 test data, 126–7 and volume-synchronised probability of informed trading, 128–31 G Goldman Sachs Electronic Trading (GSET), 159, 160, 161, 163, 166–80 passim, 167, 168, 169, 174–5 H HDF5 file format, 127 high-frequency trading (HFT): and “cheetah traders”, 1, 13 232 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 233 — #253 i i INDEX and event-based time paradigm, 15 in FX markets 65–88, 66, 72, 73, 86; see also foreign-exchange markets, 74–80 and alternative limit order book, 80–6; see also main entry and the currency market, 65–73 and trading frequencies, 65–73, 72, 73 legislative changes enable, 2 machine learning for, 91–123, 100, 101, 103, 104, 107, 108–9, 111, 117, 121 and high-frequency data, 94–6 and optimised execution in dark pools via censored exploration, 93 and optimised trade execution via reinforcement learning, 92 and predicting price movement from order book state, 92–3 and price movement from order book state, predicting, 104–15 and reinforcement learning for optimised trade execution, 96–104 and smart order routing in dark pools, 115–22 in market stress, 76–80 central bank interventions, 79–80 flash crash (2010), 77–8 yen appreciation (2007), 77 yen appreciation (2011), 78–9 markets’ operation and dynamic interaction changed by, xv and matching engine, 3, 4 and more than speed, 7–12 new paradigm in, 2–4 paradigm of, insights into, 1–17, 7, 10–11, 14 regulatory challenge of, 207–9, 210, 212, 214 good and bad news concerning, 208–14 and greater surveillance and coordination, proposals for, 215–18 and market rules, proposals to change, 218–25 and proposals to curtail HFT, 225–8 solutions, 214–28 statistics to monitor, developing, 15 and time, meaning of, 5–7 and volatility, heightening of, 12 see also low-frequency trading I implementation shortfall: approach to, illustrated, 192–203 daily estimation, 195–9 intra-day estimation, 199–203 shortfall calculations, 193–5 discussed, 186–9 with transitory price effects, 185–206, 196, 197, 198, 199, 200, 202, 203 implementation details, 204–5 and observed and efficient prices and pricing errors, 189–92 indicator zoology, 27–8 information events, 44, 46–53 and event microscope, 50–3 information leakage: and algorithmic execution, 159–83, 176–7, 178–9 BadMax approach and data sample, 166–8, 168 233 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 234 — #254 i i HIGH-FREQUENCY TRADING and BadMax and gross and net alpha, 168–70 and clustering analysis, 170–4, 171, 172, 174 and GSET, 174–5, 176–7 and high alpha of large clusters, 170–4 defining, 160–4 and execution shortfall, 164–6, 165 see also AlphaMax; BadMax L large clusters, high alpha of, 170–4 Large Hadron Collider, 125–41 latency arbitrage, 9 leakage of information: and algorithmic execution, 159–83, 176–7, 178–9 BadMax approach and data sample, 166–8, 168 and BadMax and gross and net alpha, 168–70 and clustering analysis, 170–4, 171, 172, 174 and GSET, 174–5, 176–7 and high alpha of large clusters, 170–4 defining, 160–4 and execution shortfall, 164–6, 165 see also AlphaMax; BadMax liquidity squeezers, 9 liquidity and toxicity contagion, 143–56, 144, 145, 147, 148, 151, 153, 154 empirical analysis, 151–5 order-flow toxicity contagion model, 146–51 low-frequency trading: choices needed for survival of, 15 and event-based time paradigm, 15 joining the herd, 15 and monitoring of HFT activity, 15 and order-flow toxicity, monitoring, 16 and seasonal effects, avoiding, 16 and smart brokers, 16 see also high-frequency trading M machine learning: for high-frequency trading (HFT) and market microstructure, 91–123, 100, 101, 103, 104, 107, 108–9, 111, 117, 121 and high-frequency data, 94–6 and optimised execution in dark pools via censored exploration, 93 and optimised trade execution via reinforcement learning, 92 and predicting price movement from order book state, 92–3 and price movement from order book state, predicting, 104–15 and reinforcement learning for optimised trade execution, 96–104 and smart order routing in dark pools, 115–22 Market Information Data Analytics System (MIDAS), 215–16 market microstructure: machine learning for, 91–123, 100, 101, 103, 104, 107, 108–9, 111, 117, 121 and high-frequency data, 94–6 and optimised execution in dark pools via censored exploration, 93 and optimised trade execution via reinforcement learning, 92 234 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 235 — #255 i i INDEX and predicting price movement from order book state, 92–3 and price movement from order book state, predicting, 104–15 and reinforcement learning for optimised trade execution, 96–104 and smart order routing in dark pools, 115–22 market stress: and central bank interventions, 79–80 and flash crash (2010), 77–8; see also flash crash and yen appreciation (2007), 77 and yen appreciation (2011), 78–9 Markets in Financial Instruments Directive (MiFID), 2, 21, 143, 216 microstructural volatility: in futures markets, 125–41, 133, 134, 136, 137, 138–9 experimental evaluation, 133–40 HDF5 file format, 127 maximum intermediate return, 131–2 parallelisation, 132–3 test data, 126–7 and volume-synchronised probability of informed trading, 128–31 MIDAS, see Market Information Data Analytics System N Nasdaq, CME’s joint project with, xvi O optimised trade execution, reinforcement learning for, 96–104 order book imbalance, 36–8 order-flow toxicity contagion model, 146–51 see also liquidity and toxicity contagion order protection and fair value, 38–41, 40 P pack hunters, 9 parallelisation, 132–3 price movement from order book state, predicting, 104–15 pro rata matching, 44, 59–62 probability of informed trading (PIN), 7 Project Hiberni, xvi Q quote danglers, 9 quote stuffers, 9 R regulation and high-frequency markets, 81, 207–9, 210, 212, 214 good and bad news concerning, 208–14 solutions, 214–28 and greater surveillance and coordination, proposals for, 215–18 and market rules, proposals to change, 218–25 and proposals to curtail HFT, 225–8 Regulation National Market System (Reg NMS), 2, 21, 143, 219 Regulation SCI, 216 reinforcement learning for optimised trade execution, 96–104 Rothschild, Nathan Mayer, 1 S smart order routing in dark pools, 115–22 spread/price–time priority, 82–3 235 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 236 — #256 i i HIGH-FREQUENCY TRADING T time, meaning of, and high-frequency trading, 5–7, 7 Tobin tax, 17, 81, 87 Tradeworx, 215 trading algorithms, 69–72 and algorithmic decision-making, 71–2 and algorithmic execution, 70–1 evolution of, 22–8 generations, 23–7 and indicator zoology, 27–8 see also algorithms trading frequencies, in currency market, 65–73, 72, 73; see also foreign-exchange markets trading signals: construction of, 31–8 and order book imbalance, 36–8 and timescales and weights, 31–3, 33 and trade sign autocorrelations, 34–6 transaction cost, and algorithms, 28–31 transitory price effects: approach to, illustrated, 192–203 daily estimation, 195–9 implementation shortfall calculations, 193–5 intra-day estimation, 199–203 and information shortfall, 185–206, 196, 197, 198, 199, 200, 202, 203 discussed, 186–9 implementation details, 204–5 and observed and efficient prices and pricing errors, 189–92 Treasury futures, 46, 47, 48, 51, 52, 55 V volume clock, 1–17, 7 and time, meaning of, 5–7 volume-synchronised probability of informed trading, 128–31 bars, 128 buckets, 129–30 cumulative distribution function, 130–1 volume classification, 128–9 W Walter, Elisse, 216 Waterloo, Battle of, 1 Y yen appreciation: 2007, 77 2011, 78–9 see also market stress 236 i i i i

The Water Will Come: Rising Seas, Sinking Cities, and the Remaking of the Civilized World by Jeff Goodell

"World Economic Forum" Davos, Airbnb, Anthropocene, carbon footprint, centre right, clean water, climate change refugee, creative destruction, data science, desegregation, Donald Trump, Dr. Strangelove, Elon Musk, failed state, fixed income, Frank Gehry, global pandemic, Google Earth, Higgs boson, illegal immigration, Intergovernmental Panel on Climate Change (IPCC), Large Hadron Collider, megacity, Murano, Venice glass, negative emissions, New Urbanism, ocean acidification, Paris climate accords, Pearl River Delta, Peter Thiel, planetary scale, Ray Kurzweil, Richard Florida, risk tolerance, Ronald Reagan, Silicon Valley, smart cities, South China Sea, space junk, urban planning, urban renewal, wikimedia commons

He is the child of Cuban refugees and, before he became an artist in his late twenties, had been a law school student, a street gang counselor, and a mental health counselor. He thinks of art as a continuation of that work—a way to raise awareness and make people think differently about the world around them. He has painted mangroves on city overpasses, created banners that celebrate the discovery of the Higgs boson at the Large Hadron Collider in Switzerland, and led a ten-year tree-planting campaign for schoolchildren in Miami. Given his background, it’s not surprising that Cortada was acutely aware of the parallels between political refugees of the past and climate refugees of the future. In his painting called Testamento, words from the will of a Cuban grandfather and words from the property deed of a Cuban-American granddaughter are depicted sinking beneath the waves.

The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences by Rob Kitchin

Bayesian statistics, business intelligence, business process, cellular automata, Celtic Tiger, cloud computing, collateralized debt obligation, conceptual framework, congestion charging, corporate governance, correlation does not imply causation, crowdsourcing, data science, discrete time, disruptive innovation, George Gilder, Google Earth, hype cycle, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, Large Hadron Collider, late capitalism, lifelogging, linked data, longitudinal study, machine readable, Masdar, means of production, Nate Silver, natural language processing, openstreetmap, pattern recognition, platform as a service, recommendation engine, RFID, semantic web, sentiment analysis, SimCity, slashdot, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, software as a service, statistical model, supply-chain management, technological solutionism, the scientific method, The Signal and the Noise by Nate Silver, transaction costs

When the Sloan Digital Sky Survey began operation in 2000, its telescope in New Mexico generated more observational data in the first couple of months than had previously been collected in the history of astronomy up to that point (Cukier 2010). In 2010, its archive was 140 TB of data, an amount soon to be collected every five days by the Large Synoptic Survey Telescope due to become operational in Chile in 2016 (Cukier 2010). Even more voluminous, the Large Hadron Collider at CERN, Europe’s particle-physics laboratory, generates 40 terabytes every second (The Economist 2010). In this, and other cases, the data generated are so vast that they neither get analysed nor stored, consisting instead of transient data. Indeed, the capacity to store all these data does not exist because, although storage is expanding rapidly, it is not keeping pace with data generation (Gantz et al. 2007; Manyika et al. 2011).

Underground, Overground by Andrew Martin

bank run, Boris Johnson, congestion charging, Crossrail, death from overwork, garden city movement, gentrification, Large Hadron Collider, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, plutocrats, Stephen Fry, traveling salesman, V2 rocket

The Circle generated urban myths: the man who died on it and then went round all day; the language school that conducted its classes on Circle trains, the collective daily fare being cheaper than office rental. In April 2010 the Independent reported: London is in talks with the European Organisation for Nuclear Research about the possibility of using the 23km tunnel of the Circle Line to house a new type of particle accelerator similar to the Large Hadron Collider in Geneva. Particle physicists believe the existing tunnel can be adapted to take a small-scale ‘atom smasher’ alongside the passenger line at a fraction of the cost of building a new tunnel elsewhere in Europe. (That was on 1 April, by the way.) Adding to the fun was the fact that the Circle had the worst train frequency of any line, the trouble being that it is not a line but a service, its trains being guests on the Metropolitan, District, Hammersmith & City – and often unwelcome guests, since if a Circle train went slow or broke down, it would block those other lines.

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

They are giving us, in effect, quick access to a vast collective awareness and a vast collective memory. At the same time, autonomous artificial intelligences have become world champions in a wide variety of “cerebral” games, such as chess and Go, and have taken over many sophisticated pattern-recognition tasks, such as reconstructing what happened during complex reactions at the Large Hadron Collider from a blizzard of emerging particle tracks to find new particles; or gathering clues from fuzzy X-ray, fMRI, and other types of images to diagnose medical problems. Where is this drive toward self-enhancement and innovation taking us? While the precise sequence of events and the timescale over which they’ll play out are impossible to predict (or, at least, beyond me), some basic considerations suggest that eventually the most powerful embodiments of mind will be quite different things from human brains as we know them today.

The Lost Decade: 2010–2020, and What Lies Ahead for Britain by Polly Toynbee, David Walker

banking crisis, battle of ideas, bike sharing, Boris Johnson, Brexit referendum, Bullingdon Club, call centre, car-free, centre right, collective bargaining, congestion charging, corporate governance, crony capitalism, Crossrail, David Attenborough, Dominic Cummings, Donald Trump, Downton Abbey, energy transition, Etonian, financial engineering, first-past-the-post, G4S, gender pay gap, gig economy, Gini coefficient, global village, green new deal, Greta Thunberg, high net worth, housing crisis, income inequality, industrial robot, Intergovernmental Panel on Climate Change (IPCC), James Dyson, Jeremy Corbyn, Large Hadron Collider, low interest rates, manufacturing employment, mass immigration, moral panic, mortgage debt, North Sea oil, offshore financial centre, opioid epidemic / opioid crisis, payday loans, pension reform, Phoebe Waller-Bridge, quantitative easing, Right to Buy, Saturday Night Live, selection bias, smart meter, Uber for X, ultra-processed food, urban renewal, working-age population

Life sciences were another bright example, future-orientated, highly dependent on public spending on universities and R&D. But they were bang in the path of hurricane Brexit, which hit investment, confidence and staffing. The withdrawal of the European Medicines Agency from London signalled shrinkage ahead. Great science was being done: in quantum technologies, in the UK’s contribution to CERN and the Large Hadron Collider (which was, of course, a large European collaboration in which scientific sovereignty was pooled, just like the EU). But where was the joining together with company investment plans, equity markets or other public policies? As we have noted elsewhere, it was as if the government acknowledged the question, but its answer was sketchy, underpowered, marginal.

Work! Consume! Die! by Boyle, Frankie

Boris Johnson, Desert Island Discs, Donald Trump, heat death of the universe, Jeffrey Epstein, Large Hadron Collider, Mark Zuckerberg, Marshall McLuhan, millennium bug, no-fly zone, Norman Mailer, offshore financial centre, open immigration, pez dispenser, Piper Alpha, presumed consent, Slavoj Žižek, Stephen Fry, Stephen Hawking, systems thinking, the medium is the message, trade route, WikiLeaks

There is a tense, silent ride into the galaxy until one of the oceans starts sobbing and breaks down … ‘You don’t know how terrible it was out there, we … we … had to eat Atlantis!’ The Sun even reported that sat navs and home freezers would no longer work. That’s some apocalyptic vision of the future they’ve created – a lawless land where men roam without direction trying to prepare their own Yorkshire pudding batter. The Large Hadron Collider started and the world didn’t end – which means I’m going to have to stop using that chat-up line, and start buying condoms. The collider will close for a year at the end of 2011 so that some design flaws can be fixed. Thankfully, those design flaws mean that 2011 starts next Friday and will last a week.

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

To give just a few brief examples: • Researchers working with genome data often need to perform sequencesimilarity searches, which means taking one very long string (representing a Summary | 63 DNA molecule) and matching it against a large database of strings that are simi‐ lar, but not identical. None of the databases described here can handle this kind of usage, which is why researchers have written specialized genome database software like GenBank [48]. • Particle physicists have been doing Big Data–style large-scale data analysis for decades, and projects like the Large Hadron Collider (LHC) now work with hun‐ dreds of petabytes! At such a scale custom solutions are required to stop the hardware cost from spiraling out of control [49]. • Full-text search is arguably a kind of data model that is frequently used alongside databases. Information retrieval is a large specialist subject that we won’t cover in great detail in this book, but we’ll touch on search indexes in Chapter 3 and Part III.

