Ethereum

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Mastering Ethereum: Building Smart Contracts and DApps by Andreas M. Antonopoulos, Gavin Wood Ph. D.

Amazon Web Services, bitcoin, blockchain, continuous integration, cryptocurrency, Debian, domain-specific language, don't repeat yourself, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, Firefox, Google Chrome, intangible asset, Internet of things, litecoin, move fast and break things, move fast and break things, node package manager, peer-to-peer, Ponzi scheme, prediction markets, pull request, QR code, Ruby on Rails, Satoshi Nakamoto, sealed-bid auction, sharing economy, side project, smart contracts, transaction costs, Turing complete, Turing machine, Vickrey auction, web application, WebSocket

Building Geth from source code To build Geth, change to the directory where the source code was downloaded and use the make command: $ cd go-ethereum $ make geth If all goes well, you will see the Go compiler building each component until it produces the geth executable: build/env.sh go run build/ci.go install ./cmd/geth >>> /usr/local/go/bin/go install -ldflags -X main.gitCommit=58a1e13e6dd7f52a1d... github.com/ethereum/go-ethereum/common/hexutil github.com/ethereum/go-ethereum/common/math github.com/ethereum/go-ethereum/crypto/sha3 github.com/ethereum/go-ethereum/rlp github.com/ethereum/go-ethereum/crypto/secp256k1 github.com/ethereum/go-ethereum/common [...] github.com/ethereum/go-ethereum/cmd/utils github.com/ethereum/go-ethereum/cmd/geth Done building. Run "build/bin/geth" to launch geth. $ Let’s make sure geth works without actually starting it running: $ ./build/bin/geth version Geth Version: 1.6.6-unstable Git Commit: 58a1e13e6dd7f52a1d5e67bee47d23fd6cfdee5c Architecture: amd64 Protocol Versions: [63 62] Network Id: 1 Go Version: go1.8.3 Operating System: linux [...]

-What This Book Will Teach You and EVM, Introducing the World Computer as general-purpose blockchain, Ethereum: A General-Purpose Blockchain basics, Ethereum Basics-Conclusions birth of, The Birth of Ethereum Bitcoin compared to, Compared to Bitcoin blockchain components, Components of a Blockchain, Ethereum’s Components clients (see clients, Ethereum) control and responsibility, Control and Responsibility-Control and Responsibility currency units, Ether Currency Units DApps and, From General-Purpose Blockchains to Decentralized Applications (DApps) development culture, Ethereum’s Development Culture EIPs, Ethereum Improvement Proposals (EIPs) EOAs and contracts, Externally Owned Accounts (EOAs) and Contracts Ethereum Classic compared to, Ethereum and Ethereum Classic fork history, Ethereum Fork History-Other Notable Ethereum Forks four stages of development, Ethereum’s Four Stages of Development MetaMask basics, Getting Started with MetaMask-Exploring the Transaction History of an Address purpose of, Compared to Bitcoin reasons to learn, Why Learn Ethereum? standards, Ethereum Improvement Proposals (EIPs) Turing completeness and, Ethereum and Turing Completeness wallet choices, Choosing an Ethereum Wallet web3 and, The Third Age of the Internet Ethereum Classic (ETC)Emerald Wallet and, Choosing an Ethereum Wallet Ethereum compared to, Ethereum and Ethereum Classic origins, Ethereum Classic (ETC), The DAO Hard Fork Ethereum Improvement Proposals (see EIP entries) Ethereum Modification (EMOD), Other Notable Ethereum Forks Ethereum Name Service (see ENS) Ethereum Virtual Machine (see EVM) EthereumFog (ETF), Other Notable Ethereum Forks EthereumJS, Raw Transaction Creation and Signing, EthereumJS EthereumJS helpeth, Inter Exchange Client Address Protocol, EthereumJS helpeth: A Command-Line Utility EtherInc (ETI), Other Notable Ethereum Forks EtherJar, EtherJar Etherpot smart contract lottery, Real-World Example: Etherpot and King of the Ether ethers.js, ethers.js EtherZero (ETZ), Other Notable Ethereum Forks ethpm project, Contract Libraries Ethstick contract, Real-World Example: Ethstick ETI (EtherInc), Other Notable Ethereum Forks eventscatching, Catching events defined, Quick Glossary Solidity, Events-Catching events EVM (Ethereum Virtual Machine), The Ethereum Virtual Machine-Conclusionsabout, What Is the EVM?

-What This Book Will Teach You and EVM, Introducing the World Computer as general-purpose blockchain, Ethereum: A General-Purpose Blockchain basics, Ethereum Basics-Conclusions birth of, The Birth of Ethereum Bitcoin compared to, Compared to Bitcoin blockchain components, Components of a Blockchain, Ethereum’s Components clients (see clients, Ethereum) control and responsibility, Control and Responsibility-Control and Responsibility currency units, Ether Currency Units DApps and, From General-Purpose Blockchains to Decentralized Applications (DApps) development culture, Ethereum’s Development Culture EIPs, Ethereum Improvement Proposals (EIPs) EOAs and contracts, Externally Owned Accounts (EOAs) and Contracts Ethereum Classic compared to, Ethereum and Ethereum Classic fork history, Ethereum Fork History-Other Notable Ethereum Forks four stages of development, Ethereum’s Four Stages of Development MetaMask basics, Getting Started with MetaMask-Exploring the Transaction History of an Address purpose of, Compared to Bitcoin reasons to learn, Why Learn Ethereum?


pages: 349 words: 102,827

The Infinite Machine: How an Army of Crypto-Hackers Is Building the Next Internet With Ethereum by Camila Russo

4chan, Airbnb, algorithmic trading, altcoin, always be closing, Any sufficiently advanced technology is indistinguishable from magic, Asian financial crisis, bitcoin, blockchain, Burning Man, crowdsourcing, cryptocurrency, distributed ledger, diversification, Donald Trump, East Village, Ethereum, ethereum blockchain, Flash crash, Google Glasses, Google Hangouts, hacker house, Internet of things, Mark Zuckerberg, Maui Hawaii, mobile money, new economy, peer-to-peer, Peter Thiel, pets.com, Ponzi scheme, prediction markets, QR code, reserve currency, RFC: Request For Comment, Richard Stallman, Robert Shiller, Robert Shiller, Sand Hill Road, Satoshi Nakamoto, semantic web, sharing economy, side project, Silicon Valley, Skype, slashdot, smart contracts, South of Market, San Francisco, the payments system, too big to fail, tulip mania, Turing complete, Uber for X

uid=CHE-292.124.800#. 3. in an online chat: Pete Dushenski, “A Guide to Buying 5000 Ether/Bitcoin, 2.5x More Than Ethereum’s Genesis Sale Offers,” Contravex (blog), July 23, 2014, http://www.contravex.com/2014/07/23/a-guide-to-buying-5000-ether-bitcoin-2-5x-more-than-ethereums-genesis-sale/. 15: The Ether Sale 1. prices in September 2014: Vitalik Buterin, “Launching the Ether Sale,” Ethereum Foundation Blog, July 22, 2014, https://blog.ethereum.org/2014/07/22/launching-the-ether-sale/. 2. “let’s do this”: EtherCasts, “Ethereum Pre-Sale,” YouTube, uploaded July 23, 2014, https://www.youtube.com/watch?feature=player_embedded&v=2PAHMxQCDAQ#t=216. 3. “other,” Mihai wrote: Mihai Alisie, “Mihai’s Ethereum Project Update. The First Year,” Ethereum Foundation Blog, March 14, 2015, https://blog.ethereum.org/2015/03/14/ethereum-the-first-year/. 4. a lot of people: Preston Byrne, “Whether Ether Is a Security,” Preston Byrne (blog), April 23, 2018, https://prestonbyrne.com/2018/04/23/on-ethereum-security/. 5.

“Paul,” he said: Paul is a pseudonym for the investor’s real name. 2. bugs or setbacks: Vitalik Buterin, “Olympic: Frontier Pre-Release,” Ethereum Foundation Blog, May 9, 2015, https://blog.ethereum.org/2015/05/09/olympic-frontier-pre-release/. 3. 4:26 p.m. in Berlin: Etherscan, Block #1, https://etherscan.io/block/1. 4. someone else wrote: Ethereum/go-Ethereum chat archives, Gitter, 2015, https://gitter.im/ethereum/go-ethereum/archives/2015/07/30. 17: The Shrinking Runway 1. “anyhow,” Vitalik wrote: “We just went from $530 to sub $500 in under a minute,” Reddit thread, 2014, https://www.reddit.com/r/Bitcoin/comments/2diqyy/we_just_went_from_530_to_sub_500_in_under_a/cjpxgln/. 2. “a little under two”: Vitalik Buterin, “The Evolution of Ethereum,” Ethereum Foundation Blog, September 28, 2015, https://blog.ethereum.org/2015/09/28/the-evolution-of-ethereum/. 3. Web 3 dream a reality: Gavin Wood, “The Last Blog Post,” Ethereum Foundation Blog, January 11, 2016, https://blog.ethereum.org/2016/01/11/last-blog-post/. 18: The First Dapps 1. Ethereum smart contracts: Jack Peterson, Joseph Krug, Micah Zoltu, Austin K. Williams, and Stephanie Alexander, “Augur: A Decentralized Oracle and Prediction Market Platform (v2.0),” November 1, 2019, https://www.augur.net/whitepaper.pdf. 2. he wrote on GitHub: Vitalik Buterin, “Standardized_Contract_APIs,” GitHub, June 23, 2015, https://github.com/ethereum/wiki/wiki/Standardized_Contract_APIs/499c882f3ec123537fc2fccd57eaa29e6032fe4a. 3. with their thoughts: Alex Van de Sande, “Let's talk about the coin standard,” Reddit, 2015, https://www.reddit.com/r/ethereum/comments/3n8fkn/lets_talk_about_the_coin_standard/. 4. issue being discussed: Fabian Vogelsteller, “ERC: Token standard #20,” GitHub, November 19, 2015, https://github.com/ethereum/EIPs/issues/20. 5. ended up implementing: Rune Christensen, “Introducing eDollar, the ultimate stablecoin built on Ethereum,” Reddit, 2015, https://www.reddit.com/r/ethereum/comments/30f98i/introducing_edollar_the_ultimate_stablecoin_built/. 6. companies to build on: Jeff Wilcke, “Homestead Release,” Ethereum Foundation Blog, February 29, 2016, https://blog.ethereum.org/2016/02/29/homestead-release/. 7. world had Ethereum: Gavin Andresen, “Bit-thereum,” GavinTech (blog), June 9, 2014, http://gavintech.blogspot.com/2014/06/bit-thereum.html. 19: The Magic Lock 1.

lang=en. 21: The Fork 1. called “DAO Wars”: Peter Szilagyi, “DAO Wars: Your Voice on the Soft-Fork Dilemma,” Ethereum Foundation Blog, June 24, 2016, https://blog.ethereum.org/2016/06/24/dao-wars-youre-voice-soft-fork-dilemma/. 2. jam up the network: Tjaden Hess, River Keefer, and Emin Gun Sirer, “Ethereum’s DAO Wars Soft Fork Is a Potential DoS Vector,” Hacking, Distributed, June 28, 2016, http://hackingdistributed.com/2016/06/28/ethereum-soft-fork-dos-vector/. 3. running the show: Peter Szilagyi, “The Network Strikes Back (1.4.9),” GitHub, June 29, 2016, https://github.com/ethereum/go-ethereum/releases/tag/v1.4.9. 4. the software upgrade: Andreas M. Antonopoulos, “Ethereum Fork History,” Ethereum Book, GitHub, 2016, https://github.com/ethereumbook/ethereumbook/blob/3a21b603899e27427ca64fc5d3fd57af96a3cbd8/forks-history.asciidoc. 5. worked without a glitch: Alex Van de Sande (@avsa), “Watching the successful hard fork.


Mastering Blockchain, Second Edition by Imran Bashir

3D printing, altcoin, augmented reality, autonomous vehicles, bitcoin, blockchain, business process, carbon footprint, centralized clearinghouse, cloud computing, connected car, cryptocurrency, data acquisition, Debian, disintermediation, disruptive innovation, distributed ledger, domain-specific language, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, Firefox, full stack developer, general-purpose programming language, gravity well, interest rate swap, Internet of things, litecoin, loose coupling, MITM: man-in-the-middle, MVC pattern, Network effects, new economy, node package manager, Oculus Rift, peer-to-peer, platform as a service, prediction markets, QR code, RAND corporation, Real Time Gross Settlement, reversible computing, RFC: Request For Comment, RFID, ride hailing / ride sharing, Satoshi Nakamoto, single page application, smart cities, smart contracts, smart grid, smart meter, supply-chain management, transaction costs, Turing complete, Turing machine, web application, x509 certificate

This is usually the case in private blockchain distributed ledger networks, where a private group of entities start their blockchain and use it as a permissioned blockchain. The following table shows the list of Ethereum network with their network IDs. These network IDs are used to identify the network by Ethereum clients. Network name Network ID / Chain ID Ethereum mainnet 1 Morden 2 Ropsten 3 Rinkeby 4 Kovan 42 Ethereum Classic mainnet 61 More discussion on how to connect to testnet and how to set up private nets will be discussed in Chapter 12, Ethereum Development Environment. Components of the Ethereum ecosystem The Ethereum blockchain stack consists of various components. At the core, there is the Ethereum blockchain running on the peer-to-peer Ethereum network. Secondly, there's an Ethereum client (usually Geth) that runs on the nodes and connects to the peer-to-peer Ethereum network from where blockchain is downloaded and stored locally.

Topics such as history, the definition of smart contracts, Ricardian contracts, Oracles, and the theoretical aspects of smart contracts are presented in this chapter. Chapter 10, Ethereum 101, introduces the design and architecture of the Ethereum blockchain in detail. It covers various technical concepts related to the Ethereum blockchain that explains the underlying principles, features, and components of this platform in depth. Chapter 11, Further Ethereum, continues the introduction of Ethereum from pervious chapter and covers topics related to Ethereum Virtual Machine, mining and supporting protocols for Ethereum. Chapter 12, Ethereum Development Environment, covers the topics related to setting up private networks for Ethereum smart contract development and programming. Chapter 13, Development Tools and Frameworks, provides a detailed practical introduction to the Solidity programming language and different relevant tools and frameworks that are used for Ethereum development.