…

The opposite of bounded. 558 | Glossary Index A aborts (transactions), 222, 224 in two-phase commit, 356 performance of optimistic concurrency con‐ trol, 266 retrying aborted transactions, 231 abstraction, 21, 27, 222, 266, 321 access path (in network model), 37, 60 accidental complexity, removing, 21 accountability, 535 ACID properties (transactions), 90, 223 atomicity, 223, 228 consistency, 224, 529 durability, 226 isolation, 225, 228 acknowledgements (messaging), 445 active/active replication (see multi-leader repli‐ cation) active/passive replication (see leader-based rep‐ lication) ActiveMQ (messaging), 137, 444 distributed transaction support, 361 ActiveRecord (object-relational mapper), 30, 232 actor model, 138 (see also message-passing) comparison to Pregel model, 425 comparison to stream processing, 468 Advanced Message Queuing Protocol (see AMQP) aerospace systems, 6, 10, 305, 372 aggregation data cubes and materialized views, 101 in batch processes, 406 in stream processes, 466 aggregation pipeline query language, 48 Agile, 22 minimizing irreversibility, 414, 497 moving faster with confidence, 532 Unix philosophy, 394 agreement, 365 (see also consensus) Airflow (workflow scheduler), 402 Ajax, 131 Akka (actor framework), 139 algorithms algorithm correctness, 308 B-trees, 79-83 for distributed systems, 306 hash indexes, 72-75 mergesort, 76, 402, 405 red-black trees, 78 SSTables and LSM-trees, 76-79 all-to-all replication topologies, 175 AllegroGraph (database), 50 ALTER TABLE statement (SQL), 40, 111 Amazon Dynamo (database), 177 Amazon Web Services (AWS), 8 Kinesis Streams (messaging), 448 network reliability, 279 postmortems, 9 RedShift (database), 93 S3 (object storage), 398 checking data integrity, 530 amplification of bias, 534 of failures, 364, 495 Index | 559 of tail latency, 16, 207 write amplification, 84 AMQP (Advanced Message Queuing Protocol), 444 (see also messaging systems) comparison to log-based messaging, 448, 451 message ordering, 446 analytics, 90 comparison to transaction processing, 91 data warehousing (see data warehousing) parallel query execution in MPP databases, 415 predictive (see predictive analytics) relation to batch processing, 411 schemas for, 93-95 snapshot isolation for queries, 238 stream analytics, 466 using MapReduce, analysis of user activity events (example), 404 anti-caching (in-memory databases), 89 anti-entropy, 178 Apache ActiveMQ (see ActiveMQ) Apache Avro (see Avro) Apache Beam (see Beam) Apache BookKeeper (see BookKeeper) Apache Cassandra (see Cassandra) Apache CouchDB (see CouchDB) Apache Curator (see Curator) Apache Drill (see Drill) Apache Flink (see Flink) Apache Giraph (see Giraph) Apache Hadoop (see Hadoop) Apache HAWQ (see HAWQ) Apache HBase (see HBase) Apache Helix (see Helix) Apache Hive (see Hive) Apache Impala (see Impala) Apache Jena (see Jena) Apache Kafka (see Kafka) Apache Lucene (see Lucene) Apache MADlib (see MADlib) Apache Mahout (see Mahout) Apache Oozie (see Oozie) Apache Parquet (see Parquet) Apache Qpid (see Qpid) Apache Samza (see Samza) Apache Solr (see Solr) Apache Spark (see Spark) 560 | Index Apache Storm (see Storm) Apache Tajo (see Tajo) Apache Tez (see Tez) Apache Thrift (see Thrift) Apache ZooKeeper (see ZooKeeper) Apama (stream analytics), 466 append-only B-trees, 82, 242 append-only files (see logs) Application Programming Interfaces (APIs), 5, 27 for batch processing, 403 for change streams, 456 for distributed transactions, 361 for graph processing, 425 for services, 131-136 (see also services) evolvability, 136 RESTful, 133 SOAP, 133 application state (see state) approximate search (see similarity search) archival storage, data from databases, 131 arcs (see edges) arithmetic mean, 14 ASCII text, 119, 395 ASN.1 (schema language), 127 asynchronous networks, 278, 553 comparison to synchronous networks, 284 formal model, 307 asynchronous replication, 154, 553 conflict detection, 172 data loss on failover, 157 reads from asynchronous follower, 162 Asynchronous Transfer Mode (ATM), 285 atomic broadcast (see total order broadcast) atomic clocks (caesium clocks), 294, 295 (see also clocks) atomicity (concurrency), 553 atomic increment-and-get, 351 compare-and-set, 245, 327 (see also compare-and-set operations) replicated operations, 246 write operations, 243 atomicity (transactions), 223, 228, 553 atomic commit, 353 avoiding, 523, 528 blocking and nonblocking, 359 in stream processing, 360, 477 maintaining derived data, 453 for multi-object transactions, 229 for single-object writes, 230 auditability, 528-533 designing for, 531 self-auditing systems, 530 through immutability, 460 tools for auditable data systems, 532 availability, 8 (see also fault tolerance) in CAP theorem, 337 in service level agreements (SLAs), 15 Avro (data format), 122-127 code generation, 127 dynamically generated schemas, 126 object container files, 125, 131, 414 reader determining writer’s schema, 125 schema evolution, 123 use in Hadoop, 414 awk (Unix tool), 391 AWS (see Amazon Web Services) Azure (see Microsoft) B B-trees (indexes), 79-83 append-only/copy-on-write variants, 82, 242 branching factor, 81 comparison to LSM-trees, 83-85 crash recovery, 82 growing by splitting a page, 81 optimizations, 82 similarity to dynamic partitioning, 212 backpressure, 441, 553 in TCP, 282 backups database snapshot for replication, 156 integrity of, 530 snapshot isolation for, 238 use for ETL processes, 405 backward compatibility, 112 BASE, contrast to ACID, 223 bash shell (Unix), 70, 395, 503 batch processing, 28, 389-431, 553 combining with stream processing lambda architecture, 497 unifying technologies, 498 comparison to MPP databases, 414-418 comparison to stream processing, 464 comparison to Unix, 413-414 dataflow engines, 421-423 fault tolerance, 406, 414, 422, 442 for data integration, 494-498 graphs and iterative processing, 424-426 high-level APIs and languages, 403, 426-429 log-based messaging and, 451 maintaining derived state, 495 MapReduce and distributed filesystems, 397-413 (see also MapReduce) measuring performance, 13, 390 outputs, 411-413 key-value stores, 412 search indexes, 411 using Unix tools (example), 391-394 Bayou (database), 522 Beam (dataflow library), 498 bias, 534 big ball of mud, 20 Bigtable data model, 41, 99 binary data encodings, 115-128 Avro, 122-127 MessagePack, 116-117 Thrift and Protocol Buffers, 117-121 binary encoding based on schemas, 127 by network drivers, 128 binary strings, lack of support in JSON and XML, 114 BinaryProtocol encoding (Thrift), 118 Bitcask (storage engine), 72 crash recovery, 74 Bitcoin (cryptocurrency), 532 Byzantine fault tolerance, 305 concurrency bugs in exchanges, 233 bitmap indexes, 97 blockchains, 532 Byzantine fault tolerance, 305 blocking atomic commit, 359 Bloom (programming language), 504 Bloom filter (algorithm), 79, 466 BookKeeper (replicated log), 372 Bottled Water (change data capture), 455 bounded datasets, 430, 439, 553 (see also batch processing) bounded delays, 553 in networks, 285 process pauses, 298 broadcast hash joins, 409 Index | 561 brokerless messaging, 442 Brubeck (metrics aggregator), 442 BTM (transaction coordinator), 356 bulk synchronous parallel (BSP) model, 425 bursty network traffic patterns, 285 business data processing, 28, 90, 390 byte sequence, encoding data in, 112 Byzantine faults, 304-306, 307, 553 Byzantine fault-tolerant systems, 305, 532 Byzantine Generals Problem, 304 consensus algorithms and, 366 C caches, 89, 553 and materialized views, 101 as derived data, 386, 499-504 database as cache of transaction log, 460 in CPUs, 99, 338, 428 invalidation and maintenance, 452, 467 linearizability, 324 CAP theorem, 336-338, 554 Cascading (batch processing), 419, 427 hash joins, 409 workflows, 403 cascading failures, 9, 214, 281 Cascalog (batch processing), 60 Cassandra (database) column-family data model, 41, 99 compaction strategy, 79 compound primary key, 204 gossip protocol, 216 hash partitioning, 203-205 last-write-wins conflict resolution, 186, 292 leaderless replication, 177 linearizability, lack of, 335 log-structured storage, 78 multi-datacenter support, 184 partitioning scheme, 213 secondary indexes, 207 sloppy quorums, 184 cat (Unix tool), 391 causal context, 191 (see also causal dependencies) causal dependencies, 186-191 capturing, 191, 342, 494, 514 by total ordering, 493 causal ordering, 339 in transactions, 262 sending message to friends (example), 494 562 | Index causality, 554 causal ordering, 339-343 linearizability and, 342 total order consistent with, 344, 345 consistency with, 344-347 consistent snapshots, 340 happens-before relationship, 186 in serializable transactions, 262-265 mismatch with clocks, 292 ordering events to capture, 493 violations of, 165, 176, 292, 340 with synchronized clocks, 294 CEP (see complex event processing) certificate transparency, 532 chain replication, 155 linearizable reads, 351 change data capture, 160, 454 API support for change streams, 456 comparison to event sourcing, 457 implementing, 454 initial snapshot, 455 log compaction, 456 changelogs, 460 change data capture, 454 for operator state, 479 generating with triggers, 455 in stream joins, 474 log compaction, 456 maintaining derived state, 452 Chaos Monkey, 7, 280 checkpointing in batch processors, 422, 426 in high-performance computing, 275 in stream processors, 477, 523 chronicle data model, 458 circuit-switched networks, 284 circular buffers, 450 circular replication topologies, 175 clickstream data, analysis of, 404 clients calling services, 131 pushing state changes to, 512 request routing, 214 stateful and offline-capable, 170, 511 clocks, 287-299 atomic (caesium) clocks, 294, 295 confidence interval, 293-295 for global snapshots, 294 logical (see logical clocks) skew, 291-294, 334 slewing, 289 synchronization and accuracy, 289-291 synchronization using GPS, 287, 290, 294, 295 time-of-day versus monotonic clocks, 288 timestamping events, 471 cloud computing, 146, 275 need for service discovery, 372 network glitches, 279 shared resources, 284 single-machine reliability, 8 Cloudera Impala (see Impala) clustered indexes, 86 CODASYL model, 36 (see also network model) code generation with Avro, 127 with Thrift and Protocol Buffers, 118 with WSDL, 133 collaborative editing multi-leader replication and, 170 column families (Bigtable), 41, 99 column-oriented storage, 95-101 column compression, 97 distinction between column families and, 99 in batch processors, 428 Parquet, 96, 131, 414 sort order in, 99-100 vectorized processing, 99, 428 writing to, 101 comma-separated values (see CSV) command query responsibility segregation (CQRS), 462 commands (event sourcing), 459 commits (transactions), 222 atomic commit, 354-355 (see also atomicity; transactions) read committed isolation, 234 three-phase commit (3PC), 359 two-phase commit (2PC), 355-359 commutative operations, 246 compaction of changelogs, 456 (see also log compaction) for stream operator state, 479 of log-structured storage, 73 issues with, 84 size-tiered and leveled approaches, 79 CompactProtocol encoding (Thrift), 119 compare-and-set operations, 245, 327 implementing locks, 370 implementing uniqueness constraints, 331 implementing with total order broadcast, 350 relation to consensus, 335, 350, 352, 374 relation to transactions, 230 compatibility, 112, 128 calling services, 136 properties of encoding formats, 139 using databases, 129-131 using message-passing, 138 compensating transactions, 355, 461, 526 complex event processing (CEP), 465 complexity distilling in theoretical models, 310 hiding using abstraction, 27 of software systems, managing, 20 composing data systems (see unbundling data‐ bases) compute-intensive applications, 3, 275 concatenated indexes, 87 in Cassandra, 204 Concord (stream processor), 466 concurrency actor programming model, 138, 468 (see also message-passing) bugs from weak transaction isolation, 233 conflict resolution, 171, 174 detecting concurrent writes, 184-191 dual writes, problems with, 453 happens-before relationship, 186 in replicated systems, 161-191, 324-338 lost updates, 243 multi-version concurrency control (MVCC), 239 optimistic concurrency control, 261 ordering of operations, 326, 341 reducing, through event logs, 351, 462, 507 time and relativity, 187 transaction isolation, 225 write skew (transaction isolation), 246-251 conflict-free replicated datatypes (CRDTs), 174 conflicts conflict detection, 172 causal dependencies, 186, 342 in consensus algorithms, 368 in leaderless replication, 184 Index | 563 in log-based systems, 351, 521 in nonlinearizable systems, 343 in serializable snapshot isolation (SSI), 264 in two-phase commit, 357, 364 conflict resolution automatic conflict resolution, 174 by aborting transactions, 261 by apologizing, 527 convergence, 172-174 in leaderless systems, 190 last write wins (LWW), 186, 292 using atomic operations, 246 using custom logic, 173 determining what is a conflict, 174, 522 in multi-leader replication, 171-175 avoiding conflicts, 172 lost updates, 242-246 materializing, 251 relation to operation ordering, 339 write skew (transaction isolation), 246-251 congestion (networks) avoidance, 282 limiting accuracy of clocks, 293 queueing delays, 282 consensus, 321, 364-375, 554 algorithms, 366-368 preventing split brain, 367 safety and liveness properties, 365 using linearizable operations, 351 cost of, 369 distributed transactions, 352-375 in practice, 360-364 two-phase commit, 354-359 XA transactions, 361-364 impossibility of, 353 membership and coordination services, 370-373 relation to compare-and-set, 335, 350, 352, 374 relation to replication, 155, 349 relation to uniqueness constraints, 521 consistency, 224, 524 across different databases, 157, 452, 462, 492 causal, 339-348, 493 consistent prefix reads, 165-167 consistent snapshots, 156, 237-242, 294, 455, 500 (see also snapshots) 564 | Index crash recovery, 82 enforcing constraints (see constraints) eventual, 162, 322 (see also eventual consistency) in ACID transactions, 224, 529 in CAP theorem, 337 linearizability, 324-338 meanings of, 224 monotonic reads, 164-165 of secondary indexes, 231, 241, 354, 491, 500 ordering guarantees, 339-352 read-after-write, 162-164 sequential, 351 strong (see linearizability) timeliness and integrity, 524 using quorums, 181, 334 consistent hashing, 204 consistent prefix reads, 165 constraints (databases), 225, 248 asynchronously checked, 526 coordination avoidance, 527 ensuring idempotence, 519 in log-based systems, 521-524 across multiple partitions, 522 in two-phase commit, 355, 357 relation to consensus, 374, 521 relation to event ordering, 347 requiring linearizability, 330 Consul (service discovery), 372 consumers (message streams), 137, 440 backpressure, 441 consumer offsets in logs, 449 failures, 445, 449 fan-out, 11, 445, 448 load balancing, 444, 448 not keeping up with producers, 441, 450, 502 context switches, 14, 297 convergence (conflict resolution), 172-174, 322 coordination avoidance, 527 cross-datacenter, 168, 493 cross-partition ordering, 256, 294, 348, 523 services, 330, 370-373 coordinator (in 2PC), 356 failure, 358 in XA transactions, 361-364 recovery, 363 copy-on-write (B-trees), 82, 242 CORBA (Common Object Request Broker Architecture), 134 correctness, 6 auditability, 528-533 Byzantine fault tolerance, 305, 532 dealing with partial failures, 274 in log-based systems, 521-524 of algorithm within system model, 308 of compensating transactions, 355 of consensus, 368 of derived data, 497, 531 of immutable data, 461 of personal data, 535, 540 of time, 176, 289-295 of transactions, 225, 515, 529 timeliness and integrity, 524-528 corruption of data detecting, 519, 530-533 due to pathological memory access, 529 due to radiation, 305 due to split brain, 158, 302 due to weak transaction isolation, 233 formalization in consensus, 366 integrity as absence of, 524 network packets, 306 on disks, 227 preventing using write-ahead logs, 82 recovering from, 414, 460 Couchbase (database) durability, 89 hash partitioning, 203-204, 211 rebalancing, 213 request routing, 216 CouchDB (database) B-tree storage, 242 change feed, 456 document data model, 31 join support, 34 MapReduce support, 46, 400 replication, 170, 173 covering indexes, 86 CPUs cache coherence and memory barriers, 338 caching and pipelining, 99, 428 increasing parallelism, 43 CRDTs (see conflict-free replicated datatypes) CREATE INDEX statement (SQL), 85, 500 credit rating agencies, 535 Crunch (batch processing), 