PacktPub.com Contributors About the author About the reviewer Packt is searching for authors like you Preface Who this book is for What this book covers To get the most out of this book Download the example code files Download the color images Conventions used Get in touch Reviews Blockchain 101 The growth of blockchain technology Distributed systems The history of blockchain and Bitcoin Electronic cash Blockchain Blockchain defined Peer-to-peer Distributed ledger Cryptographically-secure Append-only Updateable via consensus Generic elements of a blockchain How blockchain works How blockchain accumulates blocks Benefits and limitations of blockchain Tiers of blockchain technology Features of a blockchain Types of blockchain Distributed ledgers Distributed Ledger Technology Public blockchains Private blockchains Semiprivate blockchains Sidechains Permissioned ledger Shared ledger Fully private and proprietary blockchains Tokenized blockchains Tokenless blockchains Consensus Consensus mechanism Types of consensus mechanisms Consensus in blockchain CAP theorem and blockchain Summary Decentralization Decentralization using blockchain Methods of decentralization Disintermediation Contest-driven decentralization Routes to decentralization How to decentralize The decentralization framework example Blockchain and full ecosystem decentralization Storage Communication Computing power and decentralization Smart contracts Decentralized Organizations Decentralized Autonomous Organizations Decentralized Autonomous Corporations Decentralized Autonomous Societies Decentralized Applications (DApps) Requirements of a Decentralized Application Operations of a DApp DApp examples KYC-Chain OpenBazaar Lazooz Platforms for decentralization Ethereum MaidSafe Lisk Summary Symmetric Cryptography Working with the OpenSSL command line Introduction Mathematics Set Group Field A finite field Order An abelian group Prime fields Ring A cyclic group Modular arithmetic Cryptography Confidentiality Integrity Authentication Entity authentication Data origin authentication Non-repudiation Accountability Cryptographic primitives Symmetric cryptography Stream ciphers Block ciphers Block encryption mode Electronic Code Book Cipher Block Chaining Counter mode Keystream generation mode Message authentication mode Cryptographic hash mode Data Encryption Standard Advanced Encryption Standard How AES works Summary Public Key Cryptography Asymmetric cryptography Integer factorization Discrete logarithm Elliptic curves Public and private keys RSA Encryption and decryption using RSA Elliptic Curve Cryptography Mathematics behind ECC Point addition Point doubling Discrete logarithm problem in ECC RSA using OpenSSL RSA public and private key pair Private key Public key Exploring the public key Encryption and decryption Encryption Decryption ECC using OpenSSL ECC private and public key pair Private key Private key generation Hash functions Compression of arbitrary messages into fixed-length digest Easy to compute Preimage resistance Second preimage resistance Collision resistance Message Digest Secure Hash Algorithms Design of Secure Hash Algorithms Design of SHA-256 Design of SHA-3 (Keccak) OpenSSL example of hash functions Message Authentication Codes MACs using block ciphers Hash-based MACs Merkle trees Patricia trees Distributed Hash Tables Digital signatures RSA digital signature algorithm Sign then encrypt Encrypt then sign Elliptic Curve Digital Signature Algorithm How to generate a digital signature using OpenSSL ECDSA using OpenSSL Homomorphic encryption Signcryption Zero-Knowledge Proofs Blind signatures Encoding schemes Financial markets and trading Trading Exchanges Orders and order properties Order management and routing systems Components of a trade The underlying instrument General attributes Economics Sales Counterparty Trade life cycle Order anticipators Market manipulation Summary Introducing Bitcoin Bitcoin Bitcoin definition Bitcoin – a bird's-eye view Sending a payment to someone Digital keys and addresses Private keys in Bitcoin Public keys in Bitcoin Addresses in Bitcoin Base58Check encoding Vanity addresses Multisignature addresses Transactions The transaction life cycle Transaction fee Transaction pools The transaction data structure Metadata Inputs Outputs Verification The script language Commonly used opcodes Types of transactions Coinbase transactions Contracts Transaction verification Transaction malleability Blockchain The structure of a block The structure of a block header The genesis block Mining Tasks of the miners Mining rewards Proof of Work (PoW) The mining algorithm The hash rate Mining systems CPU GPU FPGA ASICs Mining pools Summary Bitcoin Network and Payments The Bitcoin network Wallets Non-deterministic wallets Deterministic wallets Hierarchical Deterministic wallets Brain wallets Paper wallets Hardware wallets Online wallets Mobile wallets Bitcoin payments Innovation in Bitcoin Bitcoin Improvement Proposals (BIPs) Advanced protocols Segregated Witness (SegWit) Bitcoin Cash Bitcoin Unlimited Bitcoin Gold Bitcoin investment and buying and selling bitcoins Summary Bitcoin Clients and APIs Bitcoin installation Types of Bitcoin Core clients Bitcoind Bitcoin-cli Bitcoin-qt Setting up a Bitcoin node Setting up the source code Setting up bitcoin.conf Starting up a node in testnet Starting up a node in regtest Experimenting with Bitcoin-cli Bitcoin programming and the command-line interface Summary Alternative Coins Theoretical foundations Alternatives to Proof of Work Proof of Storage Proof of Stake (PoS) Various stake types Proof of coinage Proof of Deposit (PoD) Proof of Burn Proof of Activity (PoA) Nonoutsourceable puzzles Difficulty adjustment and retargeting algorithms Kimoto Gravity Well Dark Gravity Wave DigiShield MIDAS Bitcoin limitations Privacy and anonymity Mixing protocols Third-party mixing protocols Inherent anonymity Extended protocols on top of Bitcoin Colored coins Counterparty Development of altcoins Consensus algorithms Hashing algorithms Difficulty adjustment algorithms Inter-block time Block rewards Reward halving rate Block size and transaction size Interest rate Coinage Total supply of coins Namecoin Trading Namecoins Obtaining Namecoins Generating Namecoin records Litecoin Primecoin Trading Primecoin Mining guide Zcash Trading Zcash Mining guide Address generation GPU mining Downloading and compiling nheqminer Initial Coin Offerings (ICOs) ERC20 tokens Summary Smart Contracts History Definition Ricardian contracts Smart contract templates Oracles Smart Oracles Deploying smart contracts on a blockchain The DAO Summary Ethereum 101 Introduction The yellow paper Useful mathematical symbols Ethereum blockchain Ethereum – bird's eye view The Ethereum network Mainnet Testnet Private net Components of the Ethereum ecosystem Keys and addresses Accounts Types of accounts Transactions and messages Contract creation transaction Message call transaction Messages Calls Transaction validation and execution The transaction substate State storage in the Ethereum blockchain The world state The account state Transaction receipts Ether cryptocurrency / tokens (ETC and ETH) The Ethereum Virtual Machine (EVM) Execution environment Machine state The iterator function Smart contracts Native contracts Summary Further Ethereum Programming languages Runtime bytecode Opcodes and their meaning Arithmetic operations Logical operations Cryptographic operations Environmental information Block information Stack, memory, storage, and flow operations Push operations Duplication operations Exchange operations Logging operations System operations Blocks and blockchain The genesis block The block validation mechanism Block finalization Block difficulty Gas Fee schedule Forks in the blockchain Nodes and miners The consensus mechanism Ethash CPU mining GPU mining Benchmarking Mining rigs Mining pools Wallets and client software Geth Eth Pyethapp Parity Light clients Installation Eth installation Mist browser Geth The geth console Funding the account with bitcoin Parity installation Creating accounts using the parity command line APIs, tools, and DApps Applications (DApps and DAOs) developed on Ethereum Tools Supporting protocols Whisper Swarm Scalability, security, and other challenges Trading and investment Summary Ethereum Development Environment Test networks Setting up a private net Network ID The genesis file Data directory Flags and their meaning Static nodes Starting up the private network Running Mist on private net Deploying contracts using Mist Block explorer for private net / local Ethereum block explorer Summary Development Tools and Frameworks Languages Compilers Solidity compiler (solc) Installation on Linux Installation on macOS Integrated Development Environments (IDEs) Remix Tools and libraries Node version 7 EthereumJS Ganache MetaMask Truffle Installation Contract development and deployment Writing Testing Solidity language Types Value types Boolean Integers Address Literals Integer literals String literals Hexadecimal literals Enums Function types Internal functions External functions Reference types Arrays Structs Data location Mappings Global variables Control structures Events  Inheritance Libraries Functions Layout of a Solidity source code file Version pragma Import Comments Summary Introducing Web3 Web3 Contract deployment POST requests The HTML and JavaScript frontend Installing web3.js Example Creating a web3 object Checking availability by calling any web3 method Contract functions Development frameworks Truffle Initializing Truffle Interaction with the contract Another example An example project – Proof of Idea Oracles Deployment on decentralized storage using IPFS Installing IPFS Distributed ledgers Summary Hyperledger Projects under Hyperledger Fabric Sawtooth Lake Iroha Burrow Indy Explorer Cello Composer Quilt Hyperledger as a protocol The reference architecture Requirements and design goals of Hyperledger Fabric The modular approach Privacy and confidentiality Scalability Deterministic transactions Identity Auditability Interoperability Portability Rich data queries Fabric Hyperledger Fabric Membership services Blockchain services Consensus services Distributed ledger The peer to peer protocol Ledger storage Chaincode services Components of the fabric Peers Orderer nodes Clients Channels World state database Transactions Membership Service Provider (MSP) Smart contracts Crypto service provider Applications on blockchain Chaincode implementation The application model Consensus in Hyperledger Fabric The transaction life cycle in Hyperledger Fabric Sawtooth Lake PoET Transaction families Consensus in Sawtooth The development environment – Sawtooth Lake Corda Architecture State objects Transactions Consensus Flows Components Nodes The permissioning service Network map service Notary service Oracle service Transactions Vaults CorDapp The development environment – Corda Summary Alternative Blockchains Blockchains Kadena Ripple Transactions Payments related Order related Account and security-related Interledger Application layer Transport layer Interledger layer Ledger layer Stellar Rootstock Sidechain Drivechain Quorum Transaction manager Crypto Enclave QuorumChain Network manager Tezos Storj MaidSafe BigchainDB MultiChain Tendermint Tendermint Core Tendermint Socket Protocol (TMSP) Platforms and frameworks Eris Summary Blockchain – Outside of Currencies Internet of Things Physical object layer Device layer Network layer Management layer Application layer IoT blockchain experiment First node setup Raspberry Pi node setup Installing Node.js Circuit Government Border control Voting Citizen identification (ID cards) Miscellaneous Health Finance Insurance Post-trade settlement Financial crime prevention Media Summary Scalability and Other Challenges Scalability Network plane Consensus plane Storage plane View plane Block size increase Block interval reduction Invertible Bloom Lookup Tables Sharding State channels Private blockchain Proof of Stake Sidechains Subchains Tree chains (trees) Block propagation Bitcoin-NG Plasma Privacy Indistinguishability Obfuscation Homomorphic encryption Zero-Knowledge Proofs State channels Secure multiparty computation Usage of hardware to provide confidentiality CoinJoin Confidential transactions MimbleWimble Security Smart contract security Formal verification and analysis Oyente tool Summary Current Landscape and What's Next Emerging trends Application-specific blockchains (ASBCs) Enterprise-grade blockchains Private blockchains Start-ups Strong research interest Standardization Enhancements Real-world implementations Consortia Answers to technical challenges Convergence Education of blockchain technology Employment Cryptoeconomics Research in cryptography New programming languages Hardware research and development Research in formal methods and security Alternatives to blockchains Interoperability efforts Blockchain as a Service Efforts to reduce electricity consumption Other challenges Regulation Dark side Blockchain research Smart contracts Centralization issues Limitations in cryptographic functions Consensus algorithms Scalability Code obfuscation Notable projects Zcash on Ethereum CollCo Cello Qtum Bitcoin-NG Solidus Hawk Town-Crier SETLCoin TEEChan Falcon Bletchley Casper Miscellaneous tools Solidity extension for Microsoft Visual Studio MetaMask Stratis Embark DAPPLE Meteor uPort INFURA Convergence with other industries Future Summary Another Book You May Enjoy Leave a review – let other readers know what you think Preface This book has one goal, to introduce theoretical and practical aspects of the blockchain technology.


pages: 416 words: 106,532

Cryptoassets: The Innovative Investor's Guide to Bitcoin and Beyond: The Innovative Investor's Guide to Bitcoin and Beyond by Chris Burniske, Jack Tatar

Airbnb, altcoin, asset allocation, asset-backed security, autonomous vehicles, bitcoin, blockchain, Blythe Masters, business cycle, business process, buy and hold, capital controls, Carmen Reinhart, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, commoditize, correlation coefficient, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, disintermediation, distributed ledger, diversification, diversified portfolio, Donald Trump, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, fiat currency, financial innovation, fixed income, George Gilder, Google Hangouts, high net worth, Jeff Bezos, Kenneth Rogoff, Kickstarter, Leonard Kleinrock, litecoin, Marc Andreessen, Mark Zuckerberg, market bubble, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, Network effects, packet switching, passive investing, peer-to-peer, peer-to-peer lending, Peter Thiel, pets.com, Ponzi scheme, prediction markets, quantitative easing, RAND corporation, random walk, Renaissance Technologies, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ross Ulbricht, Satoshi Nakamoto, Sharpe ratio, Silicon Valley, Simon Singh, Skype, smart contracts, social web, South Sea Bubble, Steve Jobs, transaction costs, tulip mania, Turing complete, Uber for X, Vanguard fund, WikiLeaks, Y2K

Dmitry Buterin is also very much involved in the cryptoasset world as cofounder of Blockgeeks and other influential startups. 3. http://fortune.com/ethereum-blockchain-vitalik-buterin/. 4. http://www.ioi2012.org/competition/results-2/. 5. https://backchannel.com/the-uncanny-mind-that-built-ethereum-9b448dc9d14f#.4yr8yhfp8. 6. https://blog.ethereum.org/2014/01/23/ethereum-now-going-public/. 7. http://counterparty.io/platform/. 8. https://steemit.com/ethereum/@najoh/beyond-bitcoin-and-crypto-currency-ethereum. 9. https://blog.ethereum.org/2014/01/23/ethereum-now-going-public/. 10. https://github.com/ethereum/wiki/wiki/white-paper. 11. Turing complete refers to a system that is effectively capable of the full functionality of a general purpose computer. Bitcoin was intentionally constructed not to be Turing complete to constrain complexity and prioritize security. 12. https://ethereum.org/ether. 13. Nathaniel Popper, Digital Gold: Bitcoin and the Inside Story of the Misfits and Millionaires Trying to Reinvent Monday, Harper, 2015. 14. http://www.coindesk.com/peter-thiel-fellowship-ethereum-vitalik-buterin/. 15. http://www.wtn.net/summit-2014/2014-world-technology-awards-winners. 16. http://ether.fund/market. 17. https://www.ethereum.org/foundation. 18. https://blog.ethereum.org/2015/03/14/ethereum-the-first-year/. 19. http://ethdocs.org/en/latest/introduction/history-of-ethereum.html. 20. http://ether.fund/market. 21. http://ethdocs.org/en/latest/introduction/history-of-ethereum.html. 22.

While many initially claimed the hard fork a success for Ethereum, a few big traders started to buy up as much of the native asset on the lesser supported chain as possible. Figure 5.2 The forking of Ethereum as a result of The DAO’s bug On July 23, 2016, cryptoasset exchange Poloniex listed this newly branded network, called Ethereum Classic, with its own native ether classic (ETC).31 Once a widely used exchange like Poloniex listed ETC, an open market was created for the asset, and people quickly started to speculate on its value. This drew more miners to support Ethereum Classic’s blockchain, which continues to exist to this day and as of writing tends to stick near 5 percent the network value of Ethereum.32 The site for Ethereum Classic defines the cryptoasset as “a continuation of the original Ethereum blockchain—the classic version preserving untampered history; free from external interference and subjective tampering of transactions.{{#}}8221;33 While The DAO may have been a disaster, the concept of a decentralized autonomous organization is generalizable past this single instance.

As we covered in Chapter 5, Ethereum, which we defined as a cryptocommodity, is a common platform for dApps and their associated cryptotokens. Whether this relation is for better or worse depends on the situation. In the DAOsaster, The DAO had a significantly negative impact on Ethereum. On the other hand, the successful creation and implementation of cryptotokens like Augur or SingularDTV, which are also built on Ethereum, can have a positive impact on all assets involved. As Ethereum grows as a platform for other cryptoassets, it will be important to keep an eye on the quality of the dApps that are built on it, and how the Ethereum team handles its relationship with these dApps. If Ethereum gets big enough, there may eventually be those who call themselves Ethereum Maximalists! ISSUANCE MODEL The current and ongoing rate of supply increase is extremely important to consider.


pages: 135 words: 26,407

How to DeFi by Coingecko, Darren Lau, Sze Jin Teh, Kristian Kho, Erina Azmi, Tm Lee, Bobby Ong

algorithmic trading, asset allocation, Bernie Madoff, bitcoin, blockchain, buy and hold, capital controls, collapse of Lehman Brothers, cryptocurrency, distributed ledger, diversification, Ethereum, ethereum blockchain, fiat currency, Firefox, information retrieval, litecoin, margin call, new economy, passive income, payday loans, peer-to-peer, prediction markets, QR code, reserve currency, smart contracts, tulip mania, two-sided market

Like Argent, Metamask is a non-custodial wallet and it acts as both a wallet and an interaction bridge for the Ethereum network. You can store your Ethereum and ERC20 tokens on Metamask. Acting as an interaction bridge, Metamask enables you to use all Decentralized Applications (Dapps) that are hosted on the Ethereum Network. Without the use of an interaction bridge like MetaMask, your browser would not be able to access the Ethereum blockchain unless you were running a full Ethereum node and have the entire Ethereum blockchain of over 400GB downloaded on your computer. On a technical level, MetaMask does this by injecting a javascript library known as web3.js written by the core Ethereum developers into your browser’s page to enable you to easily interact with the Ethereum network. Metamask makes interaction with DeFi Dapps on the Ethereum network very convenient on your laptop or PC.

It is a useful tool to visualize and track where your assets are across the different DeFi protocols. E Ethereum Ethereum is an open-source, programmable, decentralized platform built on blockchain technology. Compared to Bitcoin, Ethereum allows for scripting languages which has allowed for application development. Ether Ether is the cryptocurrency that powers the Ethereum blockchain. It is the fuel for the apps on the decentralized Ethereum network ERC-20 ERC is an abbreviation for Ethereum Request for Comment and 20 is the proposal identifier. It is an official protocol for proposing improvements to the Ethereum network. ERC-20 refers to the commonly adopted standard used to create tokens on Ethereum. Exposure Exposure refers to how much you are 'exposed' to the potential risk of losing your investment.

(Aaron Hay) https://medium.com/coinmonks/how-decentralized-is-decentralized-finance-89aea3070e8f Mapping Decentralized Finance https://outlierventures.io/wp-content/uploads/2019/06/Mapping-Decentralised-Finance-DeFi-report.pdf Market Report: 2019 DeFi Year in Review https://defirate.com/market-report-2019/ DeFi #3 – 2020: The Borderless State of DeFi https://research.binance.com/analysis/2020-borderless-state-of-defi Decentralized Finance with Tom Schmidt (Software Engineering Daily) https://softwareengineeringdaily.com/2020/02/25/decentralized-finance-with-tom-schmidt/ Part Two: Getting Into DeFi Chapter Three: The Decentralized Layer: Ethereum What is Ethereum? As mentioned in Chapter 1, the majority of the DeFi Dapps are currently being built on the Ethereum blockchain. But what exactly is Ethereum? Ethereum is a global, open-source platform for decentralized applications. You can think of it as a world computer that cannot be shut down. On Ethereum, software developers can write smart contracts that control digital value through a set of criteria and are accessible anywhere in the world. In this book specifically, we will be exploring Decentralized Applications (Dapps) that provide financial services known as DeFi. Smart contracts that are written by software programmers are the building blocks of these Dapps. These smart contracts are then deployed to the Ethereum network, where it will run 24/7.


pages: 218 words: 68,648

Confessions of a Crypto Millionaire: My Unlikely Escape From Corporate America by Dan Conway

Affordable Care Act / Obamacare, Airbnb, bank run, basic income, bitcoin, blockchain, buy and hold, cloud computing, cognitive dissonance, corporate governance, crowdsourcing, cryptocurrency, disruptive innovation, distributed ledger, double entry bookkeeping, Ethereum, ethereum blockchain, fault tolerance, financial independence, gig economy, Gordon Gekko, Haight Ashbury, high net worth, job satisfaction, litecoin, Marc Andreessen, Mitch Kapor, obamacare, offshore financial centre, Ponzi scheme, prediction markets, rent control, reserve currency, Ronald Coase, Satoshi Nakamoto, Silicon Valley, smart contracts, Steve Jobs, supercomputer in your pocket, Turing complete, Uber for X, universal basic income, upwardly mobile

. *** The great thing about the modern world is that you can quickly become an expert on anything. While walking the dog, I listened to podcasts about Ethereum. When stealing any free time at work, I read about Ethereum. I rejiggered my Twitter feed to follow mostly Ethereum-related contacts. At my usual Friday night Twelve Step meeting, I pulled aside a shaken-looking newcomer. He also happened to be a software engineer. I didn’t ask him about his recovery. I asked him whether he’d heard of Ethereum. At night I played Ethereum-focused YouTube videos on the big screen. My favorites were from DevCon 1, which took place in London in November 2015—the first congregation of the embryonic Ethereum community. The event had a Woodstock feel. By then I knew all about Ethereum’s creator, but these videos were the first time I laid eyes on Vitalik Buterin. This was the person who prompted me to write three Medium blogs, two of which I deleted because they were too fawning, and I’m a grown man.

What I thought would happen with Ethereum might just be happening. Ironically, the catalyst for this price rise was a sudden interest in Ethereum from corporations, governments, and other centralized institutions. Back in New York, they’d announced a new organization, spearheaded by Ethereum veterans, called the Enterprise Ethereum Alliance. There were thirty-five initial members, including some of the largest corporations in the world: Microsoft, J.P. Morgan, and British Petroleum. Over a day-long webcast conference at the J.P. Morgan office, they expressed their belief in Ethereum and sketched out working groups to aid development and interoperability with private chains. This is the thing Andrew Keys had hinted at in San Jose. The markets were responding. Blockchain might actually work, and Ethereum might actually be the winning platform.

For an ETH freak like me, ConsenSys was the hippest, edgiest, most profoundly cool company in the world. They called themselves an Ethereum Production Studio, and they ran the company as a holacracy, meaning it was structured as a flat organization, unlike a traditional corporation. Its founder, Joseph Lubin, was an early disciple of Ethereum and a mentor to Vitalik on the business side. He was a co-founder who helped Vitalik get the word out and attract developers to Ethereum after it launched in 2015. As a professional prophet, Keys traveled the world, extolling the virtues of Ethereum. Now I was with him as he talked to this group of squares in suits and ties. He was sweating and effusive, sharing the gospel, telling them how Ethereum would change everything, doling out proof points like a street-corner preacher: warehouses full of developers in the Philippines, a major recording artist interested in the Ethereum-based music dApp Ujo, big corporations quietly turning to Ethereum in an effort to become more flat.


pages: 348 words: 97,277

The Truth Machine: The Blockchain and the Future of Everything by Paul Vigna, Michael J. Casey

3D printing, additive manufacturing, Airbnb, altcoin, Amazon Web Services, barriers to entry, basic income, Berlin Wall, Bernie Madoff, bitcoin, blockchain, blood diamonds, Blythe Masters, business process, buy and hold, carbon footprint, cashless society, cloud computing, computer age, computerized trading, conceptual framework, Credit Default Swap, crowdsourcing, cryptocurrency, cyber-physical system, dematerialisation, disintermediation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, failed state, fault tolerance, fiat currency, financial innovation, financial intermediation, global supply chain, Hernando de Soto, hive mind, informal economy, intangible asset, Internet of things, Joi Ito, Kickstarter, linked data, litecoin, longitudinal study, Lyft, M-Pesa, Marc Andreessen, market clearing, mobile money, money: store of value / unit of account / medium of exchange, Network effects, off grid, pets.com, prediction markets, pre–internet, price mechanism, profit maximization, profit motive, ransomware, rent-seeking, RFID, ride hailing / ride sharing, Ross Ulbricht, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, smart contracts, smart meter, Snapchat, social web, software is eating the world, supply-chain management, Ted Nelson, the market place, too big to fail, trade route, transaction costs, Travis Kalanick, Turing complete, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, universal basic income, web of trust, zero-sum game

Barry Silbert came up with the SegWit2x compromise: “Bitcoin Scaling Agreement at Consensus 2017,” Digital Currency Group, Medium, May 23, 2017, https://medium.com/@DCGco/bitcoin-scaling-agreement-at-consensus-2017-133521fe9a77. When Buterin released his white paper in December 2013: Vitalik Buterin, “Ethereum White Paper: A Next Generation Smart Contract & Decentralized Application Platform,” http://www.the-blockchain.com/docs/Ethereum_white_paper-a_next_generation_smart_contract_and_decentralized_application_platform-vitalik-buterin.pdf. “You’re just as likely to find a web developer…”: “An Ode to the Ethereum Community,” Steemit, October 2016, https://steemit.com/ethereum/@owaisted/an-ode-to-the-ethereum-community. After launching Ethereum at the North American Bitcoin Conference: Interview with Michael J. Casey, Miami, January 26, 2014. For example: the Parity Wallet: Wolfie Zhao, “$30 Million: Ether Reported Stolen Due to Parity Wallet Breach,” CoinDesk, July 19, 2017, https://www.coindesk.com/30-million-ether-reported-stolen-parity-wallet-breach/ In what was then one of the biggest crowd sales of its kind: “The History of Ethereum,” http://www.ethdocs.org/en/latest/introduction/history-of-ethereum.html#the-ethereum-foundation-and-the-ether-presale.

As long as that’s agreed, this roiling process is viewed as an exercise in group improvement, in making Ethereum stronger, more dynamic, and adaptable. At least that’s the theory. In practice, when there’s a lot of money at stake, people get quite defensive about their rights to that money, which in turn means that successful open-source projects like Ethereum can, like Bitcoin, become quite politicized. That has left Buterin and the other early Ethereum founders—people like Lubin, Wood, and chief communications officer Stephan Tual—open to criticism that they are putting their personal interests first. Such divisions are to be expected, of course; what’s interesting is how differently the Ethereum community has dealt with them compared to the Bitcoin community. From the beginning, Ethereum was a project led by an identifiable group of people with a deliberate strategy to develop and profitably market a product.

And, much like the Segwit2x and other Bitcoin reform proposals, it wouldn’t have come into effect if a majority of the Ethereum miners didn’t accept it. For all intents and purposes, the fix was democratic—arguably, much more so than non-participatory democratic models through which crisis policymaking is enacted by national governments. And since Ethereum is more of a community of software engineers than of cryptocurrency investors, it was less contentious than Bitcoin’s struggle over hard-fork proposals. What’s more, it turned out that disgruntled Ethereum participants weren’t entirely powerless, either. A group decided to continue mining and trading the older, non-forked version of ether, with The DAO attacker’s coins still there in the transaction history. They called it Ethereum Classic, adopted the code ETC for its currency, and traded it alongside the forked Ethereum’s ETH ether. You now had two versions of Ethereum.


pages: 309 words: 54,839

Attack of the 50 Foot Blockchain: Bitcoin, Blockchain, Ethereum & Smart Contracts by David Gerard

altcoin, Amazon Web Services, augmented reality, Bernie Madoff, bitcoin, blockchain, Blythe Masters, Bretton Woods, clean water, cloud computing, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, distributed ledger, Ethereum, ethereum blockchain, Extropian, fiat currency, financial innovation, Firefox, Flash crash, Fractional reserve banking, index fund, Internet Archive, Internet of things, Kickstarter, litecoin, M-Pesa, margin call, Network effects, peer-to-peer, Peter Thiel, pets.com, Ponzi scheme, Potemkin village, prediction markets, quantitative easing, RAND corporation, ransomware, Ray Kurzweil, Ross Ulbricht, Ruby on Rails, Satoshi Nakamoto, short selling, Silicon Valley, Silicon Valley ideology, Singularitarianism, slashdot, smart contracts, South Sea Bubble, tulip mania, Turing complete, Turing machine, WikiLeaks

” [348] Peter Vessenes. “Ethereum Contracts Are Going To Be Candy For Hackers”. Blockchain, Bitcoin and Business (blog), 18 May 2016. [349] Martin Holst Swende. “Ethereum contract security: An Ethereum Roulette”. 14 August 2015. [350] Ethererik. “GovernMental’s 1100 ETH jackpot payout is stuck because it uses too much gas”. Reddit /r/ethereum, 26 April 2016. [351] “Post-Mortem Investigation (Feb 2016)”. King of the Ether. (archive) [352] “Hi! My name is Rubixi. I’m a new Ethereum Doubler. Now my new home – Rubixi.tk”. Bitcointalk.org Bitcoin Forum > Alternate cryptocurrencies > Marketplace (Altcoins) > Service Announcements (Altcoins), 11 April 2016. (archive) [353] Vitalik Buterin. “Live example of ‘underhanded solidity’ coding on mainnet”. Reddit /r/ethereum, 10 April 2016. [354] brockchainbrockshize.