419, 427 hash joins, 409 sharded joins, 408 workflows, 403 cryptography defense against attackers, 306 end-to-end encryption and authentication, 519, 543 proving integrity of data, 532 CSS (Cascading Style Sheets), 44 CSV (comma-separated values), 70, 114, 396 Curator (ZooKeeper recipes), 330, 371 curl (Unix tool), 135, 397 cursor stability, 243 Cypher (query language), 52 comparison to SPARQL, 59 D data corruption (see corruption of data) data cubes, 102 data formats (see encoding) data integration, 490-498, 543 batch and stream processing, 494-498 lambda architecture, 497 maintaining derived state, 495 reprocessing data, 496 unifying, 498 by unbundling databases, 499-515 comparison to federated databases, 501 combining tools by deriving data, 490-494 derived data versus distributed transac‐ tions, 492 limits of total ordering, 493 ordering events to capture causality, 493 reasoning about dataflows, 491 need for, 385 data lakes, 415 data locality (see locality) data models, 27-64 graph-like models, 49-63 Datalog language, 60-63 property graphs, 50 RDF and triple-stores, 55-59 query languages, 42-48 relational model versus document model, 28-42 data protection regulations, 542 data systems, 3 about, 4 Index | 565 concerns when designing, 5 future of, 489-544 correctness, constraints, and integrity, 515-533 data integration, 490-498 unbundling databases, 499-515 heterogeneous, keeping in sync, 452 maintainability, 18-22 possible faults in, 221 reliability, 6-10 hardware faults, 7 human errors, 9 importance of, 10 software errors, 8 scalability, 10-18 unreliable clocks, 287-299 data warehousing, 91-95, 554 comparison to data lakes, 415 ETL (extract-transform-load), 92, 416, 452 keeping data systems in sync, 452 schema design, 93 slowly changing dimension (SCD), 476 data-intensive applications, 3 database triggers (see triggers) database-internal distributed transactions, 360, 364, 477 databases archival storage, 131 comparison of message brokers to, 443 dataflow through, 129 end-to-end argument for, 519-520 checking integrity, 531 inside-out, 504 (see also unbundling databases) output from batch workflows, 412 relation to event streams, 451-464 (see also changelogs) API support for change streams, 456, 506 change data capture, 454-457 event sourcing, 457-459 keeping systems in sync, 452-453 philosophy of immutable events, 459-464 unbundling, 499-515 composing data storage technologies, 499-504 designing applications around dataflow, 504-509 566 | Index observing derived state, 509-515 datacenters geographically distributed, 145, 164, 278, 493 multi-tenancy and shared resources, 284 network architecture, 276 network faults, 279 replication across multiple, 169 leaderless replication, 184 multi-leader replication, 168, 335 dataflow, 128-139, 504-509 correctness of dataflow systems, 525 differential, 504 message-passing, 136-139 reasoning about, 491 through databases, 129 through services, 131-136 dataflow engines, 421-423 comparison to stream processing, 464 directed acyclic graphs (DAG), 424 partitioning, approach to, 429 support for declarative queries, 427 Datalog (query language), 60-63 datatypes binary strings in XML and JSON, 114 conflict-free, 174 in Avro encodings, 122 in Thrift and Protocol Buffers, 121 numbers in XML and JSON, 114 Datomic (database) B-tree storage, 242 data model, 50, 57 Datalog query language, 60 excision (deleting data), 463 languages for transactions, 255 serial execution of transactions, 253 deadlocks detection, in two-phase commit (2PC), 364 in two-phase locking (2PL), 258 Debezium (change data capture), 455 declarative languages, 42, 554 Bloom, 504 CSS and XSL, 44 Cypher, 52 Datalog, 60 for batch processing, 427 recursive SQL queries, 53 relational algebra and SQL, 42 SPARQL, 59 delays bounded network delays, 285 bounded process pauses, 298 unbounded network delays, 282 unbounded process pauses, 296 deleting data, 463 denormalization (data representation), 34, 554 costs, 39 in derived data systems, 386 materialized views, 101 updating derived data, 228, 231, 490 versus normalization, 462 derived data, 386, 439, 554 from change data capture, 454 in event sourcing, 458-458 maintaining derived state through logs, 452-457, 459-463 observing, by subscribing to streams, 512 outputs of batch and stream processing, 495 through application code, 505 versus distributed transactions, 492 deterministic operations, 255, 274, 554 accidental nondeterminism, 423 and fault tolerance, 423, 426 and idempotence, 478, 492 computing derived data, 495, 526, 531 in state machine replication, 349, 452, 458 joins, 476 DevOps, 394 differential dataflow, 504 dimension tables, 94 dimensional modeling (see star schemas) directed acyclic graphs (DAGs), 424 dirty reads (transaction isolation), 234 dirty writes (transaction isolation), 235 discrimination, 534 disks (see hard disks) distributed actor frameworks, 138 distributed filesystems, 398-399 decoupling from query engines, 417 indiscriminately dumping data into, 415 use by MapReduce, 402 distributed systems, 273-312, 554 Byzantine faults, 304-306 cloud versus supercomputing, 275 detecting network faults, 280 faults and partial failures, 274-277 formalization of consensus, 365 impossibility results, 338, 353 issues with failover, 157 limitations of distributed transactions, 363 multi-datacenter, 169, 335 network problems, 277-286 quorums, relying on, 301 reasons for using, 145, 151 synchronized clocks, relying on, 291-295 system models, 306-310 use of clocks and time, 287 distributed transactions (see transactions) Django (web framework), 232 DNS (Domain Name System), 216, 372 Docker (container manager), 506 document data model, 30-42 comparison to relational model, 38-42 document references, 38, 403 document-oriented databases, 31 many-to-many relationships and joins, 36 multi-object transactions, need for, 231 versus relational model convergence of models, 41 data locality, 41 document-partitioned indexes, 206, 217, 411 domain-driven design (DDD), 457 DRBD (Distributed Replicated Block Device), 153 drift (clocks), 289 Drill (query engine), 93 Druid (database), 461 Dryad (dataflow engine), 421 dual writes, problems with, 452, 507 duplicates, suppression of, 517 (see also idempotence) using a unique ID, 518, 522 durability (transactions), 226, 554 duration (time), 287 measurement with monotonic clocks, 288 dynamic partitioning, 212 dynamically typed languages analogy to schema-on-read, 40 code generation and, 127 Dynamo-style databases (see leaderless replica‐ tion) E edges (in graphs), 49, 403 property graph model, 50 edit distance (full-text search), 88 effectively-once semantics, 476, 516 Index | 567 (see also exactly-once semantics) preservation of integrity, 525 elastic systems, 17 Elasticsearch (search server) document-partitioned indexes, 207 partition rebalancing, 211 percolator (stream search), 467 usage example, 4 use of Lucene, 79 ElephantDB (database), 413 Elm (programming language), 504, 512 encodings (data formats), 111-128 Avro, 122-127 binary variants of JSON and XML, 115 compatibility, 112 calling services, 136 using databases, 129-131 using message-passing, 138 defined, 113 JSON, XML, and CSV, 114 language-specific formats, 113 merits of schemas, 127 representations of data, 112 Thrift and Protocol Buffers, 117-121 end-to-end argument, 277, 519-520 checking integrity, 531 publish/subscribe streams, 512 enrichment (stream), 473 Enterprise JavaBeans (EJB), 134 entities (see vertices) epoch (consensus algorithms), 368 epoch (Unix timestamps), 288 equi-joins, 403 erasure coding (error correction), 398 Erlang OTP (actor framework), 139 error handling for network faults, 280 in transactions, 231 error-correcting codes, 277, 398 Esper (CEP engine), 466 etcd (coordination service), 370-373 linearizable operations, 333 locks and leader election, 330 quorum reads, 351 service discovery, 372 use of Raft algorithm, 349, 353 Ethereum (blockchain), 532 Ethernet (networks), 276, 278, 285 packet checksums, 306, 519 568 | Index Etherpad (collaborative editor), 170 ethics, 533-543 code of ethics and professional practice, 533 legislation and self-regulation, 542 predictive analytics, 533-536 amplifying bias, 534 feedback loops, 536 privacy and tracking, 536-543 consent and freedom of choice, 538 data as assets and power, 540 meaning of privacy, 539 surveillance, 537 respect, dignity, and agency, 543, 544 unintended consequences, 533, 536 ETL (extract-transform-load), 92, 405, 452, 554 use of Hadoop for, 416 event sourcing, 457-459 commands and events, 459 comparison to change data capture, 457 comparison to lambda architecture, 497 deriving current state from event log, 458 immutability and auditability, 459, 531 large, reliable data systems, 519, 526 Event Store (database), 458 event streams (see streams) events, 440 deciding on total order of, 493 deriving views from event log, 461 difference to commands, 459 event time versus processing time, 469, 477, 498 immutable, advantages of, 460, 531 ordering to capture causality, 493 reads as, 513 stragglers, 470, 498 timestamp of, in stream processing, 471 EventSource (browser API), 512 eventual consistency, 152, 162, 308, 322 (see also conflicts) and perpetual inconsistency, 525 evolvability, 21, 111 calling services, 136 graph-structured data, 52 of databases, 40, 129-131, 461, 497 of message-passing, 138 reprocessing data, 496, 498 schema evolution in Avro, 123 schema evolution in Thrift and Protocol Buffers, 120 schema-on-read, 39, 111, 128 exactly-once semantics, 360, 476, 516 parity with batch processors, 498 preservation of integrity, 525 exclusive mode (locks), 258 eXtended Architecture transactions (see XA transactions) extract-transform-load (see ETL) F Facebook Presto (query engine), 93 React, Flux, and Redux (user interface libra‐ ries), 512 social graphs, 49 Wormhole (change data capture), 455 fact tables, 93 failover, 157, 554 (see also leader-based replication) in leaderless replication, absence of, 178 leader election, 301, 348, 352 potential problems, 157 failures amplification by distributed transactions, 364, 495 failure detection, 280 automatic rebalancing causing cascading failures, 214 perfect failure detectors, 359 timeouts and unbounded delays, 282, 284 using ZooKeeper, 371 faults versus, 7 partial failures in distributed systems, 275-277, 310 fan-out (messaging systems), 11, 445 fault tolerance, 6-10, 555 abstractions for, 321 formalization in consensus, 365-369 use of replication, 367 human fault tolerance, 414 in batch processing, 406, 414, 422, 425 in log-based systems, 520, 524-526 in stream processing, 476-479 atomic commit, 477 idempotence, 478 maintaining derived state, 495 microbatching and checkpointing, 477 rebuilding state after a failure, 478 of distributed transactions, 362-364 transaction atomicity, 223, 354-361 faults, 6 Byzantine faults, 304-306 failures versus, 7 handled by transactions, 221 handling in supercomputers and cloud computing, 275 hardware, 7 in batch processing versus distributed data‐ bases, 417 in distributed systems, 274-277 introducing deliberately, 7, 280 network faults, 279-281 asymmetric faults, 300 detecting, 280 tolerance of, in multi-leader replication, 169 software errors, 8 tolerating (see fault tolerance) federated databases, 501 fence (CPU instruction), 338 fencing (preventing split brain), 158, 302-304 generating fencing tokens, 349, 370 properties of fencing tokens, 308 stream processors writing to databases, 478, 517 Fibre Channel (networks), 398 field tags (Thrift and Protocol Buffers), 119-121 file descriptors (Unix), 395 financial data, 460 Firebase (database), 456 Flink (processing framework), 421-423 dataflow APIs, 427 fault tolerance, 422, 477, 479 Gelly API (graph processing), 425 integration of batch and stream processing, 495, 498 machine learning, 428 query optimizer, 427 stream processing, 466 flow control, 282, 441, 555 FLP result (on consensus), 353 FlumeJava (dataflow library), 403, 427 followers, 152, 555 (see also leader-based replication) foreign keys, 38, 403 forward compatibility, 112 forward decay (algorithm), 16 Index | 569 Fossil (version control system), 463 shunning (deleting data), 463 FoundationDB (database) serializable transactions, 261, 265, 364 fractal trees, 83 full table scans, 403 full-text search, 555 and fuzzy indexes, 88 building search indexes, 411 Lucene storage engine, 79 functional reactive programming (FRP), 504 functional requirements, 22 futures (asynchronous operations), 135 fuzzy search (see similarity search) G garbage collection immutability and, 463 process pauses for, 14, 296-299, 301 (see also process pauses) genome analysis, 63, 429 geographically distributed datacenters, 145, 164, 278, 493 geospatial indexes, 87 Giraph (graph processing), 425 Git (version control system), 174, 342, 463 GitHub, postmortems, 157, 158, 309 global indexes (see term-partitioned indexes) GlusterFS (distributed filesystem), 398 GNU Coreutils (Linux), 394 GoldenGate (change data capture), 161, 170, 455 (see also Oracle) Google Bigtable (database) data model (see Bigtable data model) partitioning scheme, 199, 202 storage layout, 78 Chubby (lock service), 370 Cloud Dataflow (stream processor), 466, 477, 498 (see also Beam) Cloud Pub/Sub (messaging), 444, 448 Docs (collaborative editor), 170 Dremel (query engine), 93, 96 FlumeJava (dataflow library), 403, 427 GFS (distributed file system), 398 gRPC (RPC framework), 135 MapReduce (batch processing), 390 570 | Index (see also MapReduce) building search indexes, 411 task preemption, 418 Pregel (graph processing), 425 Spanner (see Spanner) TrueTime (clock API), 294 gossip protocol, 216 government use of data, 541 GPS (Global Positioning System) use for clock synchronization, 287, 290, 294, 295 GraphChi (graph processing), 426 graphs, 555 as data models, 49-63 example of graph-structured data, 49 property graphs, 50 RDF and triple-stores, 55-59 versus the network model, 60 processing and analysis, 424-426 fault tolerance, 425 Pregel processing model, 425 query languages Cypher, 52 Datalog, 60-63 recursive SQL queries, 53 SPARQL, 59-59 Gremlin (graph query language), 50 grep (Unix tool), 392 GROUP BY clause (SQL), 406 grouping records in MapReduce, 406 handling skew, 407 H Hadoop (data infrastructure) comparison to distributed databases, 390 comparison to MPP databases, 414-418 comparison to Unix, 413-414, 499 diverse processing models in ecosystem, 417 HDFS distributed filesystem (see HDFS) higher-level tools, 403 join algorithms, 403-410 (see also MapReduce) MapReduce (see MapReduce) YARN (see YARN) happens-before relationship, 340 capturing, 187 concurrency and, 186 hard disks access patterns, 84 detecting corruption, 519, 530 faults in, 7, 227 sequential write throughput, 75, 450 hardware faults, 7 hash indexes, 72-75 broadcast hash joins, 409 partitioned hash joins, 409 hash partitioning, 203-205, 217 consistent hashing, 204 problems with hash mod N, 210 range queries, 204 suitable hash functions, 203 with fixed number of partitions, 210 HAWQ (database), 428 HBase (database) bug due to lack of fencing, 302 bulk loading, 413 column-family data model, 41, 99 dynamic partitioning, 212 key-range partitioning, 202 log-structured storage, 78 request routing, 216 size-tiered compaction, 79 use of HDFS, 417 use of ZooKeeper, 370 HDFS (Hadoop Distributed File System), 398-399 (see also distributed filesystems) checking data integrity, 530 decoupling from query engines, 417 indiscriminately dumping data into, 415 metadata about datasets, 410 NameNode, 398 use by Flink, 479 use by HBase, 212 use by MapReduce, 402 HdrHistogram (numerical library), 16 head (Unix tool), 392 head vertex (property graphs), 51 head-of-line blocking, 15 heap files (databases), 86 Helix (cluster manager), 216 heterogeneous distributed transactions, 360, 364 heuristic decisions (in 2PC), 363 Hibernate (object-relational mapper), 30 hierarchical model, 36 high availability (see fault tolerance) high-frequency trading, 290, 299 high-performance computing (HPC), 275 hinted handoff, 183 histograms, 16 Hive (query engine), 419, 427 for data warehouses, 93 HCatalog and metastore, 410 map-side joins, 409 query optimizer, 427 skewed joins, 408 workflows, 403 Hollerith machines, 390 hopping windows (stream processing), 472 (see also windows) horizontal scaling (see scaling out) HornetQ (messaging), 137, 444 distributed transaction support, 361 hot spots, 201 due to celebrities, 205 for time-series data, 203 in batch processing, 407 relieving, 205 