The existence of a single canonical blockchain is frequently questionable, but somehow it all muddles forth. Ethereum has a current maximum of about 14 transactions per second300 (Bitcoin’s is 7 TPS). As at mid-2017 it’s running about 2-3 TPS, having rapidly risen over 2017;301 popular dapps already fill the blocks and clog the system for hours at a time, such as the Bancor and Status ICOs. The Ethereum community seems to have faith in the Ethereum Foundation, so a fix is more likely to be accepted without a Bitcoin-style community civil war; and backward-compatibility-breaking changes in Ethereum are a regular occurrence and are mostly managed without controversy. The developers have always stated that Ethereum is explicitly experimental and unfinished (and never mind the hundreds of millions of dollars in ether swilling around in it), and that the promised fancy functionality will need years of work.302 They occasionally boggle at people treating it as much more of a finished product than they do.303 Ethereum advocates talk up corporate adoption by Microsoft and other companies – it’s a popular choice of platform for business blockchain trials, and its smart contract functionality is reused by a lot of other blockchain software – but this is adoption of the software to run separate in-house blockchains, not adoption of the public Ethereum chain and currency.

In computer science terms, this approach could only have worked by first solving the halting problem: you would need to be able to determine the outcome of any possible Ethereum program without actually running it and observing the result.361) The DAO was shut down soon after, and on 20 July the Ethereum Foundation – several of whose principals were curators of The DAO362 and/or heavily invested in it – changed how the actual code of Ethereum interpreted their blockchain (the “immutable” ledger) so as to wind back the hack and take back their money. The blockchain was “immutable,” so they changed how it was interpreted. The “impossible” bailout had happened. This illustrated the final major problem with smart contracts: CODE IS LAW until the whales are in danger of losing money. Ethereum promptly split into two separate blockchains, each with its own currency – Ethereum (ETH), the wound-back version, supported by the Ethereum Foundation, and Ethereum Classic (ETC), the original code and blockchain – because all this was too greedy even for crypto fans to put up with. Both blockchains and currencies operate today. Well done, all.


pages: 271 words: 52,814

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, disintermediation, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, intangible asset, Internet Archive, Internet of things, Khan Academy, Kickstarter, lifelogging, litecoin, Lyft, M-Pesa, microbiome, Network effects, new economy, peer-to-peer, peer-to-peer lending, peer-to-peer model, personalized medicine, post scarcity, 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, software as a service, technological singularity, Turing complete, uber lyft, unbanked and underbanked, underbanked, web application, WikiLeaks

One blockchain infrastructure project aiming to deliver a Turing-complete scripting language and Turing-complete platform is Ethereum. Ethereum is a platform and a programming language for building and publishing distributed applications. More fundamentally, Ethereum is a foundational general-purpose cryptocurrency platform that is a Turing-complete virtual machine (meaning that it can run any coin, script, or cryptocurrency project). Rather than being a blockchain, or a protocol running over a blockchain, or a metaprotocol running over a protocol like other projects, Ethereum is a fundamental underlying infrastructure platform that can run all blockchains and protocols, rather like a unified universal development platform. Each full node in the Ethereum network runs the Ethereum Virtual Machine for seamless distributed program (smart contract) execution. Ethereum is the underlying blockchain-agnostic, protocol-agnostic platform for application development to write smart contracts that can call multiple other blockchains, protocols, and cryptocurrencies.

(no publishing or posting data available) http://static.benet.ai/t/ipfs.pdf. 61 Atkin, A. “TrustDavis on Ethereum.” Slideshare, June 19, 2014. http://www.slideshare.net/aatkin1971/trustdavis-on-ethereum. 62 Galt, J. “Crypto Swartz Will Get You Paid for Your Great Content.” The CoinFront, June 23, 2014. http://thecoinfront.com/crypto-swartz-will-get-you-paid-for-your-great-content/. 63 Prisco, G. “Counterparty Recreates Ethereum on Bitcoin.” CryptoCoins News, updated November 12, 2014. https://www.cryptocoinsnews.com/counterparty-recreates-ethereum-bitcoin/. See also: “Counterparty Recreates Ethereum’s Smart Contract Platform on Bitcoin.” Counterparty Press Release. http://counterparty.io/news/counterparty-recreates-ethereums-smart-contract-platform-on-bitcoin/. 64 Swan, M. “Counterparty/Ethereum: Why Bitcoin Topped $450 Today (Was Under $350 Last Week).”

Ethereum is the underlying blockchain-agnostic, protocol-agnostic platform for application development to write smart contracts that can call multiple other blockchains, protocols, and cryptocurrencies. Ethereum has its own distributed ecosystem, which is envisioned to include file serving, messaging, and reputation vouching. The first component is Swarm (“Ethereum-Swarm,” not to be confused with the crowdfunding site Swarm) as a decentralized file-serving method. A second component is Whisper (“Ethereum-Whisper,” also not to be confused with other similarly named projects), which is a peer-to-peer protocol for secret messaging and digital cryptography. A third component is a reputation system, a way to establish reputation and reduce risk between agents in trustless networks, possibly provided by TrustDavis,61 or ideas developed in a hackathon project, Crypto Schwartz.62 Counterparty Re-creates Ethereum’s Smart Contract Platform In November 2014, Counterparty announced that it had ported the open source Ethereum programming language onto its own platform.63 The implication was that Counterparty re-created Ethereum on the existing blockchain standard, Bitcoin, so that these kinds of smart contracts might be available now, without waiting for the launch (and mining operation) of Ethereum’s own blockchain, expected in the first quarter of 2015 as of November 2014.


pages: 161 words: 44,488

The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology by William Mougayar

Airbnb, airport security, Albert Einstein, altcoin, Amazon Web Services, bitcoin, Black Swan, blockchain, business process, centralized clearinghouse, Clayton Christensen, cloud computing, cryptocurrency, disintermediation, distributed ledger, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, fixed income, global value chain, Innovator's Dilemma, Internet of things, Kevin Kelly, Kickstarter, market clearing, Network effects, new economy, peer-to-peer, peer-to-peer lending, prediction markets, pull request, QR code, ride hailing / ride sharing, Satoshi Nakamoto, sharing economy, smart contracts, social web, software as a service, too big to fail, Turing complete, web application

He looked at it for three seconds, got agitated, opened Inkscape on his Windows PC, and frenetically started drawing the first version of a blockchain-based architectural framework with Ethereum in it. That architecture drawing was later iterated upon, and appeared in one of Vitalik's blog posts, titled “On Silos.”2 Over the next several months, and up to this day, we became reverse mentors. He taught me a lot about blockchains, and I advised him on business matters and growing Ethereum. I may never comprehend a fraction of Vitalik's blockchain dreams on a given night, but one thing I am certain about, is that Vitalik Buterin is emerging as a savvy business person, following the ranks of other bright technologists, while continuing to lead the Ethereum core technology and its Foundation. I proceeded to write 50 blog posts on Bitcoin, blockchains, and Ethereum, and immersed myself with global creators, innovators, pioneers, leaders, entrepreneurs, startups, enterprise executives and practitioners who were at the leading edges of blockchain technology and its implementation.

If you enjoyed it, I invite you to explore further how to rethink trust, wealth, and information in my next book, Centerless. The new era of decentralization will soon be upon us. Blockchains do not impose restrictions on us. To the opposite, they grant us new levels of freedom, and let us program our world on top of them, any way we would like. Blockchains will be the best new tool of the decade. SELECTED BIBLIOGRAPHY Buterin, Vitalik. “Ethereum and Oracles.” Ethereum Blog. 2014. https://blog.ethereum.org/2014/07/22/ethereum-and-oracles/. Chaum, David, Debajyoti Das, Aniket Kate, Farid Javani, Alan T. Sherman, Anna Krasnova, and Joeri de Ruiter. “cMix: Anonymization by High-Performance Scalable Mixing.” Cryptology ePrint Archive. 2016. http://eprint.iacr.org/2016/008.pdf. Chaum, David. “Anniversary Keynote Address Speech, Financial Cryptography and Data Security 2016.” Twentieth International Conference.

But here's what will make the blockchain's future even more interesting: you are part of it. I hope that readers will find The Business Blockchain as useful as I found it exhilarating to write. William Mougayar Toronto, Ontario wmougayar@gmail.com MARCH 2016 NOTES 1.“A Next-Generation Smart Contract and Decentralized Application Platform,” https://github.com/ethereum/wiki/wiki/White-Paper#ethereum. 2.“On Silos,” https://blog.ethereum.org/2014/12/31/silos/. INTRODUCTION IF THE BLOCKCHAIN has not shocked you yet, I guarantee it will shake you soon. I have not seen anything like this since the start of the Internet, in terms of capturing the imagination of people, a small number first, but then spreading rapidly. Welcome to the new world of the blockchain and blockchains. At its core, the blockchain is a technology that permanently records transactions in a way that cannot be later erased but can only be sequentially updated, in essence keeping a never-ending historical trail.


pages: 515 words: 126,820

Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World by Don Tapscott, Alex Tapscott

Airbnb, altcoin, asset-backed security, autonomous vehicles, barriers to entry, bitcoin, blockchain, Blythe Masters, Bretton Woods, business process, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, cloud computing, cognitive dissonance, commoditize, corporate governance, corporate social responsibility, creative destruction, Credit Default Swap, crowdsourcing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, failed state, fiat currency, financial innovation, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, future of work, Galaxy Zoo, George Gilder, glass ceiling, Google bus, Hernando de Soto, income inequality, informal economy, information asymmetry, intangible asset, interest rate swap, Internet of things, Jeff Bezos, jimmy wales, Kickstarter, knowledge worker, Kodak vs Instagram, Lean Startup, litecoin, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, microcredit, mobile money, money market fund, Network effects, new economy, Oculus Rift, off grid, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, performance metric, Peter Thiel, planetary scale, Ponzi scheme, prediction markets, price mechanism, Productivity paradox, QR code, quantitative easing, ransomware, Ray Kurzweil, renewable energy credits, rent-seeking, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, seigniorage, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, smart grid, social graph, social intelligence, social software, standardized shipping container, Stephen Hawking, Steve Jobs, Steve Wozniak, Stewart Brand, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, The Wisdom of Crowds, transaction costs, Turing complete, Turing test, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, unorthodox policies, wealth creators, X Prize, Y2K, Zipcar

CHAPTER 4 RE-ARCHITECTING THE FIRM: THE CORE AND THE EDGES BUILDING CONSENSYS July 30, 2015, was a big day for a global group of coders, investors, entrepreneurs, and corporate strategists who think that Ethereum is the next big thing—not just for business, but possibly for civilization. Ethereum, the blockchain platform eighteen months in the making, went live. We witnessed the launch firsthand in the Brooklyn office of Consensus Systems (ConsenSys), one of the first Ethereum software development companies. Around 11:45 a.m., there were high fives all around as the Ethereum network created its “genesis block,” after which a frenzy of miners raced to win the first block of ether, Ethereum’s currency. The day was eerily suspenseful. A massive thunderstorm broke over the East River, triggering loud and random emergency flood warnings on everyone’s smart phones. According to its Web site, Ethereum is a platform that runs decentralized applications, namely smart contracts, “exactly as programmed without any possibility of downtime, censorship, fraud, or third party interference.”

Interview with Steve Omohundro, May 28, 2015. 62. The Silver Stallion, chapter 26; www.cadaeic.net/cabell.htm, accessed October 2, 2015. 63. Interview with Yochai Benkler, August 26, 2015. Chapter 11: Leadership for the Next Era 1. Stephan Tual, “Announcing the New Foundation Board and Executive Director,” Ethereum blog, Ethereum Foundation, July 30, 2015; https://blog.ethereum.org/2015/07/30/announcing-new-foundation-board-executive-director/, accessed December 1, 2015. 2. Ethereum: The World Computer, produced by Ethereum, YouTube, July 30, 2015; www.youtube.com/watch?v=j23HnORQXvs, accessed December 1, 2015. 3. Interview with Vitalik Buterin, September 30, 2015. 4. Ibid. 5. Ibid. 6. Ibid. 7. Henry VI, part 2, act 4, scene 2. 8. E-mail correspondence with Vitalik Buterin, October 1, 2015. 9.