hot standbys (see leader-based replication) HTTP, use in APIs (see services) human errors, 9, 279, 414 HyperDex (database), 88 HyperLogLog (algorithm), 466 I I/O operations, waiting for, 297 IBM DB2 (database) distributed transaction support, 361 recursive query support, 54 serializable isolation, 242, 257 XML and JSON support, 30, 42 electromechanical card-sorting machines, 390 IMS (database), 36 imperative query APIs, 46 InfoSphere Streams (CEP engine), 466 MQ (messaging), 444 distributed transaction support, 361 System R (database), 222 WebSphere (messaging), 137 idempotence, 134, 478, 555 by giving operations unique IDs, 518, 522 idempotent operations, 517 immutability advantages of, 460, 531 Index | 571 deriving state from event log, 459-464 for crash recovery, 75 in B-trees, 82, 242 in event sourcing, 457 inputs to Unix commands, 397 limitations of, 463 Impala (query engine) for data warehouses, 93 hash joins, 409 native code generation, 428 use of HDFS, 417 impedance mismatch, 29 imperative languages, 42 setting element styles (example), 45 in doubt (transaction status), 358 holding locks, 362 orphaned transactions, 363 in-memory databases, 88 durability, 227 serial transaction execution, 253 incidents cascading failures, 9 crashes due to leap seconds, 290 data corruption and financial losses due to concurrency bugs, 233 data corruption on hard disks, 227 data loss due to last-write-wins, 173, 292 data on disks unreadable, 309 deleted items reappearing, 174 disclosure of sensitive data due to primary key reuse, 157 errors in transaction serializability, 529 gigabit network interface with 1 Kb/s throughput, 311 network faults, 279 network interface dropping only inbound packets, 279 network partitions and whole-datacenter failures, 275 poor handling of network faults, 280 sending message to ex-partner, 494 sharks biting undersea cables, 279 split brain due to 1-minute packet delay, 158, 279 vibrations in server rack, 14 violation of uniqueness constraint, 529 indexes, 71, 555 and snapshot isolation, 241 as derived data, 386, 499-504 572 | Index B-trees, 79-83 building in batch processes, 411 clustered, 86 comparison of B-trees and LSM-trees, 83-85 concatenated, 87 covering (with included columns), 86 creating, 500 full-text search, 88 geospatial, 87 hash, 72-75 index-range locking, 260 multi-column, 87 partitioning and secondary indexes, 206-209, 217 secondary, 85 (see also secondary indexes) problems with dual writes, 452, 491 SSTables and LSM-trees, 76-79 updating when data changes, 452, 467 Industrial Revolution, 541 InfiniBand (networks), 285 InfiniteGraph (database), 50 InnoDB (storage engine) clustered index on primary key, 86 not preventing lost updates, 245 preventing write skew, 248, 257 serializable isolation, 257 snapshot isolation support, 239 inside-out databases, 504 (see also unbundling databases) integrating different data systems (see data integration) integrity, 524 coordination-avoiding data systems, 528 correctness of dataflow systems, 525 in consensus formalization, 365 integrity checks, 530 (see also auditing) end-to-end, 519, 531 use of snapshot isolation, 238 maintaining despite software bugs, 529 Interface Definition Language (IDL), 117, 122 intermediate state, materialization of, 420-423 internet services, systems for implementing, 275 invariants, 225 (see also constraints) inversion of control, 396 IP (Internet Protocol) unreliability of, 277 ISDN (Integrated Services Digital Network), 284 isolation (in transactions), 225, 228, 555 correctness and, 515 for single-object writes, 230 serializability, 251-266 actual serial execution, 252-256 serializable snapshot isolation (SSI), 261-266 two-phase locking (2PL), 257-261 violating, 228 weak isolation levels, 233-251 preventing lost updates, 242-246 read committed, 234-237 snapshot isolation, 237-242 iterative processing, 424-426 J Java Database Connectivity (JDBC) distributed transaction support, 361 network drivers, 128 Java Enterprise Edition (EE), 134, 356, 361 Java Message Service (JMS), 444 (see also messaging systems) comparison to log-based messaging, 448, 451 distributed transaction support, 361 message ordering, 446 Java Transaction API (JTA), 355, 361 Java Virtual Machine (JVM) bytecode generation, 428 garbage collection pauses, 296 process reuse in batch processors, 422 JavaScript in MapReduce querying, 46 setting element styles (example), 45 use in advanced queries, 48 Jena (RDF framework), 57 Jepsen (fault tolerance testing), 515 jitter (network delay), 284 joins, 555 by index lookup, 403 expressing as relational operators, 427 in relational and document databases, 34 MapReduce map-side joins, 408-410 broadcast hash joins, 409 merge joins, 410 partitioned hash joins, 409 MapReduce reduce-side joins, 403-408 handling skew, 407 sort-merge joins, 405 parallel execution of, 415 secondary indexes and, 85 stream joins, 472-476 stream-stream join, 473 stream-table join, 473 table-table join, 474 time-dependence of, 475 support in document databases, 42 JOTM (transaction coordinator), 356 JSON Avro schema representation, 122 binary variants, 115 for application data, issues with, 114 in relational databases, 30, 42 representing a résumé (example), 31 Juttle (query language), 504 K k-nearest neighbors, 429 Kafka (messaging), 137, 448 Kafka Connect (database integration), 457, 461 Kafka Streams (stream processor), 466, 467 fault tolerance, 479 leader-based replication, 153 log compaction, 456, 467 message offsets, 447, 478 request routing, 216 transaction support, 477 usage example, 4 Ketama (partitioning library), 213 key-value stores, 70 as batch process output, 412 hash indexes, 72-75 in-memory, 89 partitioning, 201-205 by hash of key, 203, 217 by key range, 202, 217 dynamic partitioning, 212 skew and hot spots, 205 Kryo (Java), 113 Kubernetes (cluster manager), 418, 506 L lambda architecture, 497 Lamport timestamps, 345 Index | 573 Large Hadron Collider (LHC), 64 last write wins (LWW), 173, 334 discarding concurrent writes, 186 problems with, 292 prone to lost updates, 246 late binding, 396 latency instability under two-phase locking, 259 network latency and resource utilization, 286 response time versus, 14 tail latency, 15, 207 leader-based replication, 152-161 (see also replication) failover, 157, 301 handling node outages, 156 implementation of replication logs change data capture, 454-457 (see also changelogs) statement-based, 158 trigger-based replication, 161 write-ahead log (WAL) shipping, 159 linearizability of operations, 333 locking and leader election, 330 log sequence number, 156, 449 read-scaling architecture, 161 relation to consensus, 367 setting up new followers, 155 synchronous versus asynchronous, 153-155 leaderless replication, 177-191 (see also replication) detecting concurrent writes, 184-191 capturing happens-before relationship, 187 happens-before relationship and concur‐ rency, 186 last write wins, 186 merging concurrently written values, 190 version vectors, 191 multi-datacenter, 184 quorums, 179-182 consistency limitations, 181-183, 334 sloppy quorums and hinted handoff, 183 read repair and anti-entropy, 178 leap seconds, 8, 290 in time-of-day clocks, 288 leases, 295 implementation with ZooKeeper, 370 574 | Index need for fencing, 302 ledgers, 460 distributed ledger technologies, 532 legacy systems, maintenance of, 18 less (Unix tool), 397 LevelDB (storage engine), 78 leveled compaction, 79 Levenshtein automata, 88 limping (partial failure), 311 linearizability, 324-338, 555 cost of, 335-338 CAP theorem, 336 memory on multi-core CPUs, 338 definition, 325-329 implementing with total order broadcast, 350 in ZooKeeper, 370 of derived data systems, 492, 524 avoiding coordination, 527 of different replication methods, 332-335 using quorums, 334 relying on, 330-332 constraints and uniqueness, 330 cross-channel timing dependencies, 331 locking and leader election, 330 stronger than causal consistency, 342 using to implement total order broadcast, 351 versus serializability, 329 LinkedIn Azkaban (workflow scheduler), 402 Databus (change data capture), 161, 455 Espresso (database), 31, 126, 130, 153, 216 Helix (cluster manager) (see Helix) profile (example), 30 reference to company entity (example), 34 Rest.li (RPC framework), 135 Voldemort (database) (see Voldemort) Linux, leap second bug, 8, 290 liveness properties, 308 LMDB (storage engine), 82, 242 load approaches to coping with, 17 describing, 11 load testing, 16 load balancing (messaging), 444 local indexes (see document-partitioned indexes) locality (data access), 32, 41, 555 in batch processing, 400, 405, 421 in stateful clients, 170, 511 in stream processing, 474, 478, 508, 522 location transparency, 134 in the actor model, 138 locks, 556 deadlock, 258 distributed locking, 301-304, 330 fencing tokens, 303 implementation with ZooKeeper, 370 relation to consensus, 374 for transaction isolation in snapshot isolation, 239 in two-phase locking (2PL), 257-261 making operations atomic, 243 performance, 258 preventing dirty writes, 236 preventing phantoms with index-range locks, 260, 265 read locks (shared mode), 236, 258 shared mode and exclusive mode, 258 in two-phase commit (2PC) deadlock detection, 364 in-doubt transactions holding locks, 362 materializing conflicts with, 251 preventing lost updates by explicit locking, 244 log sequence number, 156, 449 logic programming languages, 504 logical clocks, 293, 343, 494 for read-after-write consistency, 164 logical logs, 160 logs (data structure), 71, 556 advantages of immutability, 460 compaction, 73, 79, 456, 460 for stream operator state, 479 creating using total order broadcast, 349 implementing uniqueness constraints, 522 log-based messaging, 446-451 comparison to traditional messaging, 448, 451 consumer offsets, 449 disk space usage, 450 replaying old messages, 451, 496, 498 slow consumers, 450 using logs for message storage, 447 log-structured storage, 71-79 log-structured merge tree (see LSMtrees) replication, 152, 158-161 change data capture, 454-457 (see also changelogs) coordination with snapshot, 156 logical (row-based) replication, 160 statement-based replication, 158 trigger-based replication, 161 write-ahead log (WAL) shipping, 159 scalability limits, 493 loose coupling, 396, 419, 502 lost updates (see updates) LSM-trees (indexes), 78-79 comparison to B-trees, 83-85 Lucene (storage engine), 79 building indexes in batch processes, 411 similarity search, 88 Luigi (workflow scheduler), 402 LWW (see last write wins) M machine learning ethical considerations, 534 (see also ethics) iterative processing, 424 models derived from training data, 505 statistical and numerical algorithms, 428 MADlib (machine learning toolkit), 428 magic scaling sauce, 18 Mahout (machine learning toolkit), 428 maintainability, 18-22, 489 defined, 23 design principles for software systems, 19 evolvability (see evolvability) operability, 19 simplicity and managing complexity, 20 many-to-many relationships in document model versus relational model, 39 modeling as graphs, 49 many-to-one and many-to-many relationships, 33-36 many-to-one relationships, 34 MapReduce (batch processing), 390, 399-400 accessing external services within job, 404, 412 comparison to distributed databases designing for frequent faults, 417 diversity of processing models, 416 diversity of storage, 415 Index | 575 comparison to stream processing, 464 comparison to Unix, 413-414 disadvantages and limitations of, 419 fault tolerance, 406, 414, 422 higher-level tools, 403, 426 implementation in Hadoop, 400-403 the shuffle, 402 implementation in MongoDB, 46-48 machine learning, 428 map-side processing, 408-410 broadcast hash joins, 409 merge joins, 410 partitioned hash joins, 409 mapper and reducer functions, 399 materialization of intermediate state, 419-423 output of batch workflows, 411-413 building search indexes, 411 key-value stores, 412 reduce-side processing, 403-408 analysis of user activity events (exam‐ ple), 404 grouping records by same key, 406 handling skew, 407 sort-merge joins, 405 workflows, 402 marshalling (see encoding) massively parallel processing (MPP), 216 comparison to composing storage technolo‐ gies, 502 comparison to Hadoop, 414-418, 428 master-master replication (see multi-leader replication) master-slave replication (see leader-based repli‐ cation) materialization, 556 aggregate values, 101 conflicts, 251 intermediate state (batch processing), 420-423 materialized views, 101 as derived data, 386, 499-504 maintaining, using stream processing, 467, 475 Maven (Java build tool), 428 Maxwell (change data capture), 455 mean, 14 media monitoring, 467 median, 14 576 | Index meeting room booking (example), 249, 259, 521 membership services, 372 Memcached (caching server), 4, 89 memory in-memory databases, 88 durability, 227 serial transaction execution, 253 in-memory representation of data, 112 random bit-flips in, 529 use by indexes, 72, 77 memory barrier (CPU instruction), 338 MemSQL (database) in-memory storage, 89 read committed isolation, 236 memtable (in LSM-trees), 78 Mercurial (version control system), 463 merge joins, MapReduce map-side, 410 mergeable persistent data structures, 174 merging sorted files, 76, 402, 405 Merkle trees, 532 Mesos (cluster manager), 418, 506 message brokers (see messaging systems) message-passing, 136-139 advantages over direct RPC, 137 distributed actor frameworks, 138 evolvability, 138 MessagePack (encoding format), 116 messages exactly-once semantics, 360, 476 loss of, 442 using total order broadcast, 348 messaging systems, 440-451 (see also streams) backpressure, buffering, or dropping mes‐ sages, 441 brokerless messaging, 442 event logs, 446-451 comparison to traditional messaging, 448, 451 consumer offsets, 449 replaying old messages, 451, 496, 498 slow consumers, 450 message brokers, 443-446 acknowledgements and redelivery, 445 comparison to event logs, 448, 451 multiple consumers of same topic, 444 reliability, 442 uniqueness in log-based messaging, 522 Meteor (web framework), 456 microbatching, 477, 495 microservices, 132 (see also services) causal dependencies across services, 493 loose coupling, 502 relation to batch/stream processors, 389, 508 Microsoft Azure Service Bus (messaging), 444 Azure Storage, 155, 398 Azure Stream Analytics, 466 DCOM (Distributed Component Object Model), 134 MSDTC (transaction coordinator), 356 Orleans (see Orleans) SQL Server (see SQL Server) migrating (rewriting) data, 40, 130, 461, 497 modulus operator (%), 210 MongoDB (database) aggregation pipeline, 48 atomic operations, 243 BSON, 41 document data model, 31 hash partitioning (sharding), 203-204 key-range partitioning, 202 lack of join support, 34, 42 leader-based replication, 153 MapReduce support, 46, 400 oplog parsing, 455, 456 partition splitting, 212 request routing, 216 secondary indexes, 207 Mongoriver (change data capture), 455 monitoring, 10, 19 monotonic clocks, 288 monotonic reads, 164 MPP (see massively parallel processing) MSMQ (messaging), 361 multi-column indexes, 87 multi-leader replication, 168-177 (see also replication) handling write conflicts, 171 conflict avoidance, 172 converging toward a consistent state, 172 custom conflict resolution logic, 173 determining what is a conflict, 174 linearizability, lack of, 333 replication topologies, 175-177 use cases, 168 clients with offline operation, 170 collaborative editing, 170 multi-datacenter replication, 168, 335 multi-object transactions, 228 need for, 231 Multi-Paxos (total order broadcast), 367 multi-table index cluster tables (Oracle), 41 multi-tenancy, 284 multi-version concurrency control (MVCC), 239, 266 detecting stale MVCC reads, 263 indexes and snapshot isolation, 241 mutual exclusion, 261 (see also locks) MySQL (database) binlog coordinates, 156 binlog parsing for change data capture, 455 circular replication topology, 175 consistent snapshots, 156 distributed transaction support, 361 InnoDB storage engine (see InnoDB) JSON support, 30, 42 leader-based replication, 153 performance of XA transactions, 360 row-based replication, 160 schema changes in, 40 snapshot isolation support, 242 (see also InnoDB) statement-based replication, 159 Tungsten Replicator (multi-leader replica‐ tion), 170 conflict detection, 177 N nanomsg (messaging library), 442 Narayana (transaction coordinator), 356 NATS (messaging), 137 near-real-time (nearline) processing, 390 (see also stream processing) Neo4j (database) Cypher query language, 52 graph data model, 50 Nephele (dataflow engine), 421 netcat (Unix tool), 397 Netflix Chaos Monkey, 7, 280 Network Attached Storage (NAS), 146, 398 network model, 36 Index | 577 graph databases versus, 60 imperative query APIs, 46 Network Time Protocol (see NTP) networks congestion and queueing, 282 datacenter network topologies, 276 faults (see faults) linearizability and network delays, 338 network partitions, 279, 337 timeouts and unbounded delays, 281 next-key locking, 260 nodes (in graphs) (see vertices) nodes (processes), 556 handling outages in leader-based replica‐ tion, 156 system models for failure, 307 noisy neighbors, 284 nonblocking atomic commit, 359 nondeterministic operations accidental nondeterminism, 423 partial failures in distributed systems, 275 nonfunctional requirements, 22 nonrepeatable reads, 238 (see also read skew) normalization (data representation), 33, 556 executing joins, 39, 42, 403 foreign key references, 231 in systems of record, 386 versus denormalization, 462 NoSQL, 29, 499 transactions and, 223 Notation3 (N3), 56 npm (package manager), 428 NTP (Network Time Protocol), 287 accuracy, 289, 293 adjustments to monotonic clocks, 289 multiple server addresses, 306 numbers, in XML and JSON encodings, 114 O object-relational mapping (ORM) frameworks, 30 error handling and aborted transactions, 232 unsafe read-modify-write cycle code, 244 object-relational mismatch, 29 observer pattern, 506 offline systems, 390 (see also batch processing) 578 | Index stateful, offline-capable clients, 170, 511 offline-first applications, 511 offsets consumer offsets in partitioned logs, 449 messages in partitioned logs, 447 OLAP (online analytic processing), 91, 556 data cubes, 102 OLTP (online transaction processing), 90, 556 analytics queries versus, 411 workload characteristics, 253 one-to-many relationships, 30 JSON representation, 32 online systems, 389 (see also services) Oozie (workflow scheduler), 402 OpenAPI (service definition format), 133 OpenStack Nova (cloud infrastructure) use of ZooKeeper, 370 Swift (object storage), 398 operability, 19 operating systems versus databases, 499 operation identifiers, 518, 522 operational transformation, 174 operators, 421 flow of data between, 424 in stream processing, 464 optimistic concurrency control, 261 Oracle (database) distributed transaction support, 361 GoldenGate (change data capture), 161, 170, 455 lack of serializability, 226 leader-based replication, 153 multi-table index cluster tables, 41 not preventing write skew, 248 partitioned indexes, 209 PL/SQL language, 255 preventing lost updates, 245 read committed isolation, 236 Real Application Clusters (RAC), 330 recursive query support, 54 snapshot isolation support, 239, 242 TimesTen (in-memory database), 89 WAL-based replication, 160 XML support, 30 ordering, 339-352 by sequence numbers, 343-348 causal ordering, 339-343 partial order, 341 limits of total ordering, 493 total order broadcast, 348-352 Orleans (actor framework), 139 outliers (response time), 14 Oz (programming language), 504 P package managers, 428, 505 packet switching, 285 packets corruption of, 306 sending via UDP, 442 PageRank (algorithm), 49, 424 paging (see virtual memory) ParAccel (database), 93 parallel databases (see massively parallel pro‐ cessing) parallel execution of graph analysis algorithms, 426 queries in MPP databases, 216 Parquet (data format), 96, 131 (see also column-oriented storage) use in Hadoop, 414 partial failures, 275, 310 limping, 311 partial order, 341 partitioning, 199-218, 556 and replication, 200 in batch processing, 429 multi-partition operations, 514 enforcing constraints, 522 secondary index maintenance, 495 of key-value data, 201-205 by key range, 202 skew and hot spots, 205 rebalancing partitions, 209-214 automatic or manual rebalancing, 213 problems with hash mod N, 210 using dynamic partitioning, 212 using fixed number of partitions, 210 using N partitions per node, 212 replication and, 147 request routing, 214-216 secondary indexes, 206-209 document-based partitioning, 206 term-based partitioning, 208 serial execution of transactions and, 255 Paxos (consensus algorithm), 366 ballot number, 368 Multi-Paxos (total order broadcast), 367 percentiles, 14, 556 calculating efficiently, 16 importance of high percentiles, 16 use in service level agreements (SLAs), 15 Percona XtraBackup (MySQL tool), 156 performance describing, 13 of distributed transactions, 360 of in-memory databases, 89 of linearizability, 338 of multi-leader replication, 169 perpetual inconsistency, 525 pessimistic concurrency control, 261 phantoms (transaction isolation), 250 materializing conflicts, 251 preventing, in serializability, 259 physical clocks (see clocks) pickle (Python), 113 Pig (dataflow language), 419, 427 replicated joins, 409 skewed joins, 407 workflows, 403 Pinball (workflow scheduler), 402 pipelined execution, 423 in Unix, 394 point in time, 287 polyglot persistence, 29 polystores, 501 PostgreSQL (database) BDR (multi-leader replication), 170 causal ordering of writes, 177 Bottled Water (change data capture), 455 Bucardo (trigger-based replication), 161, 173 distributed transaction support, 361 foreign data wrappers, 501 full text search support, 490 leader-based replication, 153 log sequence number, 156 MVCC implementation, 239, 241 PL/pgSQL language, 255 PostGIS geospatial indexes, 87 preventing lost updates, 245 preventing write skew, 248, 261 read committed isolation, 236 recursive query support, 54 representing graphs, 51 Index | 579 serializable snapshot isolation (SSI), 261 snapshot isolation support, 239, 242 WAL-based replication, 160 XML and JSON support, 30, 42 pre-splitting, 212 Precision Time Protocol (PTP), 290 predicate locks, 259 predictive analytics, 533-536 amplifying bias, 534 ethics of (see ethics) feedback loops, 536 preemption of datacenter resources, 418 of threads, 298 Pregel processing model, 425 primary keys, 85, 556 compound primary key (Cassandra), 204 primary-secondary replication (see leaderbased replication) privacy, 536-543 consent and freedom of choice, 538 data as assets and power, 540 deleting data, 463 ethical considerations (see ethics) legislation and self-regulation, 542 meaning of, 539 surveillance, 537 tracking behavioral data, 536 probabilistic algorithms, 16, 466 process pauses, 295-299 processing time (of events), 469 producers (message streams), 440 programming languages dataflow languages, 504 for stored procedures, 255 functional reactive programming (FRP), 504 logic programming, 504 Prolog (language), 61 (see also Datalog) promises (asynchronous operations), 135 property graphs, 50 Cypher query language, 52 Protocol Buffers (data format), 117-121 field tags and schema evolution, 120 provenance of data, 531 publish/subscribe model, 441 publishers (message streams), 440 punch card tabulating machines, 390 580 | Index pure functions, 48 putting computation near data, 400 Q Qpid (messaging), 444 quality of service (QoS), 285 Quantcast File System (distributed filesystem), 398 query languages, 42-48 aggregation pipeline, 48 CSS and XSL, 44 Cypher, 52 Datalog, 60 Juttle, 504 MapReduce querying, 46-48 recursive SQL queries, 53 relational algebra and SQL, 42 SPARQL, 59 query optimizers, 37, 427 queueing delays (networks), 282 head-of-line blocking, 15 latency and response time, 14 queues (messaging), 137 quorums, 179-182, 556 for leaderless replication, 179 in consensus algorithms, 368 limitations of consistency, 181-183, 334 making decisions in distributed systems, 301 monitoring staleness, 182 multi-datacenter replication, 184 relying on durability, 309 sloppy quorums and hinted handoff, 183 R R-trees (indexes), 87 RabbitMQ (messaging), 137, 444 leader-based replication, 153 race conditions, 225 (see also concurrency) avoiding with linearizability, 331 caused by dual writes, 452 dirty writes, 235 in counter increments, 235 lost updates, 242-246 preventing with event logs, 462, 507 preventing with serializable isolation, 252 write skew, 246-251 Raft (consensus algorithm), 366 sensitivity to network problems, 369 term number, 368 use in etcd, 353 RAID (Redundant Array of Independent Disks), 7, 398 railways, schema migration on, 496 RAMCloud (in-memory storage), 89 ranking algorithms, 424 RDF (Resource Description Framework), 57 querying with SPARQL, 59 RDMA (Remote Direct Memory Access), 276 read committed isolation level, 234-237 implementing, 236 multi-version concurrency control (MVCC), 239 no dirty reads, 234 no dirty writes, 235 read path (derived data), 509 read repair (leaderless replication), 178 for linearizability, 335 read replicas (see leader-based replication) read skew (transaction isolation), 238, 266 as violation of causality, 340 read-after-write consistency, 163, 524 cross-device, 164 read-modify-write cycle, 243 read-scaling architecture, 161 reads as events, 513 real-time collaborative editing, 170 near-real-time processing, 390 (see also stream processing) publish/subscribe dataflow, 513 response time guarantees, 298 time-of-day clocks, 288 rebalancing partitions, 209-214, 556 (see also partitioning) automatic or manual rebalancing, 213 dynamic partitioning, 212 fixed number of partitions, 210 fixed number of partitions per node, 212 problems with hash mod N, 210 recency guarantee, 324 recommendation engines batch process outputs, 412 batch workflows, 403, 420 iterative processing, 424 statistical and numerical algorithms, 428 records, 399 events in stream processing, 440 recursive common table expressions (SQL), 54 redelivery (messaging), 445 Redis (database) atomic operations, 243 durability, 89 Lua scripting, 255 single-threaded execution, 253 usage example, 4 redundancy hardware components, 7 of derived data, 386 (see also derived data) Reed–Solomon codes (error correction), 398 refactoring, 22 (see also evolvability) regions (partitioning), 199 register (data structure), 325 relational data model, 28-42 comparison to document model, 38-42 graph queries in SQL, 53 in-memory databases with, 89 many-to-one and many-to-many relation‐ ships, 33 multi-object transactions, need for, 231 NoSQL as alternative to, 29 object-relational mismatch, 29 relational algebra and SQL, 42 versus document model convergence of models, 41 data locality, 41 relational databases eventual consistency, 162 history, 28 leader-based replication, 153 logical logs, 160 philosophy compared to Unix, 499, 501 schema changes, 40, 111, 130 statement-based replication, 158 use of B-tree indexes, 80 relationships (see edges) reliability, 6-10, 489 building a reliable system from unreliable components, 276 defined, 6, 22 hardware faults, 7 human errors, 9 importance of, 10 of messaging systems, 442 Index | 581 software errors, 8 Remote Method Invocation (Java RMI), 134 remote procedure calls (RPCs), 134-136 (see also services) based on futures, 135 data encoding and evolution, 136 issues with, 134 using Avro, 126, 135 using Thrift, 135 versus message brokers, 137 repeatable reads (transaction isolation), 242 replicas, 152 replication, 151-193, 556 and durability, 227 chain replication, 155 conflict resolution and, 246 consistency properties, 161-167 consistent prefix reads, 165 monotonic reads, 164 reading your own writes, 162 in distributed filesystems, 398 leaderless, 177-191 detecting concurrent writes, 184-191 limitations of quorum consistency, 181-183, 334 sloppy quorums and hinted handoff, 183 monitoring staleness, 182 multi-leader, 168-177 across multiple datacenters, 168, 335 handling write conflicts, 171-175 replication topologies, 175-177 partitioning and, 147, 200 reasons for using, 145, 151 single-leader, 152-161 failover, 157 implementation of replication logs, 158-161 relation to consensus, 367 setting up new followers, 155 synchronous versus asynchronous, 153-155 state machine replication, 349, 452 using erasure coding, 398 with heterogeneous data systems, 453 replication logs (see logs) reprocessing data, 496, 498 (see also evolvability) from log-based messaging, 451 request routing, 214-216 582 | Index approaches to, 214 parallel query execution, 216 resilient systems, 6 (see also fault tolerance) response time as performance metric for services, 13, 389 guarantees on, 298 latency versus, 14 mean and percentiles, 14 user experience, 15 responsibility and accountability, 535 REST (Representational State Transfer), 133 (see also services) RethinkDB (database) document data model, 31 dynamic partitioning, 212 join support, 34, 42 key-range partitioning, 202 leader-based replication, 153 subscribing to changes, 456 Riak (database) Bitcask storage engine, 72 CRDTs, 174, 191 dotted version vectors, 191 gossip protocol, 216 hash partitioning, 203-204, 211 last-write-wins conflict resolution, 186 leaderless replication, 177 LevelDB storage engine, 78 linearizability, lack of, 335 multi-datacenter support, 184 preventing lost updates across replicas, 246 rebalancing, 213 search feature, 209 secondary indexes, 207 siblings (concurrently written values), 190 sloppy quorums, 184 ring buffers, 450 Ripple (cryptocurrency), 532 rockets, 10, 36, 305 RocksDB (storage engine), 78 leveled compaction, 79 rollbacks (transactions), 222 rolling upgrades, 8, 112 routing (see request routing) row-oriented storage, 96 row-based replication, 160 rowhammer (memory corruption), 529 RPCs (see remote procedure calls) Rubygems (package manager), 428 rules (Datalog), 61 S safety and liveness properties, 308 in consensus algorithms, 366 in transactions, 222 sagas (see compensating transactions) Samza (stream processor), 466, 467 fault tolerance, 479 streaming SQL support, 466 sandboxes, 9 SAP HANA (database), 93 scalability, 10-18, 489 approaches for coping with load, 17 defined, 22 describing load, 11 describing performance, 13 partitioning and, 199 replication and, 161 scaling up versus scaling out, 146 scaling out, 17, 146 (see also shared-nothing architecture) scaling up, 17, 146 scatter/gather approach, querying partitioned databases, 207 SCD (slowly changing dimension), 476 schema-on-read, 39 comparison to evolvable schema, 128 in distributed filesystems, 415 schema-on-write, 39 schemaless databases (see schema-on-read) schemas, 557 Avro, 122-127 reader determining writer’s schema, 125 schema evolution, 123 dynamically generated, 126 evolution of, 496 affecting application code, 111 compatibility checking, 126 in databases, 129-131 in message-passing, 138 in service calls, 136 flexibility in document model, 39 for analytics, 93-95 for JSON and XML, 115 merits of, 127 schema migration on railways, 496 Thrift and Protocol Buffers, 117-121 schema evolution, 120 traditional approach to design, fallacy in, 462 searches building search indexes in batch processes, 411 k-nearest neighbors, 429 on streams, 467 partitioned secondary indexes, 206 secondaries (see leader-based replication) secondary indexes, 85, 557 partitioning, 206-209, 217 document-partitioned, 206 index maintenance, 495 term-partitioned, 208 problems with dual writes, 452, 491 updating, transaction isolation and, 231 secondary sorts, 405 sed (Unix tool), 392 self-describing files, 127 self-joins, 480 self-validating systems, 530 semantic web, 57 semi-synchronous replication, 154 sequence number ordering, 343-348 generators, 294, 344 insufficiency for enforcing constraints, 347 Lamport timestamps, 345 use of timestamps, 291, 295, 345 sequential consistency, 351 serializability, 225, 233, 251-266, 557 linearizability versus, 329 pessimistic versus optimistic concurrency control, 261 serial execution, 252-256 partitioning, 255 using stored procedures, 253, 349 serializable snapshot isolation (SSI), 261-266 detecting stale MVCC reads, 263 detecting writes that affect prior reads, 264 distributed execution, 265, 364 performance of SSI, 265 preventing write skew, 262-265 two-phase locking (2PL), 257-261 index-range locks, 260 performance, 258 Serializable (Java), 113 Index | 583 serialization, 113 (see also encoding) service discovery, 135, 214, 372 using DNS, 216, 372 service level agreements (SLAs), 15 service-oriented architecture (SOA), 132 (see also services) services, 131-136 microservices, 132 causal dependencies across services, 493 loose coupling, 502 relation to batch/stream processors, 389, 508 remote procedure calls (RPCs), 134-136 issues with, 134 similarity to databases, 132 web services, 132, 135 session windows (stream processing), 472 (see also windows) sessionization, 407 sharding (see partitioning) shared mode (locks), 258 shared-disk architecture, 146, 398 shared-memory architecture, 146 shared-nothing