According to its Web site, Ethereum is a platform that runs decentralized applications, namely smart contracts, “exactly as programmed without any possibility of downtime, censorship, fraud, or third party interference.” Ethereum is like bitcoin in that its ether motivates a network of peers to validate transactions, secure the network, and achieve consensus about what exists and what has occurred. But unlike bitcoin it contains some powerful tools to help developers and others create software services ranging from decentralized games to stock exchanges. Ethereum was conceived in 2013 by then-nineteen-year-old Vitalik Buterin, a Canadian of Russian descent. He had argued to the bitcoin core developers that the platform needed a more robust scripting language for developing applications. When they rejected him, he decided to craft his own platform. ConsenSys was first off the block, so to speak, launched to create Ethereum-based apps. Flash-forward a couple of years and the analogy is clear: Linus Torvalds is to Linux what Vitalik Buterin is to Ethereum.


pages: 410 words: 119,823

Radical Technologies: The Design of Everyday Life by Adam Greenfield

3D printing, Airbnb, augmented reality, autonomous vehicles, bank run, barriers to entry, basic income, bitcoin, blockchain, business intelligence, business process, call centre, cellular automata, centralized clearinghouse, centre right, Chuck Templeton: OpenTable:, cloud computing, collective bargaining, combinatorial explosion, Computer Numeric Control, computer vision, Conway's Game of Life, cryptocurrency, David Graeber, dematerialisation, digital map, disruptive innovation, distributed ledger, drone strike, Elon Musk, Ethereum, ethereum blockchain, facts on the ground, fiat currency, global supply chain, global village, Google Glasses, IBM and the Holocaust, industrial robot, informal economy, information retrieval, Internet of things, James Watt: steam engine, Jane Jacobs, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Kevin Kelly, Kickstarter, late capitalism, license plate recognition, lifelogging, M-Pesa, Mark Zuckerberg, means of production, megacity, megastructure, minimum viable product, money: store of value / unit of account / medium of exchange, natural language processing, Network effects, New Urbanism, Occupy movement, Oculus Rift, Pareto efficiency, pattern recognition, Pearl River Delta, performance metric, Peter Eisenman, Peter Thiel, planetary scale, Ponzi scheme, post scarcity, post-work, RAND corporation, recommendation engine, RFID, rolodex, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, smart cities, smart contracts, social intelligence, sorting algorithm, special economic zone, speech recognition, stakhanovite, statistical model, stem cell, technoutopianism, Tesla Model S, the built environment, The Death and Life of Great American Cities, The Future of Employment, transaction costs, Uber for X, undersea cable, universal basic income, urban planning, urban sprawl, Whole Earth Review, WikiLeaks, women in the workforce

If Deleuze and Guattari held that the fundamental task of a philosopher is the creation of new concepts, indeed, it’s not entirely ridiculous to think of Buterin’s work in this way.3 However we may evaluate them practically or ethically, the explosion of post-Satoshi development has populated the world with new and challenging objects of thought, and the community around Ethereum has been especially fruitful in this regard. Ethereum does offer its own token of value—a cryptocurrency called Ether4—and people do mine and trade in Ether directly, just as they might Bitcoin. But what the network does with it is quite a bit subtler and more interesting than the mere transfer of value between human beings. Buterin had conceived Ethereum from the outset as a single, massively distributed computing engine sprawled across the global network, in which all processing is paid for in increments of Ether. In this model, computing power aggregated from that of individual machines becomes immanent to the network itself. This architecture allows Ethereum to serve as a platform for networked applications that run on a decentralized, peer-to-peer basis, rather than the more conventional client-server model.

But the provisions at the very heart of the DAO may be difficult to reconcile with the values and commitments of any left politics worthy of the name. Consider Ethereum’s description of a DAO’s origin: “The way this particular democracy works is that it has an Owner which works like an administrator, CEO or a President. The Owner can add (or remove) voting members to the organization.”24 It’s the original Owner of a DAO, then, that sets its binding decision rules, and retains the capacity to change that rule whenever it desires. This is certainly a novel and interesting definition of a democracy. And in fact it’s owners all the way down. Remember too that a DAO requires that members buy shares in it in order to participate. This requirement is imposed by the Ethereum framework itself: a DAO is woven of smart contracts, and like all such contracts running under Ethereum, pays a sum of Ether to the network node that executes it.

abstract_id=2580664. 24.Ethereum Project, “How to Build a Democracy on the Blockchain: Distributed Autonomous Organization,” undated, ethereum.org/dao. 25.Stephan Tual, “On DAO Contractors and Curators,” Slock.it blog, April 10, 2016, blog.slock.it/on-contractors-and-curators-2fb9238b2553#.3jnmvy1jm. 26.Elinor Ostrom, Governing the Commons: The Evolution of Institutions for Collective Action, Cambridge UK: Cambridge University Press, 1990. 27.Michael Cox, Gwen Arnold and Sergio Villamayor Tomás, “A review of design principles for community-based natural resource management,” Ecology and Society, Volume 15, Number 4: 38, 2010; see also Ostrom’s own work The Challenge of Common-Pool Resources. 28.Stavros Stavrides, Common Space, Zed Books, London, 2016. 29.Though, in fairness, Ethereum’s DAO tutorial later points out steps that can be taken to limit an Owner’s power, enacting these measures requires that Owner’s consent. 30.Michael Del Castillo, “The DAO: Or How A Leaderless Ethereum Project Raised $50 Million,” CoinDesk, May 12, 2016. 31.Tom Simonite, “The ‘Autonomous Corporation’ Called The DAO Is Not a Good Way To Spend $130 Million,” MIT Technology Review, May 17, 2016; Jon Evans, “All The Cool Kids Are Doing Ethereum Now,” TechCrunch, May 22, 2016; Emin Gün Sirer, “Caution: The DAO Can Turn Into A Naturally Arising Ponzi,” Hacking, Distributed, June 13, 2016; Kyle Torpey, Tweet, May 11, 2016. twitter.com/kyletorpey/status/730535910949916672 32.Dino Mark, Vlad Zamfir and Emin Gün Sirer.


pages: 296 words: 86,610

The Bitcoin Guidebook: How to Obtain, Invest, and Spend the World's First Decentralized Cryptocurrency by Ian Demartino

3D printing, AltaVista, altcoin, bitcoin, blockchain, buy low sell high, capital controls, cloud computing, corporate governance, crowdsourcing, cryptocurrency, distributed ledger, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, fiat currency, Firefox, forensic accounting, global village, GnuPG, Google Earth, Haight Ashbury, Jacob Appelbaum, Kevin Kelly, Kickstarter, litecoin, M-Pesa, Marc Andreessen, Marshall McLuhan, Oculus Rift, peer-to-peer, peer-to-peer lending, Ponzi scheme, prediction markets, QR code, ransomware, Ross Ulbricht, Satoshi Nakamoto, self-driving car, Skype, smart contracts, Steven Levy, the medium is the message, underbanked, WikiLeaks, Zimmermann PGP

(How this works and how it keeps people honest is beyond the scope of this chapter.) There is a Bitcoin-like coin in Ethereum, called Ether, that makes the system run, secures the network and settles contracts. What has really made headlines, however, is that major technology companies, banks and financial institutions around the world have announced they are working on projects using Ethereum. Details are thin at this point, but UBS and Barclays have both announced an interest in Ethereum, and Microsoft is offering Ethereum in some capacity on its cloud computing service, making it easy for developers to create Ethereum apps. This support from the outside world is unheard of for cryptocurrencies not named Bitcoin and that, more than anything, is the biggest sign that Ethereum will have some success going forward. It has a long way to go before it becomes the next Bitcoin, which is still light-years ahead in support from both inside and outside the community.

It has a long road ahead of it, because as it turns out, even useless scam coins die hard. Ethereum Algorithm: Ethash Mining Type: Proof-of-Work with plans to switch to new proof-of-stake method Block Time: Around 20 seconds Block Reward: 5 Ether per block Maximum Blocksize: 1MB Total Number: No limit I conclude with perhaps the most exciting cryptocurrency since Bitcoin. Ethereum is more than a coin, describing itself thus: “Ethereum is a decentralized platform that runs smart contracts: applications that run exactly as programmed without any possibility of downtime, censorship, fraud or third party interference. Ethereum is how the Internet was supposed to work.” As with Nxt and CounterParty, it allows for asset/token creation. But more than that, Ethereum has its own programming language built in, which has resulted in some very exciting projects.

It has a long way to go before it becomes the next Bitcoin, which is still light-years ahead in support from both inside and outside the community. Ethereum has proven itself head and shoulders above the rest of the altcoin world. Its product took far longer than expected to be released, and that caused many to write it off. But when it was, the mainstream world seemed to take notice. Other coins have powerful features, but only Ethereum has its own programming language. This doesn’t mean a lot to people without programming experience, but it apparently means a lot to the large entities that have expressed interest in it. A cryptocurrency’s feature’s usefulness is tied directly to the quality and quantity of the people using it. If no one is using an asset exchange or if only scammers are using it, it is not very useful. The support for Ethereum from the outside world is, to me, a sign that the altcoin world is finally solidifying.


pages: 326 words: 91,559

Everything for Everyone: The Radical Tradition That Is Shaping the Next Economy by Nathan Schneider

1960s counterculture, Affordable Care Act / Obamacare, Airbnb, altcoin, Amazon Mechanical Turk, back-to-the-land, basic income, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Brewster Kahle, Burning Man, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Clayton Christensen, collaborative economy, collective bargaining, Community Supported Agriculture, corporate governance, creative destruction, crowdsourcing, cryptocurrency, Debian, disruptive innovation, do-ocracy, Donald Knuth, Donald Trump, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, Food sovereignty, four colour theorem, future of work, gig economy, Google bus, hydraulic fracturing, Internet Archive, Jeff Bezos, jimmy wales, joint-stock company, Joseph Schumpeter, Julian Assange, Kickstarter, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, mass immigration, means of production, multi-sided market, new economy, offshore financial centre, old-boy network, Peter H. Diamandis: Planetary Resources, post-work, precariat, premature optimization, pre–internet, profit motive, race to the bottom, Richard Florida, Richard Stallman, ride hailing / ride sharing, Sam Altman, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, Silicon Valley, Slavoj Žižek, smart contracts, Steve Jobs, Steve Wozniak, Stewart Brand, transaction costs, Turing test, Uber and Lyft, uber lyft, underbanked, undersea cable, universal basic income, Upton Sinclair, Vanguard fund, white flight, Whole Earth Catalog, WikiLeaks, women in the workforce, working poor, Y Combinator, Y2K, Zipcar

Buterin’s original white paper can be found at github.com/ethereum/wiki/wiki/White-Paper. 8. Perhaps the first scholarly presentation to take Ethereum seriously was Primavera De Filippi, “Ethereum: Freenet or Skynet?” luncheon at Berkman Klein Center for Internet and Society at Harvard University (April 15, 2014), cyber.harvard.edu/events/luncheon/2014/04/difilippi; see also the widely circulated video “Vitalik Buterin Reveals Ethereum at Bitcoin Miami 2014,” youtube.com/watch?v=l9dpjN3Mwps; a compelling early analysis of Buterin’s worldview is Sam Frank, “Come With Us If You Want to Live,” Harper’s Magazine (January 2015); for a technical perspective, see Ethereum Foundation, “How to Build a Democracy on the Blockchain,” ethereum.org/dao. 9. Vitalik Buterin, comment on Reddit thread (April 6, 2014), reddit.com/r/ethereum/comments/22av9m/code_your_own_utopia. 10.

Just a few weeks earlier, a nineteen-year-old Russian Canadian named Vitalik Buterin had published a proposal for what he called Ethereum.7 What Bitcoin was for money, Ethereum would be for everything else. It turns out that the basic idea of an ironclad list with no single caretaker—the blockchain—has an enormous range of potential applications. Rather than listing transactions, for instance, it can list contracts and enforce them computationally, resulting in an autonomous legal system without courts or cops. A blockchain of websites could be the basis of a more secure kind of internet. “It’s an operating system for society,” D’Onofrio said. Before long, coders were sketching out prototypes for what they called decentralized autonomous organizations, or DAOs—entities made up of Ethereum “smart contracts.” One might code a constitution for a nongeographic country that people can choose to join, pay taxes to, receive benefits from, and cast votes in—and whose rules they would then have to obey.

He later interrupted the discussions on technical feasibility and implementation with stories of real-life good deeds done through his lodge, offline. Ethereum went live in 2015. Its underlying currency, ether, soon became second only to bitcoin on the crypto-markets, with a total value in the billions of dollars. Walmart is using Ethereum to manage supply chains, and J. P. Morgan is writing smart contracts to automate transactions. A coalition of US credit unions is building a “CU Ledger” to manage member identities. Some people are trying to craft the perfect co-ops or other sorts of egalitarian DAOs, but they’re not making money like the ones concocting blockchain ledgers for big, old banks.10 A year into Ethereum’s life, the system hit trouble. A glitch in the code enabled a hacker to siphon millions of dollars’ worth of ether from a flagship DAO known simply as “the DAO.”


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Bitcoin: The Future of Money? by Dominic Frisby

3D printing, altcoin, bank run, banking crisis, banks create money, barriers to entry, bitcoin, blockchain, capital controls, Chelsea Manning, cloud computing, computer age, cryptocurrency, disintermediation, Ethereum, ethereum blockchain, fiat currency, fixed income, friendly fire, game design, Isaac Newton, Julian Assange, land value tax, litecoin, M-Pesa, mobile money, money: store of value / unit of account / medium of exchange, Occupy movement, Peter Thiel, Ponzi scheme, prediction markets, price stability, QR code, quantitative easing, railway mania, Ronald Reagan, Ross Ulbricht, Satoshi Nakamoto, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, Stephen Hawking, Steve Jobs, Ted Nelson, too big to fail, transaction costs, Turing complete, War on Poverty, web application, WikiLeaks

‘That is what we’re hoping to do.’ How Bitcoin is just the start of something much, much bigger Ethereum is probably the most talked-about development in cryptography at present. Some call it Bitcoin 2.0. It combines the decentralized mining system central to Bitcoin with a software development platform. Its founders say the potential applications are unlimited: from peer-to-peer betting, to financial derivatives, to identity and reputation systems, to insurance and legal contracts. Some say Satoshi Nakamoto may now even be working for Ethereum. Its former CEO is Charles Hoskinson. A bespectacled, bearded, extremely bright, friendly and fast-talking mathematician. I met him over Skype. I wanted to talk to him about Ethereum. But there was something else. I’d been tipped off that he was holding copies of all the private emails Satoshi had sent when Bitcoin was being developed.

‘And so that’s our hope, that’s what we want to do. And the app catalogue is totally decentralized just like the network. So even we don’t control it – so we can’t take apps down or anything and the government can’t take apps down or something like that. So, that’s what we’re trying to do: mainstream this dis-intermediation technology’. The implications of Ethereum – if it takes off – are clearly enormous. For more information about Ethereum, visit ethereum.org. 10 Should You Buy In? You can’t stop things like Bitcoin. It’s like trying to stop gunpowder. It will be everywhere and the world will have to readjust. John McAfee, computer scientist, founder of McAfee Inc In the 1830s and 1840s a mania gripped the UK. A similar mania would soon grip the US in the 1870s and again in the 1890s.