architecture, 17, 146-147, 557 (see also replication) distributed filesystems, 398 (see also distributed filesystems) partitioning, 199 use of network, 277 sharks biting undersea cables, 279 counting (example), 46-48 finding (example), 42 website about (example), 44 shredding (in relational model), 38 siblings (concurrent values), 190, 246 (see also conflicts) similarity search edit distance, 88 genome data, 63 k-nearest neighbors, 429 single-leader replication (see leader-based rep‐ lication) single-threaded execution, 243, 252 in batch processing, 406, 421, 426 in stream processing, 448, 463, 522 size-tiered compaction, 79 skew, 557 584 | Index clock skew, 291-294, 334 in transaction isolation read skew, 238, 266 write skew, 246-251, 262-265 (see also write skew) meanings of, 238 unbalanced workload, 201 compensating for, 205 due to celebrities, 205 for time-series data, 203 in batch processing, 407 slaves (see leader-based replication) sliding windows (stream processing), 472 (see also windows) sloppy quorums, 183 (see also quorums) lack of linearizability, 334 slowly changing dimension (data warehouses), 476 smearing (leap seconds adjustments), 290 snapshots (databases) causal consistency, 340 computing derived data, 500 in change data capture, 455 serializable snapshot isolation (SSI), 261-266, 329 setting up a new replica, 156 snapshot isolation and repeatable read, 237-242 implementing with MVCC, 239 indexes and MVCC, 241 visibility rules, 240 synchronized clocks for global snapshots, 294 snowflake schemas, 95 SOAP, 133 (see also services) evolvability, 136 software bugs, 8 maintaining integrity, 529 solid state drives (SSDs) access patterns, 84 detecting corruption, 519, 530 faults in, 227 sequential write throughput, 75 Solr (search server) building indexes in batch processes, 411 document-partitioned indexes, 207 request routing, 216 usage example, 4 use of Lucene, 79 sort (Unix tool), 392, 394, 395 sort-merge joins (MapReduce), 405 Sorted String Tables (see SSTables) sorting sort order in column storage, 99 source of truth (see systems of record) Spanner (database) data locality, 41 snapshot isolation using clocks, 295 TrueTime API, 294 Spark (processing framework), 421-423 bytecode generation, 428 dataflow APIs, 427 fault tolerance, 422 for data warehouses, 93 GraphX API (graph processing), 425 machine learning, 428 query optimizer, 427 Spark Streaming, 466 microbatching, 477 stream processing on top of batch process‐ ing, 495 SPARQL (query language), 59 spatial algorithms, 429 split brain, 158, 557 in consensus algorithms, 352, 367 preventing, 322, 333 using fencing tokens to avoid, 302-304 spreadsheets, dataflow programming capabili‐ ties, 504 SQL (Structured Query Language), 21, 28, 43 advantages and limitations of, 416 distributed query execution, 48 graph queries in, 53 isolation levels standard, issues with, 242 query execution on Hadoop, 416 résumé (example), 30 SQL injection vulnerability, 305 SQL on Hadoop, 93 statement-based replication, 158 stored procedures, 255 SQL Server (database) data warehousing support, 93 distributed transaction support, 361 leader-based replication, 153 preventing lost updates, 245 preventing write skew, 248, 257 read committed isolation, 236 recursive query support, 54 serializable isolation, 257 snapshot isolation support, 239 T-SQL language, 255 XML support, 30 SQLstream (stream analytics), 466 SSDs (see solid state drives) SSTables (storage format), 76-79 advantages over hash indexes, 76 concatenated index, 204 constructing and maintaining, 78 making LSM-Tree from, 78 staleness (old data), 162 cross-channel timing dependencies, 331 in leaderless databases, 178 in multi-version concurrency control, 263 monitoring for, 182 of client state, 512 versus linearizability, 324 versus timeliness, 524 standbys (see leader-based replication) star replication topologies, 175 star schemas, 93-95 similarity to event sourcing, 458 Star Wars analogy (event time versus process‐ ing time), 469 state derived from log of immutable events, 459 deriving current state from the event log, 458 interplay between state changes and appli‐ cation code, 507 maintaining derived state, 495 maintenance by stream processor in streamstream joins, 473 observing derived state, 509-515 rebuilding after stream processor failure, 478 separation of application code and, 505 state machine replication, 349, 452 statement-based replication, 158 statically typed languages analogy to schema-on-write, 40 code generation and, 127 statistical and numerical algorithms, 428 StatsD (metrics aggregator), 442 stdin, stdout, 395, 396 Stellar (cryptocurrency), 532 Index | 585 stock market feeds, 442 STONITH (Shoot The Other Node In The Head), 158 stop-the-world (see garbage collection) storage composing data storage technologies, 499-504 diversity of, in MapReduce, 415 Storage Area Network (SAN), 146, 398 storage engines, 69-104 column-oriented, 95-101 column compression, 97-99 defined, 96 distinction between column families and, 99 Parquet, 96, 131 sort order in, 99-100 writing to, 101 comparing requirements for transaction processing and analytics, 90-96 in-memory storage, 88 durability, 227 row-oriented, 70-90 B-trees, 79-83 comparing B-trees and LSM-trees, 83-85 defined, 96 log-structured, 72-79 stored procedures, 161, 253-255, 557 and total order broadcast, 349 pros and cons of, 255 similarity to stream processors, 505 Storm (stream processor), 466 distributed RPC, 468, 514 Trident state handling, 478 straggler events, 470, 498 stream processing, 464-481, 557 accessing external services within job, 474, 477, 478, 517 combining with batch processing lambda architecture, 497 unifying technologies, 498 comparison to batch processing, 464 complex event processing (CEP), 465 fault tolerance, 476-479 atomic commit, 477 idempotence, 478 microbatching and checkpointing, 477 rebuilding state after a failure, 478 for data integration, 494-498 586 | Index maintaining derived state, 495 maintenance of materialized views, 467 messaging systems (see messaging systems) reasoning about time, 468-472 event time versus processing time, 469, 477, 498 knowing when window is ready, 470 types of windows, 472 relation to databases (see streams) relation to services, 508 search on streams, 467 single-threaded execution, 448, 463 stream analytics, 466 stream joins, 472-476 stream-stream join, 473 stream-table join, 473 table-table join, 474 time-dependence of, 475 streams, 440-451 end-to-end, pushing events to clients, 512 messaging systems (see messaging systems) processing (see stream processing) relation to databases, 451-464 (see also changelogs) API support for change streams, 456 change data capture, 454-457 derivative of state by time, 460 event sourcing, 457-459 keeping systems in sync, 452-453 philosophy of immutable events, 459-464 topics, 440 strict serializability, 329 strong consistency (see linearizability) strong one-copy serializability, 329 subjects, predicates, and objects (in triplestores), 55 subscribers (message streams), 440 (see also consumers) supercomputers, 275 surveillance, 537 (see also privacy) Swagger (service definition format), 133 swapping to disk (see virtual memory) synchronous networks, 285, 557 comparison to asynchronous networks, 284 formal model, 307 synchronous replication, 154, 557 chain replication, 155 conflict detection, 172 system models, 300, 306-310 assumptions in, 528 correctness of algorithms, 308 mapping to the real world, 309 safety and liveness, 308 systems of record, 386, 557 change data capture, 454, 491 treating event log as, 460 systems thinking, 536 T t-digest (algorithm), 16 table-table joins, 474 Tableau (data visualization software), 416 tail (Unix tool), 447 tail vertex (property graphs), 51 Tajo (query engine), 93 Tandem NonStop SQL (database), 200 TCP (Transmission Control Protocol), 277 comparison to circuit switching, 285 comparison to UDP, 283 connection failures, 280 flow control, 282, 441 packet checksums, 306, 519, 529 reliability and duplicate suppression, 517 retransmission timeouts, 284 use for transaction sessions, 229 telemetry (see monitoring) Teradata (database), 93, 200 term-partitioned indexes, 208, 217 termination (consensus), 365 Terrapin (database), 413 Tez (dataflow engine), 421-423 fault tolerance, 422 support by higher-level tools, 427 thrashing (out of memory), 297 threads (concurrency) actor model, 138, 468 (see also message-passing) atomic operations, 223 background threads, 73, 85 execution pauses, 286, 296-298 memory barriers, 338 preemption, 298 single (see single-threaded execution) three-phase commit, 359 Thrift (data format), 117-121 BinaryProtocol, 118 CompactProtocol, 119 field tags and schema evolution, 120 throughput, 13, 390 TIBCO, 137 Enterprise Message Service, 444 StreamBase (stream analytics), 466 time concurrency and, 187 cross-channel timing dependencies, 331 in distributed systems, 287-299 (see also clocks) clock synchronization and accuracy, 289 relying on synchronized clocks, 291-295 process pauses, 295-299 reasoning about, in stream processors, 468-472 event time versus processing time, 469, 477, 498 knowing when window is ready, 470 timestamp of events, 471 types of windows, 472 system models for distributed systems, 307 time-dependence in stream joins, 475 time-of-day clocks, 288 timeliness, 524 coordination-avoiding data systems, 528 correctness of dataflow systems, 525 timeouts, 279, 557 dynamic configuration of, 284 for failover, 158 length of, 281 timestamps, 343 assigning to events in stream processing, 471 for read-after-write consistency, 163 for transaction ordering, 295 insufficiency for enforcing constraints, 347 key range partitioning by, 203 Lamport, 345 logical, 494 ordering events, 291, 345 Titan (database), 50 tombstones, 74, 191, 456 topics (messaging), 137, 440 total order, 341, 557 limits of, 493 sequence numbers or timestamps, 344 total order broadcast, 348-352, 493, 522 consensus algorithms and, 366-368 Index | 587 implementation in ZooKeeper and etcd, 370 implementing with linearizable storage, 351 using, 349 using to implement linearizable storage, 350 tracking behavioral data, 536 (see also privacy) transaction coordinator (see coordinator) transaction manager (see coordinator) transaction processing, 28, 90-95 comparison to analytics, 91 comparison to data warehousing, 93 transactions, 221-267, 558 ACID properties of, 223 atomicity, 223 consistency, 224 durability, 226 isolation, 225 compensating (see compensating transac‐ tions) concept of, 222 distributed transactions, 352-364 avoiding, 492, 502, 521-528 failure amplification, 364, 495 in doubt/uncertain status, 358, 362 two-phase commit, 354-359 use of, 360-361 XA transactions, 361-364 OLTP versus analytics queries, 411 purpose of, 222 serializability, 251-266 actual serial execution, 252-256 pessimistic versus optimistic concur‐ rency control, 261 serializable snapshot isolation (SSI), 261-266 two-phase locking (2PL), 257-261 single-object and multi-object, 228-232 handling errors and aborts, 231 need for multi-object transactions, 231 single-object writes, 230 snapshot isolation (see snapshots) weak isolation levels, 233-251 preventing lost updates, 242-246 read committed, 234-238 transitive closure (graph algorithm), 424 trie (data structure), 88 triggers (databases), 161, 441 implementing change data capture, 455 implementing replication, 161 588 | Index triple-stores, 55-59 SPARQL query language, 59 tumbling windows (stream processing), 472 (see also windows) in microbatching, 477 tuple spaces (programming model), 507 Turtle (RDF data format), 56 Twitter constructing home timelines (example), 11, 462, 474, 511 DistributedLog (event log), 448 Finagle (RPC framework), 135 Snowflake (sequence number generator), 294 Summingbird (processing library), 497 two-phase commit (2PC), 353, 355-359, 558 confusion with two-phase locking, 356 coordinator failure, 358 coordinator recovery, 363 how it works, 357 issues in practice, 363 performance cost, 360 transactions holding locks, 362 two-phase locking (2PL), 257-261, 329, 558 confusion with two-phase commit, 356 index-range locks, 260 performance of, 258 type checking, dynamic versus static, 40 U UDP (User Datagram Protocol) comparison to TCP, 283 multicast, 442 unbounded datasets, 439, 558 (see also streams) unbounded delays, 558 in networks, 282 process pauses, 296 unbundling databases, 499-515 composing data storage technologies, 499-504 federation versus unbundling, 501 need for high-level language, 503 designing applications around dataflow, 504-509 observing derived state, 509-515 materialized views and caching, 510 multi-partition data processing, 514 pushing state changes to clients, 512 uncertain (transaction status) (see in doubt) uniform consensus, 365 (see also consensus) uniform interfaces, 395 union type (in Avro), 125 uniq (Unix tool), 392 uniqueness constraints asynchronously checked, 526 requiring consensus, 521 requiring linearizability, 330 uniqueness in log-based messaging, 522 Unix philosophy, 394-397 command-line batch processing, 391-394 Unix pipes versus dataflow engines, 423 comparison to Hadoop, 413-414 comparison to relational databases, 499, 501 comparison to stream processing, 464 composability and uniform interfaces, 395 loose coupling, 396 pipes, 394 relation to Hadoop, 499 UPDATE statement (SQL), 40 updates preventing lost updates, 242-246 atomic write operations, 243 automatically detecting lost updates, 245 compare-and-set operations, 245 conflict resolution and replication, 246 using explicit locking, 244 preventing write skew, 246-251 V validity (consensus), 365 vBuckets (partitioning), 199 vector clocks, 191 (see also version vectors) vectorized processing, 99, 428 verification, 528-533 avoiding blind trust, 530 culture of, 530 designing for auditability, 531 end-to-end integrity checks, 531 tools for auditable data systems, 532 version control systems, reliance on immutable data, 463 version vectors, 177, 191 capturing causal dependencies, 343 versus vector clocks, 191 Vertica (database), 93 handling writes, 101 replicas using different sort orders, 100 vertical scaling (see scaling up) vertices (in graphs), 49 property graph model, 50 Viewstamped Replication (consensus algo‐ rithm), 366 view number, 368 virtual machines, 146 (see also cloud computing) context switches, 297 network performance, 282 noisy neighbors, 284 reliability in cloud services, 8 virtualized clocks in, 290 virtual memory process pauses due to page faults, 14, 297 versus memory management by databases, 89 VisiCalc (spreadsheets), 504 vnodes (partitioning), 199 Voice over IP (VoIP), 283 Voldemort (database) building read-only stores in batch processes, 413 hash partitioning, 203-204, 211 leaderless replication, 177 multi-datacenter support, 184 rebalancing, 213 reliance on read repair, 179 sloppy quorums, 184 VoltDB (database) cross-partition serializability, 256 deterministic stored procedures, 255 in-memory storage, 89 output streams, 456 secondary indexes, 207 serial execution of transactions, 253 statement-based replication, 159, 479 transactions in stream processing, 477 W WAL (write-ahead log), 82 web services (see services) Web Services Description Language (WSDL), 133 webhooks, 443 webMethods (messaging), 137 WebSocket (protocol), 512 Index | 589 windows (stream processing), 466, 468-472 infinite windows for changelogs, 467, 474 knowing when all events have arrived, 470 stream joins within a window, 473 types of windows, 472 winners (conflict resolution), 173 WITH RECURSIVE syntax (SQL), 54 workflows (MapReduce), 402 outputs, 411-414 key-value stores, 412 search indexes, 411 with map-side joins, 410 working set, 393 write amplification, 84 write path (derived data), 509 write skew (transaction isolation), 246-251 characterizing, 246-251, 262 examples of, 247, 249 materializing conflicts, 251 occurrence in practice, 529 phantoms, 250 preventing in snapshot isolation, 262-265 in two-phase locking, 259-261 options for, 248 write-ahead log (WAL), 82, 159 writes (database) atomic write operations, 243 detecting writes affecting prior reads, 264 preventing dirty writes with read commit‐ ted, 235 WS-* framework, 133 (see also services) WS-AtomicTransaction (2PC), 355 590 | Index X XA transactions, 355, 361-364 heuristic decisions, 363 limitations of, 363 xargs (Unix tool), 392, 396 XML binary variants, 115 encoding RDF data, 57 for application data, issues with, 114 in relational databases, 30, 41 XSL/XPath, 45 Y Yahoo!

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

To give just a few brief examples: Researchers working with genome data often need to perform sequence-similarity searches, which means taking one very long string (representing a DNA molecule) and matching it against a large database of strings that are similar, but not identical. None of the databases described here can handle this kind of usage, which is why researchers have written specialized genome database software like GenBank [48]. Particle physicists have been doing Big Data–style large-scale data analysis for decades, and projects like the Large Hadron Collider (LHC) now work with hundreds of petabytes! At such a scale custom solutions are required to stop the hardware cost from spiraling out of control [49]. Full-text search is arguably a kind of data model that is frequently used alongside databases. Information retrieval is a large specialist subject that we won’t cover in great detail in this book, but we’ll touch on search indexes in Chapter 3 and Part III.

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InfiniteGraph (database), Graph-Like Data Models InnoDB (storage engine)clustered index on primary key, Storing values within the index not preventing lost updates, Automatically detecting lost updates preventing write skew, Characterizing write skew, Implementation of two-phase locking serializable isolation, Implementation of two-phase locking snapshot isolation support, Snapshot Isolation and Repeatable Read inside-out databases, Designing Applications Around Dataflow(see also unbundling databases) integrating different data systems (see data integration) integrity, Timeliness and Integritycoordination-avoiding data systems, Coordination-avoiding data systems correctness of dataflow systems, Correctness of dataflow systems in consensus formalization, Fault-Tolerant Consensus integrity checks, Don’t just blindly trust what they promise(see also auditing) end-to-end, The end-to-end argument, The end-to-end argument again use of snapshot isolation, Snapshot Isolation and Repeatable Read maintaining despite software bugs, Maintaining integrity in the face of software bugs Interface Definition Language (IDL), Thrift and Protocol Buffers, Avro intermediate state, materialization of, Materialization of Intermediate State-Discussion of materialization internet services, systems for implementing, Cloud Computing and Supercomputing invariants, Consistency(see also constraints) inversion of control, Separation of logic and wiring IP (Internet Protocol)unreliability of, Cloud Computing and Supercomputing ISDN (Integrated Services Digital Network), Synchronous Versus Asynchronous Networks isolation (in transactions), Isolation, Single-Object and Multi-Object Operations, Glossarycorrectness and, Aiming for Correctness for single-object writes, Single-object writes serializability, Serializability-Performance of serializable snapshot isolationactual serial execution, Actual Serial Execution-Summary of serial execution serializable snapshot isolation (SSI), Serializable Snapshot Isolation (SSI)-Performance of serializable snapshot isolation two-phase locking (2PL), Two-Phase Locking (2PL)-Index-range locks violating, Single-Object and Multi-Object Operations weak isolation levels, Weak Isolation Levels-Materializing conflictspreventing lost updates, Preventing Lost Updates-Conflict resolution and replication read committed, Read Committed-Implementing read committed snapshot isolation, Snapshot Isolation and Repeatable Read-Repeatable read and naming confusion iterative processing, Graphs and Iterative Processing-Parallel execution J Java Database Connectivity (JDBC)distributed transaction support, XA transactions network drivers, The Merits of Schemas Java Enterprise Edition (EE), The problems with remote procedure calls (RPCs), Introduction to two-phase commit, XA transactions Java Message Service (JMS), Message brokers compared to databases(see also messaging systems) comparison to log-based messaging, Logs compared to traditional messaging, Replaying old messages distributed transaction support, XA transactions message ordering, Acknowledgments and redelivery Java Transaction API (JTA), Introduction to two-phase commit, XA transactions Java Virtual Machine (JVM)bytecode generation, The move toward declarative query languages garbage collection pauses, Process Pauses process reuse in batch processors, Dataflow engines JavaScriptin MapReduce querying, MapReduce Querying setting element styles (example), Declarative Queries on the Web use in advanced queries, MapReduce Querying Jena (RDF framework), The RDF data model Jepsen (fault tolerance testing), Aiming for Correctness jitter (network delay), Network congestion and queueing joins, Glossaryby index lookup, Reduce-Side Joins and Grouping expressing as relational operators, The move toward declarative query languages in relational and document databases, Many-to-One and Many-to-Many Relationships MapReduce map-side joins, Map-Side Joins-MapReduce workflows with map-side joinsbroadcast hash joins, Broadcast hash joins merge joins, Map-side merge joins partitioned hash joins, Partitioned hash joins MapReduce reduce-side joins, Reduce-Side Joins and Grouping-Handling skewhandling skew, Handling skew sort-merge joins, Sort-merge joins parallel execution of, Comparing Hadoop to Distributed Databases secondary indexes and, Other Indexing Structures stream joins, Stream Joins-Time-dependence of joinsstream-stream join, Stream-stream join (window join) stream-table join, Stream-table join (stream enrichment) table-table join, Table-table join (materialized view maintenance) time-dependence of, Time-dependence of joins support in document databases, Convergence of document and relational databases JOTM (transaction coordinator), Introduction to two-phase commit JSONAvro schema representation, Avro binary variants, Binary encoding for application data, issues with, JSON, XML, and Binary Variants in relational databases, The Object-Relational Mismatch, Convergence of document and relational databases representing a résumé (example), The Object-Relational Mismatch Juttle (query language), Designing Applications Around Dataflow K k-nearest neighbors, Specialization for different domains Kafka (messaging), Message brokers, Using logs for message storageKafka Connect (database integration), API support for change streams, Deriving several views from the same event log Kafka Streams (stream processor), Stream analytics, Maintaining materialized viewsfault tolerance, Rebuilding state after a failure leader-based replication, Leaders and Followers log compaction, Log compaction, Maintaining materialized views message offsets, Using logs for message storage, Idempotence request routing, Request Routing transaction support, Atomic commit revisited usage example, Thinking About Data Systems Ketama (partitioning library), Partitioning proportionally to nodes key-value stores, Data Structures That Power Your Databaseas batch process output, Key-value stores as batch process output hash indexes, Hash Indexes-Hash Indexes in-memory, Keeping everything in memory partitioning, Partitioning of Key-Value Data-Skewed Workloads and Relieving Hot Spotsby hash of key, Partitioning by Hash of Key, Summary by key range, Partitioning by Key Range, Summary dynamic partitioning, Dynamic partitioning skew and hot spots, Skewed Workloads and Relieving Hot Spots Kryo (Java), Language-Specific Formats Kubernetes (cluster manager), Designing for frequent faults, Separation of application code and state L lambda architecture, The lambda architecture Lamport timestamps, Lamport timestamps Large Hadron Collider (LHC), Summary last write wins (LWW), Converging toward a consistent state, Implementing Linearizable Systemsdiscarding concurrent writes, Last write wins (discarding concurrent writes) problems with, Timestamps for ordering events prone to lost updates, Conflict resolution and replication late binding, Separation of logic and wiring latencyinstability under two-phase locking, Performance of two-phase locking network latency and resource utilization, Can we not simply make network delays predictable?

Origin Story: A Big History of Everything by David Christian

"World Economic Forum" Davos, Albert Einstein, Anthropocene, Arthur Eddington, butterfly effect, Capital in the Twenty-First Century by Thomas Piketty, Cepheid variable, colonial rule, Colonization of Mars, Columbian Exchange, complexity theory, cosmic microwave background, cosmological constant, creative destruction, cuban missile crisis, dark matter, demographic transition, double helix, Easter island, Edward Lorenz: Chaos theory, Ernest Rutherford, European colonialism, Francisco Pizarro, Haber-Bosch Process, Harvard Computers: women astronomers, Isaac Newton, James Watt: steam engine, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kickstarter, Kim Stanley Robinson, Large Hadron Collider, Late Heavy Bombardment, Marshall McLuhan, microbiome, nuclear winter, Paris climate accords, planetary scale, rising living standards, Search for Extraterrestrial Intelligence, Stephen Hawking, Steven Pinker, Stuart Kauffman, TED Talk, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, trade route, Yogi Berra

This is a colossal number, so if you uncompress a tiny bit of matter, you get a huge amount of energy. That’s what happens when an H-bomb explodes. In the early universe, the opposite process occurred. Huge amounts of energy were compressed into tiny amounts of matter, like motes of dust in a vast fog of energy. Remarkably, we humans have managed to re-create such energies briefly, in the Large Hadron Collider outside Geneva. And, yes, particles do start popping out of that boiling ocean of energy. And we’re still in the first second … The First Structures Within the chaotic fog of energy just after the big bang, distinct forms and structures began to appear. Though the fog of energy is always there, the structures that emerged from it will give our origin story shape and a plotline.

The Intelligence Trap: Revolutionise Your Thinking and Make Wiser Decisions by David Robson

active measures, Affordable Care Act / Obamacare, Albert Einstein, Alfred Russel Wallace, Atul Gawande, autism spectrum disorder, availability heuristic, behavioural economics, classic study, cognitive bias, corporate governance, correlation coefficient, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, deep learning, deliberate practice, dematerialisation, Donald Trump, Dunning–Kruger effect, fake news, Flynn Effect, framing effect, fundamental attribution error, illegal immigration, Isaac Newton, job satisfaction, knowledge economy, Large Hadron Collider, lone genius, meta-analysis, Nelson Mandela, obamacare, Parler "social media", pattern recognition, post-truth, price anchoring, reality distortion field, Richard Feynman, risk tolerance, Silicon Valley, social intelligence, Steve Jobs, sunk-cost fallacy, tacit knowledge, TED Talk, the scientific method, theory of mind, traveling salesman, ultimatum game, Y2K, Yom Kippur War

As one vivid example, consider the story of Paul Frampton. A brilliant physicist at the University of North Carolina, his work ranged from a new theory of dark matter (the mysterious, invisible mass holding our universe together) to the prediction of a subatomic particle called the ‘axigluon’, a theory that is inspiring experiments at the Large Hadron Collider. In 2011, however, he began online dating, and soon struck up a friendship with a former bikini model named Denise Milani. In January the next year, she invited him to visit her on a photoshoot in La Paz, Bolivia. When he arrived, however, he found a message – she’d had to leave for Argentina instead.

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

In some sense they describe the ‘square-root’ of geometry and, just as understanding the concept of the square root of –1 took centuries, the same might be true of spinors.4 Dirac’s influence is felt most strongly by scientists studying the universe’s tiniest constituents. Experimenters can now smash particles together with energies so high that even Rutherford would have been impressed: at the Large Hadron Collider, the huge particle accelerator at CERN, they can recreate the conditions of the universe to within a millionth of a millionth of a second of the beginning of time. During the subatomic collisions produced in this and other accelerators, experimenters routinely see subatomic particles created and destroyed, processes that can be explained only using relativistic quantum field theory.

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Sapasvee Anagami 1 Isenstein, Harald 1, 2 n46 isotope separation 1, 2, 3, 4, 5 Israel 1 Ivanenko, Dmitry ‘Dimus’ 1, 2, 3 Jackson, Lydia (previously Elisaveta Fen) 1 Japan PD and Heisenberg visit 1 new militarism in 1 bombing of Hiroshima 1, 2 bombing of Nagasaki 1 surrender of 1 ‘Jazz Band’ (informal group of Soviet theorists) 1, 2 Jeans, Sir James 1, 2, 3 The Mysterious Universe 1 Jeffreys, Harold 1 ‘Jewish physics’ 200, 1 John Paul II, Pope 1 Joliot-Curie, Frédéric 1, 2 Joliot-Curie, Irène 1, 2, 3 Jones, Norman 1, 2n34, 3n8 Jordan, Pascual 1, 2, 3, 4 works with Born and Heisenberg at Göttingen 1, 2 and groups of electrons 1 personality 1 appearance 1 and field theory 1, 2 and the Dirac equation 1 Nazi past 1, 2 Joyce, James 1 Finnegans Wake 1 A Portrait of the Artist as a Young Man 1 Julius Road, Bristol (No.6) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24n33, 25n24 Kant, Immanuel and beauty 1, 2n54 and truth 1 Kapitza, Anna (‘Rat’) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 Kapitza, Peter 1, 2, 3, 4, 5, 6, 7, 8 settles in the UK 1 personality 1, 2, 3, 4 influences PD 1 resented by Blackett 1 obsession with the crocodile 1, 2, 3, 4n29 Russia’s industrialisation and electrification 1 relationship with Rutherford 1, 2, 3, 4, 5 compared with PD 1 supports Communist goals 1, 2 under surveillance 1, 2, 3, 4, 5, 6 sets up the Kapitza Club 1 attitude to experimental physics 1 marries Anna Krylova 1 co-edits the ‘International Series of Monographs on Physics’ 1 at the Cavendish Physical Society annual dinner 1 the Bukharin visit to Cambridge 1 MI5 monitors him 1, 2 vacation with PD in the Crimea 1 and the anti-electron 1 PD works with him in his laboratory 1, 2, 3, 4 detained by the Soviet Government 1, 2, 3 and Rutherford’s death 1 seeks Landau’s release 1, 2n40 wartime telegram to PD 1 nominated by PD for a Nobel Prize 1, 2n37 invents method of liquefying oxygen 1 ‘Hero of Socialist Labour’ 1 and Beria 1 in disgrace 1 letters to Stalin 1 and PD’s passion for beauty 1 visits Cambridge in 1966 1 Nobel Prize in Physics 1 death 1 PD spends his last hours talking about him 1 ‘The Training of the Young Scientist in the USSR’ 1 Kapitza-Dirac effect 1, 2, 3, 4, 5n27 Kapitza Club 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11n28, 12n52 Keats, John 1 Kennedy, John F. 1 Kent State University 1 ket 1 Keynes, John Maynard 1, 2, 3, 4 Kharkhov 1 Khrushchev, Nikita 1, 2, 3 Kierkegaard, Søren 1 Kitchener, Lord 1 Klampenborg Forest, Denmark 1 Klein, Oskar 1, 2, 3 n30 Koh-i-Noor restaurant, St John’s Street, Cambridge 1, 2n7 Kronborg castle, Denmark 1 Kubrick, Stanley 1 Kuhn, Thomas 1, 2 Kun, Béla 1, 2 Kursunoglu, Behram 1, 2, 3, 4n23 Kyoto 1 Labour government 1 Labour Party 1, 2, 3 Lagerlöf, Selma 1n10 Lagrange, Jopseph Louis 1 Lagrangian 1 Lake District 1, 2, 3 Lake Elmore 1 Lamb, Charles: ‘The Old Familiar Faces’ 1 Lamb, Willis 1, 2 Landau, Lev 1, 2, 3, 4, 5, 6, 7, 8, 9, 10n40 Landshoff, Peter 1n18 Langer, Rudolph 1 Lannutti, Joe 1 Large Hadron Collider 1 large numbers hypothesis 1, 2, 3, 4, 5n13 Larmor, Sir Joseph 1, 2, 3n44 lasers 1, 2, 3, 4 Lawrence, Ernest 1 Lawrence, T.E.: Seven Pillars of Wisdom 1 Lederman, Ellen 1, 2, 3n35 Lederman, Leon 1, 2, 3, 4, 5, 6n35 Lee, T. D. 1, 2, 3n63 left-right symmetry 1, 2n4 Leiden, Netherlands, PD visits 1, 2, 3, 4n5 Leipzig Heisenberg appointed full professor 1 PD in 1 Lemaître, Abbé Georges 1, 2, 3n52 Lenin, Vladimir 1, 2, 3, 4, 5, 6, 7 Leningrad, PD in 1, 2, 3 leptons 1, 2 Liberal Party 1, 2 Life magazine 1 light viewed as photons 1, 2, 3n20 in a continuous wave 1, 2, 3, 4 emitted and absorbed by atoms 1 energy of light tranferrable to atoms only in quanta (Planck) 1 as particles 1 see also radiation, electromagnetic Lindau, Germany 1965 meeting 1 1971 meeting 1 1982 meeting 1, 2n61 Lindemann, Frederick 1, 2, 3, 4 Lindstrom, Andy 1 Lippmann, Gabriel 1n21 Liverpool 1 Lloyd George, David 1, 2 Locarno, Treaty of (1925) 1, 2 logical positivists 1 London Charles Dirac in 1 in Second World War 1, 2, 3 Dirac family stays in 1 London Mathematical Society 1n16 Los Alamos headquarters, New Mexico 1, 2 Lost Lake, near Tallahassee 1 Lourdes 1 Lucasian Professorship of Mathematics 1, 2, 3, 4, 5 Luftwaffe 1, 2 Lyons, Eugene 1 McCarthy, Joseph 1 MacDonald, Ramsay 1, 2, 3, 4, 5 magnetic monopole 1, 2, 3, 4, 5, 6, 7, 8n5, 9n48 Manchester 1 Manchester Guardian 1, 2, 3, 4, 5, 6 Manchester University 1, 2 Manhattan, New York 1, 2, 3 Manhattan Project 1, 2, 3, 4, 5, 6, 7, 8 Martineau, Harriet 1n29 Marx, Karl 1 Marxism 1, 2, 3, 4, 5 mathematics aesthetic view of 1 applied 1, 2, 3, 4n7 beauty of 1, 2, 3, 4 Bohr’s attitude to 1 God as a mathematician 1, 2 mathematical rigour 1 PD’s sometimes cavalier attitude to 1 pragmatic approach to the mathematics of engineering 1 pure 1, 2, 3, 4n6 game in which people invent the rules, PD’s view as 1 matrices and electron spin 1 Heisenberg’s quantum theory 1, 2, 3 MAUD committee 1, 2n3 Maugham, W.

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 incidence of people playing computers in chess, backgammon, and now Go has been steadily increasing since the advent of computer programs that play at championship levels, and so has the machine augmented intelligence of the human players.40 Deep learning will boost the intelligence not just of scientific investigators but of workers in all professions. Scientific instruments are generating data at prodigious rate. Elementary particle collisions at the Large Hadron Collider (LHC) in Geneva generate 25 petabyes of data each year. The Large Synoptic Sky Telescope (LSST) will generate 6 petabytes of data each year. Machine learning is being used to analyze the huge physics and astronomy datasets that are too big for humans to search by traditional methods.41 For example, DeepLensing is a neural network that recognizes images of distant galaxies that have been distorted by light bending by “gravitational lenses” around another galaxy along the line of sight.

Radical Abundance: How a Revolution in Nanotechnology Will Change Civilization by K. Eric Drexler

3D printing, additive manufacturing, agricultural Revolution, Bill Joy: nanobots, Brownian motion, carbon footprint, Cass Sunstein, conceptual framework, continuation of politics by other means, crowdsourcing, dark matter, data science, double helix, failed state, Ford Model T, general purpose technology, global supply chain, Higgs boson, industrial robot, iterative process, Large Hadron Collider, Mars Rover, means of production, Menlo Park, mutually assured destruction, Neil Armstrong, New Journalism, Nick Bostrom, performance metric, radical decentralization, reversible computing, Richard Feynman, Silicon Valley, South China Sea, Thomas Malthus, V2 rocket, Vannevar Bush, Vision Fund, zero-sum game

Chemical engineers investigate chemical systems, testing combinations of reactants, temperature, pressure, and time in search of conditions that maximize product yield; they may undertake inquiries every day, yet in the end their experiments support engineering design and analysis. Conversely, experimental physicists undertake engineering when they develop machines like the Large Hadron Collider. With its tunnels, vacuum systems, superconducting magnets, and ten-thousand-ton particle detectors, this machine demanded engineering design on a grand scale, yet all as part of a program of scientific inquiry.* But the close, intertwining links between scientific inquiry and engineering design can obscure how deeply they differ.