He seems to have a fondness for maps and to be especially interested in diet (in particular, its relationship with genes). He mentions Ethereum a great deal, but the subject he keeps coming back to is Bitcoin. His pinned tweet links to the ‘best computer science paper on Bitcoin’. He comments that, ‘scams are fuelled by misplaced trust. Trust math, (next best) traditional auditing. Make bad security fail early’. And he asserts that ‘Trusted third party: security hole (mtGox) or large traditional bureaucracy (bank). Choose your poison.’ The first people he followed – Gavin Andreson, Andrew Miller and Peter Todd – were all heavily involved in Bitcoin from an early stage. The first companies he followed were Blockstream Project – which is ‘digitizing the entire planet’s assets for the betterment of all its occupants’ – Ethereum and Computer Science, which gives you daily tweets about computer science.


pages: 472 words: 117,093

Machine, Platform, Crowd: Harnessing Our Digital Future by Andrew McAfee, Erik Brynjolfsson

"Robert Solow", 3D printing, additive manufacturing, AI winter, Airbnb, airline deregulation, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, backtesting, barriers to entry, bitcoin, blockchain, British Empire, business cycle, business process, carbon footprint, Cass Sunstein, centralized clearinghouse, Chris Urmson, cloud computing, cognitive bias, commoditize, complexity theory, computer age, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Dean Kamen, discovery of DNA, disintermediation, disruptive innovation, distributed ledger, double helix, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ethereum, ethereum blockchain, everywhere but in the productivity statistics, family office, fiat currency, financial innovation, George Akerlof, global supply chain, Hernando de Soto, hive mind, information asymmetry, Internet of things, inventory management, iterative process, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, joint-stock company, Joseph Schumpeter, Kickstarter, law of one price, longitudinal study, Lyft, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Marc Andreessen, Mark Zuckerberg, meta analysis, meta-analysis, Mitch Kapor, moral hazard, multi-sided market, Myron Scholes, natural language processing, Network effects, new economy, Norbert Wiener, Oculus Rift, PageRank, pattern recognition, peer-to-peer lending, performance metric, plutocrats, Plutocrats, precision agriculture, prediction markets, pre–internet, price stability, principal–agent problem, Ray Kurzweil, Renaissance Technologies, Richard Stallman, ride hailing / ride sharing, risk tolerance, Ronald Coase, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Pinker, supply-chain management, TaskRabbit, Ted Nelson, The Market for Lemons, The Nature of the Firm, Thomas Davenport, Thomas L Friedman, too big to fail, transaction costs, transportation-network company, traveling salesman, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, ubercab, Watson beat the top human players on Jeopardy!, winner-take-all economy, yield management, zero day

They were instead about the vulnerabilities of cryptocurrencies and smart contracts revealed by the exploit. The Nakamoto Institute’s withering assessment was that Ethereum was “doomed.” Its combination of poor programming and terms of use that essentially made this lousy programming legally binding spelled disaster. Believers in the dream of decentralizing all the things, however, weren’t yet ready to give up. In July of 2016, Vitalik Buterin, one of Ethereum’s cofounders and the author (at nineteen years old) of the influential 2013 “Ethereum White Paper,” announced a “hard fork” in the cryptocurrency and its blockchain. If a majority of participants in The DAO accepted this fork (which was embodied in a new version of the Ethereum software), all previous transactions that occurred within the decentralized autonomous organization would be essentially forgotten, and all involved ethers would be returned to their original owners.

GMT: The DAO, “Introduction to the DAO,” last modified June 29, 2016, https://daowiki.atlassian.net/wiki/display/DAO/Introduction+to+the+DAO. 302 “The DAO”: Will Dunn, “The Rise and Fall of The DAO, the First Code-Based Company,” NS Tech, July 22, 2016, http://tech.newstatesman.com/feature/dao-code-based-company. 303 “paradigm shift” that could “offer new opportunities”: Seth Bannon, “The Tao of ‘The DAO’ or: How the Autonomous Corporation Is Already Here,” TechCrunch, May 16, 2016, https://techcrunch.com/2016/05/16/the-tao-of-the-dao-or-how-the-autonomous-corporation-is-already-here. 303 “entrepreneurs of the future”: Joanna Belbey, “How to Invest in the Institutional Revolution of Blockchain,” Forbes, January 18, 2017, http://www.forbes.com/sites/joannabelbey/2017/01/18/how-to-invest-in-the-institutional-revolution-of-blockchain/2/#5807c7603890. 303 Real money: Giulio Prisco, “The DAO Raises More than $117 Million in World’s Largest Crowdfunding to Date,” Bitcoin Magazine, May 16, 2016, https://bitcoinmagazine.com/articles/the-dao-raises-more-than-million-in-world-s-largest-crowdfunding-to-date-1463422191. 303 $162 million: The DAO, “Introduction.” 303 Shortly before The DAO’s funding window closed: Nathaniel Popper, “Paper Points Up Flaws in Venture Fund Based on Virtual Money,” New York Times, May 27, 2016, https://www.nytimes.com/2016/05/28/business/dealbook/paper-points-up-flaws-in-venture-fund-based-on-virtual-money.html. 303 “We discuss these attacks”: Dino Mark, Vlad Zamfir, and Emin Gün Sirer, “A Call for a Temporary Moratorium on ‘The DAO,’ ” Draft (v0.3.2), last modified May 30, 2016, https://docs.google.com/document/d/10kTyCmGPhvZy94F7VWyS-dQ4lsBacR2dUgGTtV98C40. 304 The anonymous hacker: Nathaniel Popper, “A Hacking of More than $50 Million Dashes Hopes in the World of Virtual Currency,” New York Times, June 17, 2016, https://www.nytimes.com/2016/06/18/business/dealbook/hacker-may-have-removed-more-than-50-million-from-experimental-cybercurrency-project.html. 304 Daniel Krawisz: Daniel Krawisz, LinkedIn profile, accessed February 7, 2017, https://www.linkedin.com/in/daniel-krawisz-323bb121. 304 The Nakamoto Institute’s withering assessment: Daniel Krawisz, “Ethereum Is Doomed,” Satoshi Nakamoto Institute, June 20, 2016, http://nakamotoinstitute.org/mempool/ethereum-is-doomed. 304 “hard fork”: E. J. Spode, “The Great Cryptocurrency Heist,” Aeon, February 14, 2017, https://aeon.co/essays/trust-the-inside-story-of-the-rise-and-fall-of-ethereum. 305 “In [minority members’] view”: Ibid. 305 “Ethereum Classic”: Ibid. 306 “The Resolution of the Bitcoin Experiment”: Mike Hearn, “The Resolution of the Bitcoin Experiment,” Mike’s blog, January 14, 2016, https://blog.plan99.net/the-resolution-of-the-bitcoin-experiment-dabb30201f7#.rvh0ditgj. 306 “It has failed because the community has failed”: Ibid. 306 the performance of the Bitcoin system suffered: Daniel Palmer, “Scalability Debate Continues as Bitcoin XT Proposal Stalls,” CoinDesk, January 11, 2016, http://www.coindesk.com/scalability-debate-bitcoin-xt-proposal-stalls. 306 Chinese exchanges accounted for 42%: Nathaniel Popper, “How China Took Center Stage in Bitcoin’s Civil War,” New York Times, June 29, 2016, https://www.nytimes.com/2016/07/03/business/dealbook/bitcoin-china.html. 306 an estimated 70% of all Bitcoin-mining gear: Danny Vincent, “We Looked inside a Secret Chinese Bitcoin Mine,” BBC News, May 4, 2016, http://www.bbc.com/future/story/20160504-we-looked-inside-a-secret-chinese-bitcoin-mine. 308 “a kid in Africa with a smartphone”: Brandon Griggs, “Futurist: We’ll Someday Accept Computers as Human,” CNN, March 12, 2012, http://www.cnn.com/2012/03/12/tech/innovation/ray-kurzweil-sxsw. 309 “The Nature of the Firm”: R.

The DAO made clear that there would be no second-guessing the decisions and outcomes it generated. So when it sent a third of its ethers to an anonymous hacker, that was a legitimate outcome under its complete contract. The hard fork in the Ethereum software announced in July of 2016 undid the hacker’s work. However, the fork also infuriated many members of that cryptocurrency’s community, who saw it as exactly the kind of thing that an owner would do, and the whole point of Ethereum was not only that it had no owners, but more fundamentally that it was not ownable. As a result, the Ethereum community split in two. Someone well versed in transaction cost economics and the realities of incomplete contracting might have predicted an outcome like this. The two of us are pessimistic that totally decentralized, purely crowd-based entities like The DAO will ever be economically dominant, no matter how technologically solid they become.


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The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order by Paul Vigna, Michael J. Casey

Airbnb, altcoin, bank run, banking crisis, bitcoin, blockchain, Bretton Woods, buy and hold, California gold rush, capital controls, carbon footprint, clean water, collaborative economy, collapse of Lehman Brothers, Columbine, Credit Default Swap, cryptocurrency, David Graeber, disintermediation, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, fiat currency, financial innovation, Firefox, Flash crash, Fractional reserve banking, hacker house, Hernando de Soto, high net worth, informal economy, intangible asset, Internet of things, inventory management, Joi Ito, Julian Assange, Kickstarter, Kuwabatake Sanjuro: assassination market, litecoin, Long Term Capital Management, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, McMansion, means of production, Menlo Park, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, Network effects, new economy, new new economy, Nixon shock, offshore financial centre, payday loans, Pearl River Delta, peer-to-peer, peer-to-peer lending, pets.com, Ponzi scheme, prediction markets, price stability, profit motive, QR code, RAND corporation, regulatory arbitrage, rent-seeking, reserve currency, Robert Shiller, Robert Shiller, Ross Ulbricht, Satoshi Nakamoto, seigniorage, shareholder value, sharing economy, short selling, Silicon Valley, Silicon Valley startup, Skype, smart contracts, special drawing rights, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, supply-chain management, Ted Nelson, The Great Moderation, the market place, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, tulip mania, Turing complete, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, underbanked, WikiLeaks, Y Combinator, Y2K, zero-sum game, Zimmermann PGP

For Daniel Larimer, one basic conceptual obstacle: Daniel Larimer, interviewed by Michael J. Casey, April 8, 2014. In mid-2013, journalist Vitalik Buterin also got: Vitalik Buterin, interviewed by Michael J. Casey, January 26, 2014. Buterin first laid out his vision in a white paper: Vitalik Buterin, “Ethereum White Paper,” January 2014, https://www.ethereum.org/pdfs/EthereumWhitePaper.pdf. The team also planned a fund-raiser: Michael J. Casey, “BitBeat: Ethereum Presale Hits $12.7 Million Tally,” Wall Street Journal, MoneyBeat blog, http://blogs.wsj.com/moneybeat/2014/08/05/bitbeat-ethereum-presale-hits-12-7-million-tally/. Here, once again at the vanguard: “The Ripple Protocol: Executive Summary for Financial Institutions,” Ripple.com, https://ripple.com/files/ripple-FIs.pdf. David Andolfatto, the chief economist at: David Andolfatto, “Bitcoin and Beyond: The Possibilities and the Pitfalls of Virtual Currencies,” Federal Reserve Bank of St.

Sounding every bit the MBA-qualified financial engineer, Buterin rattles off concepts for apps that could run on Ethereum and help reinvent Wall Street: digital-currency-denominated derivative contracts through which traditional currencies and commodities trade as digital IOU tokens; Ethereum-based security offerings that function without a need for the underwriting and book-running services of an investment bank; decentralized algorithms to challenge the sinister “dark pool” investment vehicles and high-frequency trading machines with which hedge funds, investment banks, and Wall Street high rollers get an edge on the market. But he admits he’s just tossing out ideas. For now, Ethereum is an unproven project. The ether-based compensation model for miners and the system of proof by which they would obtain their compensation was still a work in progress at the time of writing.

The solution he came up with quickly took the cryptocurrency world by storm: a completely redesigned, fully versatile, decentralized blockchain that could function as an open platform on which all manner of contracts and decentralized applications could be installed. He called it Ethereum. “We are hoping to be like the Android of cryptocurrency,” Buterin says, referring to the Google-designed mobile operating system that’s used by multiple models of smartphones and which had by 2014 inspired more than a million apps. “On Android you can install Google Maps, you can install Gmail, you can install whatever you want. That’s where we want cryptocurrency to go. Ethereum provides the base layer, and if you want to install a wallet, there’s an app for that; if you want to install a block explorer, you can design one; or a merchant payments solution or whatever.” A self-taught computer geek and hacker with no formal cryptography background, Buterin first laid out his vision in a white paper.


pages: 571 words: 106,255

The Bitcoin Standard: The Decentralized Alternative to Central Banking by Saifedean Ammous

Airbnb, altcoin, bank run, banks create money, bitcoin, Black Swan, blockchain, Bretton Woods, British Empire, business cycle, capital controls, central bank independence, conceptual framework, creative destruction, cryptocurrency, currency manipulation / currency intervention, currency peg, delayed gratification, disintermediation, distributed ledger, Ethereum, ethereum blockchain, fiat currency, fixed income, floating exchange rates, Fractional reserve banking, full employment, George Gilder, global reserve currency, high net worth, invention of the telegraph, Isaac Newton, iterative process, jimmy wales, Joseph Schumpeter, market bubble, market clearing, means of production, money: store of value / unit of account / medium of exchange, moral hazard, Network effects, Paul Samuelson, peer-to-peer, Peter Thiel, price mechanism, price stability, profit motive, QR code, ransomware, reserve currency, Richard Feynman, risk tolerance, Satoshi Nakamoto, secular stagnation, smart contracts, special drawing rights, Stanford marshmallow experiment, The Nature of the Firm, the payments system, too big to fail, transaction costs, Walter Mischel, zero-sum game

The trials and tribulations of Ethereum, the largest coin in terms of market value after Bitcoin, illustrate this point vividly. The Decentralized Autonomous Organization (DAO) was the first implementation of smart contracts on the Ethereum network. After more than $150 million was invested in this smart contract, an attacker was able to execute the code in a way that diverted around one‐third of all the DAO's assets to his own account. It would be arguably inaccurate to describe this attack as a theft, because all the depositors had accepted that their money will be controlled by the code and nothing else, and the attacker had done nothing but execute the code as it was accepted by the depositors. In the aftermath of the DAO hack, Ethereum developers created a new version of Ethereum where this inconvenient mistake never occurred, confiscating the attacker's funds and distributing them to his victims.

While this would be great for a new start‐up, it is anathema to a project that wants to demonstrate credible commitment to a fixed monetary policy. Should the teams behind any particular altcoin decide to change its monetary policy, it would be a relatively straightforward thing to achieve. Ethereum, for instance, does not yet have a clear vision of what it wants its monetary policy to be in the future, leaving the matter up to community discussion. While this may work wonders for the community spirit of Ethereum, it is no way to build a global hard money, which, to be fair, Ethereum does not claim to do. Whether it is because they are aware of this point, or to avoid run‐ins with political authority, or as a marketing gimmick, most altcoins do not market themselves as competitors to Bitcoin, but as performing tasks different to Bitcoin.

Code competence will always offer a strategic advantage to the most proficient over everyone else. This all became apparent with the first implementation of smart contracts on the Ethereum network, the Decentralized Autonomous Organization (DAO). After more than $150 million was invested in this smart contract, an attacker was able to execute the code in a way that diverted around a third of all the DAO's assets to his own account. It would be arguably inaccurate to describe this attack as a theft, because all the depositors had accepted that their money would be controlled by the code and nothing else, and the attacker had done nothing but execute the code as it was accepted by the depositors. In the aftermath of the DAO hack, Ethereum developers created a new version of Ethereum where this inconvenient mistake never occurred. This re‐injection of subjective human management is at odds with the objective of making code into law, and questions the entire rationale of smart contracts.


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The Politics of Bitcoin: Software as Right-Wing Extremism by David Golumbia

3D printing, A Declaration of the Independence of Cyberspace, Affordable Care Act / Obamacare, bitcoin, blockchain, Burning Man, crony capitalism, cryptocurrency, currency peg, distributed ledger, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, Extropian, fiat currency, Fractional reserve banking, George Gilder, jimmy wales, litecoin, Marc Andreessen, money: store of value / unit of account / medium of exchange, Mont Pelerin Society, new economy, obamacare, Peter Thiel, Philip Mirowski, risk tolerance, Ronald Reagan, Satoshi Nakamoto, seigniorage, Silicon Valley, Singularitarianism, smart contracts, Stewart Brand, technoutopianism, The Chicago School, Travis Kalanick, WikiLeaks

Baton Rouge, La.: Third Millennium Press. Bustillos, Maria. 2015. “Inside the Fight over Bitcoin’s Future.” New Yorker (August 25). http://www.newyorker.com/. Burdekin, Richard C., and Pierre L. Siklos, eds. 2004. Deflation: Current and Historical Perspectives. New York: Cambridge University Press. Buterin, Vitalik. 2014. “DAOs, DACs, Das, and More: An Incomplete Terminology Guide.” Ethereum (May 6). http://blog.ethereum.org/. Carrico, Dale. 2005. “Pancryptics: Technocultural Transformations of the Subject of Privacy.” Ph.D. diss., University of California, Berkeley. —. 2009. “Condensed Critique of Transhumanism.” Amor Mundi (January 25). http://amormundi.blogspot.com/. —. 2013a. “Futurological Discourse and Posthuman Terrains.” Existenz 8, no. 2: 47–63. —. 2013b. “The Superlative Summary.” Amor Mundi (July 14). http://amormundi.blogspot.com/.

One of the main proponents of DAOs and DACs is Vitalik Buterin, author of the passage about “smart contracts” above, “a Canadian college dropout and Bitcoin enthusiast” (Schneider 2014), cofounder of Bitcoin Magazine, and a recipient of one of the US$100,000 Thiel Fellowships funded by the eponymous right-wing technology entrepreneur and PayPal founder Peter Thiel (Rizzo 2014a)—fellowships that specifically promote the rejection of higher education, in a manner harmonious with the rejection by Thiel and others on the right wing of public goods (Lind 2014). Buterin is a cofounder of Ethereum, the best-known project to generalize blockchain technology into applications that go beyond currency-like systems. Buterin (2014) describes DAOs “and their subclass, DACs,” as the “holy grail” of decentralized applications. A DAO “is an entity that lives on the internet and exists autonomously, but also heavily relies on hiring individuals to perform certain tasks that the automaton itself cannot do.”

“An Introduction to the Cypherpunk Tale.” Bitcoin.com (August 30). http://www.bitcoin.com/. —. 2016. “Central Banks’ Failed Policies Are Strengthening Bitcoin.” Bitcoin.com (January 12). https://news.bitcoin.com/. Richardson, Tim. 2001. “Beenz Denies It’s about to Be Canned: Global ‘Net’ Currency Devalued Big-Time.” The Register (May 16). http://www.theregister.co.uk/. Rizzo, Pete. 2014a. “$100k Peter Thiel Fellowship Awarded to Ethereum’s Vitalik Buterin.” CoinDesk (June 5). http://www.coindesk.com/. —. 2014b. “Tokyo Police Launch Investigation into Missing Mt. Gox Bitcoin.” CoinDesk (July 30). http://www.coindesk.com/. Robinson, Jeffrey. 2014. Bitcon: The Naked Truth about Bitcoin. Seattle: Amazon Digital Services. “Ron Paul Sites Are Obsessed with Jews, Zionists, and Israel.” 2011. RonPaulSupporters.com (December). http://ronpaulsupporters.com/.


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The Code of Capital: How the Law Creates Wealth and Inequality by Katharina Pistor

"Robert Solow", Andrei Shleifer, Asian financial crisis, asset-backed security, barriers to entry, Bernie Madoff, bilateral investment treaty, bitcoin, blockchain, Bretton Woods, business cycle, business process, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, collateralized debt obligation, colonial rule, conceptual framework, Corn Laws, corporate governance, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, Donald Trump, double helix, Edward Glaeser, Ethereum, ethereum blockchain, facts on the ground, financial innovation, financial intermediation, fixed income, Francis Fukuyama: the end of history, full employment, global reserve currency, Hernando de Soto, income inequality, intangible asset, investor state dispute settlement, invisible hand, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, Kenneth Rogoff, land reform, land tenure, London Interbank Offered Rate, Long Term Capital Management, means of production, money market fund, moral hazard, offshore financial centre, phenotype, Ponzi scheme, price mechanism, price stability, profit maximization, railway mania, regulatory arbitrage, reserve currency, Ronald Coase, Satoshi Nakamoto, secular stagnation, self-driving car, shareholder value, Silicon Valley, smart contracts, software patent, sovereign wealth fund, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, time value of money, too big to fail, trade route, transaction costs, Wolfgang Streeck

If the code had bugs that could be exploited, this was a mistake that should be fixed by writing better code in the future; changing the code retroactively went against the fundamentals of the digital code as immutable and threatened to undermine its standing as an alternative to the discretionary power that is associated with states and state law. a n e w co d e ? 197 The decision rules of The DAO required a majority vote, and the pragmatists won the day; they altered the code, unwound The DAO, and returned the ether to the majority of the token holders. The minority, however, held on to the original code, which they now labeled “Ethereum Classic” (ETC), a new digital asset, which competes with the adulterated original Ethereum (ETH).38 The DAO is a cautionary tale of coded determinism operating in an unpredictable world. It also is a good illustration of how codes evolve, whether they are legal or digital. The pragmatists among The DAO’s token holders decided to leave the final say about its fate in the hands of humans. This was wise if one considers that the code itself is of human creation and if one values human autonomy over an abstract principle of immutability.

., p. 7. 27. De Soto, The Mystery of Capital, p. 179. 28. For a survey of the effects of formalizing property rights in the developing world in recent years, see Klaus Deininger, Land Policies for Growth and Poverty Reduction, World Bank Policy Research Reports (Washington, DC: World Bank, 2003). 29. The concept of the decentralized autonomous organization (DAO) is illustrated on the Ethereum website: https://www.ethereum.org/dao. For a useful account of The DAO’s brief existence, see Muhammed Izhar Mehar et al., “Understanding a Revolutionary and Flawed Grand Experiment in Blockchain: The DAO Attack,” available online at ssrn.com/abstract=3014782 (2017). 30. See the SEC’s press release of July 25, 2017, available online at https:// www.sec.gov/news/press-release/2017-131, about its investigative report that concluded that ICOs of the kind The DAO had issued were securities and as such subject to regulations and supervision. 31.

In the wake of a frenzy in the offerings of tokens or coins in digital ventures to the public, also dubbed “initial coin offerings,” or ICOs after the legacy practice of “initial public offerings” of shares or bonds, the US Securities and Exchange Commission (SEC) intervened. It affirmed that ICOs qualify as “securities” that are subject to standard registration requirements, a decision that reached The DAO only posthumously.30 The DAO was a venture capital fund that was built on the Ethereum blockchain. The DAO was designed to operate without a board of directors or any human officers. Instead, the firms’ investors received voting rights that allowed them to participate directly in developing investment strategies by proposing new investment opportunities to the firm. If agreed by the majority of investors, they would be implemented by the code, an open-source software that was available for everyone to see, but not for everyone to change.


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The Internet of Money by Andreas M. Antonopoulos

AltaVista, altcoin, bitcoin, blockchain, clean water, cognitive dissonance, cryptocurrency, disruptive innovation, Ethereum, ethereum blockchain, financial exclusion, global reserve currency, litecoin, London Interbank Offered Rate, Marc Andreessen, Oculus Rift, packet switching, peer-to-peer lending, Ponzi scheme, QR code, ransomware, reserve currency, Satoshi Nakamoto, self-driving car, Skype, smart contracts, the medium is the message, trade route, underbanked, WikiLeaks, zero-sum game

Currency as a Language Bitcoin Expo 2014 - Keynote; Toronto, Ontario, Canada; April 2014 Video Link: https://www.youtube.com/watch?v=jw28y81s7Wo This is going to be a bit more of a philosophical talk about the future of cryptocurrencies and what I’ve learned here at this event. This event is called the Bitcoin Expo 2014. It might have been called the Bitcoin and Ethereum Expo 2014. I don’t know if you noticed, but Ethereum had a pretty big presence here. An interesting question comes up, actually quite a few people have asked me: "Does Ethereum threaten the future of bitcoin? Does it steal some of its thunder?" Those are questions I’ve heard several times, and I’ve heard people refer to that issue in trying to understand altcoins - wondering whether altcoins essentially threaten the dominance of bitcoin, if they make bitcoin weaker, if they distribute the value of the network too broadly. 7.1.

What if scarcity is not derived from the issuer but is derived in terms of adoption and in terms of the token itself? "Currency as a means of expression, currency as a tool of language, is no longer up to the issuer. It is up to us as individuals making a choice to use that currency, and we give it value through our use." We’re going to have currencies for different uses. Already, you have bitcoin that provides a very specific monetary policy. You have Ethereum that can provide a contract platform. There’s Namecoin for distributed naming conventions. There are many others, and there will be many others that will solve other problems: protein folding, the search for extraterrestrial life. Maybe we’ll have currencies that are better for microtransactions and micropayments with very fast resolution. Maybe we’ll have currencies that are better for larger transactions, like real estate.

We’re going to start treating currency as an application, and in order to do that we’re going to need interfaces that allow us a unified currency experience, that allow us to have a single wallet with perhaps 150 different currencies in it. Because of inventions like sidechains, decentralized exchanges, fluid liquid systems and the complete absence of monopoly, of lock-in, of hostage situations around the currency, we will be able to instantaneously and at very low cost convert from bitcoin to Namecoin to Dogecoin to Ethereum. If we can do that, then it doesn’t matter because we won’t do that; our unified wallet interface will do that, by trying to see what we’re trying to achieve with our currency. If I’m buying a house, it might express my transactional will in the modality of bitcoin because that is the most suitable currency. When I try to name the domain for that house, it will convert some to Namecoin. The contract itself will be paid in ether.


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

accounting loophole / creative accounting, Ada Lovelace, Airbnb, algorithmic trading, asset allocation, autonomous vehicles, balance sheet recession, bank run, banks create money, Basel III, basic income, Ben Bernanke: helicopter money, bitcoin, blockchain, Bretton Woods, business cycle, business process, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, cashless society, cellular automata, central bank independence, Claude Shannon: information theory, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, complexity theory, constrained optimization, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, David Graeber, deskilling, Diane Coyle, discrete time, disruptive innovation, distributed ledger, diversification, double entry bookkeeping, Ethereum, ethereum blockchain, fiat currency, financial innovation, financial intermediation, Flash crash, floating exchange rates, Fractional reserve banking, full employment, George Akerlof, 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, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, knowledge economy, large denomination, liquidity trap, London Whale, low skilled workers, M-Pesa, Marc Andreessen, market bubble, market fundamentalism, Mexican peso crisis / tequila crisis, MITM: man-in-the-middle, 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, 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, Satoshi Nakamoto, Satyajit Das, savings glut, seigniorage, Silicon Valley, Skype, smart contracts, software as a service, software is eating the world, speech recognition, statistical model, Stephen Hawking, 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, Von Neumann architecture, Washington Consensus

A smart contract, according to Ethereum’s founder, Vitalik Buterin, “is a computer program that directly controls some digital asset.” Smart Contracts are essentially the same as Apps, except they perform a different kind of automation. While the traditional Apps available on a Google Play Store or Apple App Store are useful for certain operations, Smart Contracts function as Apps that perform value exchange operations when they receive a certain input. Just as the blockchain is a digitally native protocol that is designed for value exchange, Smart Contracts are native to the Blockchain and perform value exchange operations based on the input signals that they receive from the Blockchain. This is currently one of the explosive areas of innovation and protocols developed by platforms like Ethereum are allowing the large scale deployment of Smart Contracts.

Retrieved from International Business Times: 230 appendix a ■ Bibliography and References http://www.ibtimes.com/next-financial-crisis-could-be-predicted-smartereconomic-model-experts-say-2313345 Palley, T. I. (2007). Financialization: What It Is and Why It Matters. Washington, D.C.: The Levy Economics Institute and Economics for Democratic and Open Societies. Palmer, D. (2016, Feburary 24). 7 Cool Decentralized Apps Being Built on Ethereum. Retrieved from CoinDesk: http://www.coindesk.com/7-cool-decentralized-appsbuilt-ethereum/ Partnoy, F. (2009). Infectious Greed: How Deceit and Risk Corrupted the Financial Markets. New York City: PublicAffairs. Plotkin, A. J. (2016). Small groups and long memories promote cooperation. Nature, Scientific Reports 6, Article number: 26889, doi:10.1038/srep26889. PwC. (2016). Blurred Lines: How FinTech is shaping Financial Services. Pricewaterhouse Cooper.