The Future of Fusion Energy by Jason Parisi, Justin Ball

Albert Einstein, Arthur Eddington, Boeing 747, carbon footprint, carbon tax, Colonization of Mars, cuban missile crisis, decarbonisation, electricity market, energy security, energy transition, heat death of the universe, Intergovernmental Panel on Climate Change (IPCC), invention of the steam engine, ITER tokamak, Kickstarter, Large Hadron Collider, megaproject, Mikhail Gorbachev, mutually assured destruction, nuclear winter, performance metric, profit motive, random walk, Richard Feynman, Ronald Reagan, Stuxnet, the scientific method, time dilation, uranium enrichment

Chapter 7 The Present: ITER ITER is a huge tokamak and one of the most ambitious science experiments ever. It is expected to be the first device in human history to confine a plasma that generates more fusion power than the heating power needed to sustain it. ITER, alongside scientific megaprojects like the International Space Station and the Large Hadron Collider, help to define humanity and our capacity for international collaboration. While you may not realize this, chances are high that ITER is being built in your name. This is because it is the biggest scientific collaboration ever, with 35 countries (representing over half the world’s population) contributing time, money, and components.

Pathfinders: The Golden Age of Arabic Science by Jim Al-Khalili

agricultural Revolution, Albert Einstein, Andrew Wiles, Book of Ingenious Devices, colonial rule, Commentariolus, Dmitri Mendeleev, Eratosthenes, Henri Poincaré, invention of the printing press, invention of the telescope, invention of the wheel, Isaac Newton, Islamic Golden Age, Johannes Kepler, Joseph Schumpeter, Kickstarter, Large Hadron Collider, liberation theology, retrograde motion, scientific worldview, Silicon Valley, Simon Singh, stem cell, Stephen Hawking, the scientific method, Thomas Malthus, time dilation, trade route, William of Occam

But despite this incredible legacy, Ptolemy made surprisingly few astronomical observations himself – unlike Hipparchus – and what he did make he often failed to report correctly.1 The observatory that al-Ma’mūn commissioned in Baghdad to check many of the Greek observations reported in the Almagest was probably the world’s first state-funded large-scale science project. Modern science often involves the participation of thousands of scientists in multinational, multi-billion-dollar projects such as the Large Hadron Collider at CERN in Geneva. What al-Ma’mūn achieved, albeit on a far more modest scale, would produce no less spectacular results. He put together an impressive team of mathematicians, astronomers and geographers to work on three major projects that would have been impossible for one man working alone.

Think Like a Rocket Scientist: Simple Strategies You Can Use to Make Giant Leaps in Work and Life by Ozan Varol

Abraham Maslow, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, Amazon Web Services, Andrew Wiles, Apollo 11, Apollo 13, Apple's 1984 Super Bowl advert, Arthur Eddington, autonomous vehicles, Ben Horowitz, Boeing 747, Cal Newport, Clayton Christensen, cloud computing, Colonization of Mars, dark matter, delayed gratification, different worldview, discovery of DNA, double helix, Elon Musk, fail fast, fake news, fear of failure, functional fixedness, Gary Taubes, Gene Kranz, George Santayana, Google Glasses, Google X / Alphabet X, Inbox Zero, index fund, Isaac Newton, it is difficult to get a man to understand something, when his salary depends on his not understanding it, James Dyson, Jeff Bezos, job satisfaction, Johannes Kepler, Kickstarter, knowledge worker, Large Hadron Collider, late fees, lateral thinking, lone genius, longitudinal study, Louis Pasteur, low earth orbit, Marc Andreessen, Mars Rover, meta-analysis, move fast and break things, multiplanetary species, Neal Stephenson, Neil Armstrong, Nick Bostrom, obamacare, Occam's razor, out of africa, Peter Pan Syndrome, Peter Thiel, Pluto: dwarf planet, private spaceflight, Ralph Waldo Emerson, reality distortion field, Richard Feynman, Richard Feynman: Challenger O-ring, Ronald Reagan, Sam Altman, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, Simon Singh, Skinner box, SpaceShipOne, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, subprime mortgage crisis, sunk-cost fallacy, TED Talk, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Tyler Cowen, Upton Sinclair, Vilfredo Pareto, We wanted flying cars, instead we got 140 characters, Whole Earth Catalog, women in the workforce, Yogi Berra

For centuries, the scientific community was split into two camps, with one camp believing light is a particle like motes of dust and others arguing it’s a wave, like the ripples in the water. It turned out that both camps were right (or wrong, depending on how you view it). Light straddled these two categories and exhibited the properties of both a particle and a wave. The Large Hadron Collider is a seventeen-mile particle accelerator that smashes together subatomic particles called hadrons. Their collision has been described as “less of a collision and more of a symphony.”26 When hadrons collide, they actually glide through each other, and “their fundamental components pass so close together that they can talk to each other.”27 If this symphony plays out the right way, the colliding hadrons “can pluck deep hidden fields that will sing their own tune in response—by producing new particles.”28 Multiple hypotheses dance with each other the same way.

The Invention of Science: A New History of the Scientific Revolution by David Wootton

agricultural Revolution, Albert Einstein, book value, British Empire, classic study, clockwork universe, Commentariolus, commoditize, conceptual framework, Dava Sobel, double entry bookkeeping, double helix, en.wikipedia.org, Ernest Rutherford, Fellow of the Royal Society, fudge factor, germ theory of disease, Google X / Alphabet X, Hans Lippershey, interchangeable parts, invention of gunpowder, invention of the steam engine, invention of the telescope, Isaac Newton, Jacques de Vaucanson, James Watt: steam engine, Johannes Kepler, John Harrison: Longitude, knowledge economy, Large Hadron Collider, lateral thinking, lone genius, Mercator projection, On the Revolutions of the Heavenly Spheres, Philip Mirowski, placebo effect, QWERTY keyboard, Republic of Letters, social intelligence, spice trade, spinning jenny, Suez canal 1869, tacit knowledge, technological determinism, the scientific method, Thomas Kuhn: the structure of scientific revolutions

Experientia and experimentum (‘experience’ and ‘experiment’) are more or less synonymous in classical, medieval and early modern Latin, and all the modern languages that have both words initially reflect the Latin usage.7 In modern English the distinction is clear: going to the ballet is an experience; the Large Hadron Collider is an experiment. But this distinction emerged slowly and became firmly established only during the course of the eighteenth century. The OED gives 1727 as the last date at which ‘experiment’ as a verb was used to mean ‘experience’, and 1763 as the last date at which ‘experience’ as a noun was used to mean ‘experiment’.iii Insensitive to this change of meaning, scholars frequently translate the word experimentum in Latin texts as ‘experiment’, thus often giving a totally false impression of its meaning, which is commonly ‘experience’.

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Collingwood) 431 Imaginary Invalid, The (Molière) 393 immutable mobiles 303 impetus theory 574 Index of Prohibited Books 276, 379 indexes, importance of 305n India 128, 137, 177 Indiscreet Jewels, The (Denis Diderot) 51 Industrial Revolution clockwork facilitates 486 contribution of science to 479, 508 early medieval forerunner 484 effect and duration 18, 429 geared machinery 484 precision instrumentation of 423 Scientific Revolution and 13, 17, 19, 476 16th century progress claimed 431, 446 skills involved 445 steam engine and 490 inertia 19, 50, 372 Ingrassia, Giovanni Filippo 85, 95, 96 Inquisition (Roman) Bruno burnt alive 10, 149 della Porta and 276 Descartes and 362 Galileo condemned by 37, 107, 545 Stellato before 157 torture by 314–15 Institutes of the Orator (Quintilian) 403 Institutiones (Cassiodorus) 451n instruments, scientific 209, 244–5, 560 Instruments for the Restoration of Anatomy (Tycho Brahe) 180 intellectual property 337 Intelligent Design 445 internet, the 593–4 interpretation 83 Interpreter, The (John Cowell) 402 Introductio ad veram physicam (John Keill) 473 Introductio geographica (Peter Apian) 189 Introduction to the Study of Experimental Medicine, An (Claude Bernard) 426 invention 61n, 66–7, 82n Isaac, Joel 585–6 Isis 512 Islam 37, 66, 113 Italian (language) 30 Jackson, Thomas 402 James I, King 159 (and see below) James VI, King (of Scotland) 6, 10 (and see above) Jansen, Cornelius 289–90 Jansenism 295, 297 Japanese 484 Jardin des Plantes, Paris 356 Jerusalem 115n, 119, 120 Jesuits Aristotle and the new science 537n Clavius leading astronomer of 118 Galileo and 37, 197n, 225, 226 Gilbert’s ideas and 324, 328 missionaries 7 scholastic philosophers at colleges 31 van Helmont and 291 Venus orbiting the sun 24n Jews 66, 76 John of Glogau 72 John of Jandun 114 John of Saxony 337 John of Wallingford 118 Johns, Adrian 26n Johnson, Dr Samuel 26, 284, 474 Jones, William 564 Jonson, Ben 9, 355 Joubert, Laurent 304 Journal des sçavans 341 Jovilabe 480 Judaei, Themo 117, 135, 326 judgement 422 Julius Caesar 99 Julius Caesar (William Shakespeare) 5 Jupiter, moons of difficulties caused by 218 eclipses of 480 Galileo discovers 38, 86, 88, 407 Kepler’s terminology for 48 measuring longitudes by 481 naming of 96, 99 rapid confirmation of discovery 89, 92, 237 Rømer’s work 518 use as a clock, 215 juries 407, 419, 426 Kant, Immanuel 327 Kay, John 484 Keill, John 473 Kelley, Donald 551 Kepler, Johannes 211–14, 262–6 barnacle geese 268 conflating maths and natural philosophy 24n contacts Galileo and responses from 220–1, 224 contemporary knowledge of 8 Conversation with Galileo’s Starry Messenger 9, 302 Epitome astronomiae Copernicanae 130n, 152n, 252 escaping from circular movement 390n Gilbert’s model of magnetism and 329, 516–17 his teacher 192 Holy Roman Emperor and 31 hypotheses, types of 386–7 infinite size of universe 243 laws of planetary motion 11 Mars and 193, 301, 305 mathematician, as 424 Mercury in transit 223n Newton on 376, 393 on published writings 198n printing press recognised by 306 Rudolphine tables 307 satellites 48 sea and land levels 130n speed of light measurements and 521 universe as a clock 485 variety of publications by 205 King, Gregory 259, 260 Kircher, Athanasius 279 Knauss, Friedrich von 445 Knieper, Hans 196 knowledge access to 78–9 Aristotle’s concept of 68 as power 83–4 circulation of 340–1 experience and 81, 125n, 253, 320, 341, 421 fact as basis of 252, 297, 309 gained from discovery 80–1 Gassendi’s theory of 410 Hobbes on 298, 546, 548–9 ‘knowledge economy’ 479 Locke on 405, 420 Merton on 96 Montaigne on 557, 559, 561 new concepts of 397 no new knowledge to be had 62, 74, 78, 104 OED distinctions 420 Renaissance attitudes 73 sensation and 322 types of 323, 395n various attitudes to 321 vocabulary to be used 541–2 Wittgenstein on 23, 45 Knowledge and Social Imagery (David Bloor) 580, 589 Koch, Robert 540 Kosmotheoros (Christiaan Huygens) 234 Koyré, Alexandre coining ‘Scientific Revolution’ 16, 17, 20 ideas of place and space 19 quoted 595 science and progress 512 thought, importance of 50 Kuhn, Thomas see also Structure of Scientific Revolutions, The alternative views of science 538, 542, 543 coining ‘Copernican Revolution’ 18, 55, 145 see also On the Revolutions of the Heavenly Spheres (Nicolaus Copernicus) communication between different intellectual worlds 46n Conant and 394, 544 consensus science 346 Copernicanism triumphs 516 Copernicus and Tycho Brahe 13n Isaac on 585–6 Koyré’s influence 19 new approach of 561–2 on Newton 382 on reading outdated texts 110–11 opposition of science and technology 479 phases of Venus 246n Ptolemaic science 573 publishes on English and French approaches 425–6 quoted 251 science and progress 512–13, 541 Wittgenstein and 45 ‘Kuhn loss’ 554n la Boëtie, Étienne de 555, 556, 557 La Condition postmoderne (Jean-François Lyotard) 41 La Mettrie, Julien Offray de 439 Lactantius 81 language 42n, 46–51, 53, 63–5, 579 Lanzarote 98n Large Hadron Collider 312 Laski, Harold J. 17, 19 Late Discourse (Kenelm Digby) 293 latent heat 478 Latin Cambridge entrance requirement 15 cloud names 47 Columbus and Galileo 57–8 experience and experiment 312, 347 ‘fact’, the word 254–5, 283–4, 289, 295 Lily’s Grammar 547 ‘scientific’, the word, and 29 Latin Dictionary, A (eds.

The One Device: The Secret History of the iPhone by Brian Merchant

Airbnb, animal electricity, Apollo Guidance Computer, Apple II, Apple's 1984 Super Bowl advert, Black Lives Matter, Charles Babbage, citizen journalism, Citizen Lab, Claude Shannon: information theory, computer vision, Computing Machinery and Intelligence, conceptual framework, cotton gin, deep learning, DeepMind, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, Ford paid five dollars a day, Frank Gehry, gigafactory, global supply chain, Google Earth, Google Hangouts, Higgs boson, Huaqiangbei: the electronics market of Shenzhen, China, information security, Internet of things, Jacquard loom, John Gruber, John Markoff, Jony Ive, Large Hadron Collider, Lyft, M-Pesa, MITM: man-in-the-middle, more computing power than Apollo, Mother of all demos, natural language processing, new economy, New Journalism, Norbert Wiener, offshore financial centre, oil shock, pattern recognition, peak oil, pirate software, profit motive, QWERTY keyboard, reality distortion field, ride hailing / ride sharing, rolodex, Shenzhen special economic zone , Silicon Valley, Silicon Valley startup, skeuomorphism, skunkworks, Skype, Snapchat, special economic zone, speech recognition, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, TED Talk, Tim Cook: Apple, Tony Fadell, TSMC, Turing test, uber lyft, Upton Sinclair, Vannevar Bush, zero day

We take a couple wrong turns as we wander through an endless series of hallways. “There is no logic to the numbering of the buildings,” Mazur says. We’re currently in building 1, but the structure next door is building 50. “So someone finally made an app for iPhone to help people find their way. I use it all the time.” CERN is best known for its Large Hadron Collider, the particle accelerator that runs under the premises in a seventeen-mile subterranean ring. It’s the facility where scientists found the Higgs boson, the so-called God particle. For decades, CERN has been host to a twenty-plus-nation collaboration, a haven that transcends geopolitical tensions to foster collaborative research.

The Future of the Professions: How Technology Will Transform the Work of Human Experts by Richard Susskind, Daniel Susskind

23andMe, 3D printing, Abraham Maslow, additive manufacturing, AI winter, Albert Einstein, Amazon Mechanical Turk, Amazon Robotics, Amazon Web Services, Andrew Keen, Atul Gawande, Automated Insights, autonomous vehicles, Big bang: deregulation of the City of London, big data - Walmart - Pop Tarts, Bill Joy: nanobots, Blue Ocean Strategy, business process, business process outsourcing, Cass Sunstein, Checklist Manifesto, Clapham omnibus, Clayton Christensen, clean water, cloud computing, commoditize, computer age, Computer Numeric Control, computer vision, Computing Machinery and Intelligence, conceptual framework, corporate governance, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, death of newspapers, disintermediation, Douglas Hofstadter, driverless car, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, Filter Bubble, full employment, future of work, Garrett Hardin, Google Glasses, Google X / Alphabet X, Hacker Ethic, industrial robot, informal economy, information retrieval, interchangeable parts, Internet of things, Isaac Newton, James Hargreaves, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, knowledge economy, Large Hadron Collider, lifelogging, lump of labour, machine translation, Marshall McLuhan, Metcalfe’s law, Narrative Science, natural language processing, Network effects, Nick Bostrom, optical character recognition, Paul Samuelson, personalized medicine, planned obsolescence, pre–internet, Ray Kurzweil, Richard Feynman, Second Machine Age, self-driving car, semantic web, Shoshana Zuboff, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, Susan Wojcicki, tacit knowledge, TED Talk, telepresence, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, transaction costs, Turing test, Two Sigma, warehouse robotics, Watson beat the top human players on Jeopardy!, WikiLeaks, world market for maybe five computers, Yochai Benkler, young professional

Zuboff termed this the ‘informating power of intelligent technology’.35 Although the term ‘informating’ did not catch on, her main insight is now received wisdom—that analysis of large bodies of data generated by our technologies can provide us with valuable new insights, and can help us make more responsible predictions in many fields. The discipline that has emerged to specialize in this capture and analysis of information is now popularly referred to as ‘Big Data’. When this term was first used, it was confined to techniques for the handling of vast bodies of data—for example, the masses of data recorded by the Large Hadron Collider. Now, Big Data is also used to refer to the use of technology to analyse much smaller bodies of information. Some speak instead of ‘data analytics’, ‘data science’, and ‘predictive analytics’, all of which seem to mean roughly the same thing.36 Specialists in the area, whatever label is preferred, are often called ‘data scientists’.

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