Some skeptics still stubbornly state that, owing to regulatory and operational limitations, this technology will remain on the fringes of finance and exist as just a cryptocurrency. But the evidence shows that it is much more. It is a protocol, a commodity, an automation system, a secure exchange, a ledger, and a community that is creating a counter-culture movement. 23 On the 30th of April 2016, the founders of SLOCK.IT launched the DAO (Decentralized Autonomous Organization) on the Ethereum platform. 65 Chapter 2 ■ Fragmentation of Finance At the same time, incumbents and startups face different challenges. While banks invest more heavily in innovation (e.g., Bank of America has a $3 billion annual innovation budget), they still need to find ways to diffuse their innovation strategies across their organizations, yet retain market share. To this end, banks have begun to collaborate with each other to develop new platforms with similar standards to update their legacy infrastructure; one of the main objectives of the R3 consortium is to address the issue of standards for global cross-border Blockchain use.


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Orwell Versus the Terrorists: A Digital Short by Jamie Bartlett

augmented reality, barriers to entry, bitcoin, blockchain, crowdsourcing, cryptocurrency, Edward Snowden, Ethereum, ethereum blockchain, Kuwabatake Sanjuro: assassination market, Satoshi Nakamoto, technoutopianism, Zimmermann PGP

Bitcoin creates an immutable, unchangeable public copy of every transaction ever made by its users, which is hosted and verified by every computer that downloads the software. This public copy is called the ‘blockchain’. Pretty soon, enthusiasts figured out that the blockchain system could be used for anything. Armed with 30,000 Bitcoins (around $12 million) of crowdfunded support, the Ethereum project is dedicated to creating a new, blockchain-operated internet. Ethereum’s developers hope the system will herald a revolution in the way we use the net – allowing us to do everything online directly with each other, not through the big companies that currently mediate our online interaction and whom we have little choice but to trust with our data. Already others have applied this principle to all sorts of areas. One man built a permanent domain name system called Namecoin; another an untraceable email system call Bitmessage.


pages: 375 words: 88,306

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism by Arun Sundararajan

additive manufacturing, Airbnb, AltaVista, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, basic income, bitcoin, blockchain, Burning Man, call centre, collaborative consumption, collaborative economy, collective bargaining, commoditize, corporate social responsibility, cryptocurrency, David Graeber, distributed ledger, employer provided health coverage, Erik Brynjolfsson, Ethereum, ethereum blockchain, Frank Levy and Richard Murnane: The New Division of Labor, future of work, George Akerlof, gig economy, housing crisis, Howard Rheingold, information asymmetry, Internet of things, inventory management, invisible hand, job automation, job-hopping, Kickstarter, knowledge worker, Kula ring, Lyft, Marc Andreessen, megacity, minimum wage unemployment, moral hazard, moral panic, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, peer-to-peer rental, profit motive, purchasing power parity, race to the bottom, recommendation engine, regulatory arbitrage, rent control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Ross Ulbricht, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart contracts, Snapchat, social software, supply-chain management, TaskRabbit, The Nature of the Firm, total factor productivity, transaction costs, transportation-network company, two-sided market, Uber and Lyft, Uber for X, uber lyft, universal basic income, Zipcar

Dionysis Zindros, “A Pseudonymous Trust System for a Decentralized Anonymous Marketplace,” GitHub Gist, 2015, https://gist.github.com/dionyziz/e3b296861175e0ebea4b. 11. Melanie Swan, Blockchain: Blueprint for a New Economy (Sebastopol, CA: O’Reilly Media, Inc., 2015). 12. Primavera De Fillipi, “Ethereum: Freenet or Skynet?,” Talk presented at the Berkman Center for Internet & Society, Harvard University, Cambridge, MA, April 15, 2014. 13. Lawrence Lessig, Code and Other Laws of Cyberspace (New York: Basic Books, 1999). 14. Vitalik Buterin, “Decentralized Protocol Monetization and Forks,” Ethereum Blog, April 30, 2014. https://blog.ethereum.org/2014/04/30/decentralized-protocol-monetization-and-forks. 15. It is likely that architecting it “optimally” is impossible, based on a set of results from a branch of economics called mechanism design. 16. Chris Dixon, “Some Ideas for Native Bitcoin Apps.”

Perhaps some of the greatest opportunity from decentralized peer-to-peer systems will come from the emerging decentralized autonomous organizations (DAOs) and decentralized collaborative organizations (DCOs) such as those that are being architected by Buterik’s Ethereum and by Field and DeFillipi’s Backfeed. Such organizations posit a holistic model for organizing economic activity in a decentralized manner. Perhaps these will allow the kind of decentralized, distributed ownership and control of the “platform cooperatives” that I discuss in chapter 8. One might wonder what realistic possibilities exist for organizations that seemingly exist embedded only in computer code. However, as Buterik points out about decentralized protocols in general, “On the one hand, much like Bitcoin itself, they are in a very clear way ‘backed by nothing.’ On the other hand, they actually have quite a powerful backing underneath, and one that is difficult to unseat.” What is this backing that Buterik refers to? As he notes in an Ethereum Blog post in April 2014, “It is important to first understand that, in the space of tech companies and especially social networking startups, a large number of them are literally backed by almost nothing but social consensus.”

You also earn zooz by inviting others to download the app. (The project leaders also sold some zooz to raise money.) Once the level of adoption in any neighborhood is sufficiently high, the ridesharing portion of the app gets activated. You can then use your accumulated zooz to buy rides, much like you’d use currency to buy an Uber or Lyft ride. As Vitalik Buterin, an influential writer about decentralized peer-to-peer systems and the founder of Ethereum, a decentralized platform that runs smart contracts, noted in a blog post, “the idea of releasing a new currency as a mechanism for funding protocol development is perhaps one of the most interesting economic innovations to come out of the cryptocurrency space.”14 But a critical determinant of success is architecting this distribution of value right.15 It also seems important for the manifestation of this value, the “coin,” to be of continuing value as the platform grows and matures.


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The Evolution of Everything: How New Ideas Emerge by Matt Ridley

"Robert Solow", affirmative action, Affordable Care Act / Obamacare, Albert Einstein, Alfred Russel Wallace, AltaVista, altcoin, anthropic principle, anti-communist, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Boris Johnson, British Empire, Broken windows theory, Columbian Exchange, computer age, Corn Laws, cosmological constant, creative destruction, Credit Default Swap, crony capitalism, crowdsourcing, cryptocurrency, David Ricardo: comparative advantage, demographic transition, Deng Xiaoping, discovery of DNA, Donald Davies, double helix, Downton Abbey, Edward Glaeser, Edward Lorenz: Chaos theory, Edward Snowden, endogenous growth, epigenetics, Ethereum, ethereum blockchain, facts on the ground, falling living standards, Ferguson, Missouri, financial deregulation, financial innovation, Frederick Winslow Taylor, Geoffrey West, Santa Fe Institute, George Gilder, George Santayana, Gunnar Myrdal, Henri Poincaré, hydraulic fracturing, imperial preference, income per capita, indoor plumbing, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Jane Jacobs, Jeff Bezos, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kevin Kelly, Khan Academy, knowledge economy, land reform, Lao Tzu, long peace, Lyft, M-Pesa, Mahatma Gandhi, Mark Zuckerberg, means of production, meta analysis, meta-analysis, mobile money, money: store of value / unit of account / medium of exchange, Mont Pelerin Society, moral hazard, Necker cube, obamacare, out of africa, packet switching, peer-to-peer, phenotype, Pierre-Simon Laplace, price mechanism, profit motive, RAND corporation, random walk, Ray Kurzweil, rent-seeking, reserve currency, Richard Feynman, rising living standards, road to serfdom, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, sharing economy, smart contracts, South Sea Bubble, Steve Jobs, Steven Pinker, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, twin studies, uber lyft, women in the workforce

FCC to Congress: U.N.’s ITU Internet plans ‘must be stopped’. zdnet.com 5 February 2013. On net censorship, MacKinnon, Rebecca 2012. Consent of the Networked. Basic Books. On blockchains, Frisby, Dominic 2014. Bitcoin: The Future of Money?. Unbound. On Nick Szabo’s ‘shelling out’, nakamotoinstitute.org/shelling-out/. On Ethereum’s white paper, A Next-Generation Smart Contract and Decentralized Application Platform. https://github.com/ethereum. On private money, Dowd, K. 2014. New Private Monies. IEA. On smart contracts, De Filippi, P. 2014. Ethereum: freenet or skynet?. At cyber.law.harvard.edu/events 14 April 2014. On digital politics, Carswell, Douglas 2014. iDemocracy will change Westminster for the Better. Govknow.com 20 April 2014. And Carswell, Douglas 2012. The End of Politics and the Birth of iDemocracy. Biteback. Also Mair, Peter 2013.

If you live under a despotic regime, sending a message critical of your government on Twitter leaves you vulnerable to that government coercing Twitter, the company, into handing over your details. With Twister, that will not be possible. Then there is Namecoin, which aims to issue internet names in a decentralised, peer-to-peer fashion; Storj, which plans to allow cloud storage of files hidden inside blockchains; and Ethereum, which is a decentralised peer-to-peer network ‘designed to replace absolutely anything that can be described in code’, as Matthew Sparkes puts it. The digital expert Primavera De Filippi sees Ethereum and its ilk coming up with smart contracts, allowing ‘distributed autonomous organisations’ that, once they have been deployed on the blockchain, ‘no longer need (nor heed) their creators’. In other words, not just driverless cars, but ownerless firms. Imagine in the future summoning a taxi that not only has no driver, but that belongs to a computer network, not to a human being.

His motivation was clear. Bitcoin was designed to maintain its value without any precious-metal backing, without any centralised issuer, and without any intrinsic value. Satoshi invited users to ‘escape the arbitrary inflation risk of centrally managed currencies!’ It is hard to get your head around how bitcoin works. One of the pithiest explanations I have come across is in a recent launch by Ethereum, a business built to follow up on bitcoin: ‘The innovation provided by Satoshi is the idea of combining a very simple decentralised consensus protocol, based on nodes combining transactions into a “block” every ten minutes, creating an ever-growing blockchain, with proof of work as a mechanism through which nodes gain the right to participate in the system.’ If you think that’s hard to understand, you are not alone.


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Before Babylon, Beyond Bitcoin: From Money That We Understand to Money That Understands Us (Perspectives) by David Birch

agricultural Revolution, Airbnb, bank run, banks create money, bitcoin, blockchain, Bretton Woods, British Empire, Broken windows theory, Burning Man, business cycle, capital controls, cashless society, Clayton Christensen, clockwork universe, creative destruction, credit crunch, cross-subsidies, crowdsourcing, cryptocurrency, David Graeber, dematerialisation, Diane Coyle, disruptive innovation, distributed ledger, double entry bookkeeping, Ethereum, ethereum blockchain, facts on the ground, fault tolerance, fiat currency, financial exclusion, financial innovation, financial intermediation, floating exchange rates, Fractional reserve banking, index card, informal economy, Internet of things, invention of the printing press, invention of the telegraph, invention of the telephone, invisible hand, Irish bank strikes, Isaac Newton, Jane Jacobs, Kenneth Rogoff, knowledge economy, Kuwabatake Sanjuro: assassination market, large denomination, M-Pesa, market clearing, market fundamentalism, Marshall McLuhan, Martin Wolf, mobile money, money: store of value / unit of account / medium of exchange, new economy, Northern Rock, Pingit, prediction markets, price stability, QR code, quantitative easing, railway mania, Ralph Waldo Emerson, Real Time Gross Settlement, reserve currency, Satoshi Nakamoto, seigniorage, Silicon Valley, smart contracts, social graph, special drawing rights, technoutopianism, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, tulip mania, wage slave, Washington Consensus, wikimedia commons

On the one hand there were advocates of the ‘code is law’ school of thought who felt that the investors should take their medicine, and on the other there were advocates of the ‘pragmatic’ school of thought who felt that the transactions should be reversed. Since you can’t go back and edit a blockchain (which is sort of the point of it), this is achieved by ‘forking’ to create a new blockchain. This was done but a significant minority of miners felt that this was the wrong decision so they continued with the original blockchain as Ethereum Classic. At the time of writing, the ‘market cap’ of Ethereum is significantly higher than that of Ethereum Classic. Ripple After Bitcoin and Ethereum, the third biggest cryptocurrency is Ripple, which unlike those first two has its roots in local exchange trading systems (Peck 2013). It is a protocol for value exchange that uses a shared ledger but it does not use a Bitcoin-like blockchain, preferring another kind of what is known as a ‘Byzantine fault-tolerant consensus-forming process’.

Crypto-alternatives Not only will there be cryptocurrencies beyond Bitcoin and not only will they be better – more powerful and more efficient – there will also be a great many of them as the cost of launching a digital currency falls. Without launching into a treatise on cryptocurrencies, I think it would be useful to take a quick look at a couple of the newer cryptocurrencies on the block (pun intended) to give a sense of the spectrum of possibilities. Ethereum Ethereum is comparable to Bitcoin, in that it uses a blockchain, but it was designed to provide a better platform for shared ledger applications. One of the most interesting users of such applications was the Distributed Autonomous Organization (DAO). The general concept of a distributed autonomous organization goes back a few years, having roots in organizational decentralization theories that have been turbocharged (as William Mougayar puts it) by cryptocurrency technologies and trust-based automation (Mougayar 2016), but the DAO in question was created as a new kind of business: an investor-directed investment fund.


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Blockchain Basics: A Non-Technical Introduction in 25 Steps by Daniel Drescher

bitcoin, blockchain, business process, central bank independence, collaborative editing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, Ethereum, ethereum blockchain, fiat currency, job automation, linked data, peer-to-peer, place-making, Satoshi Nakamoto, smart contracts, transaction costs

About the Technical Reviewer Laurence Kirk who after a successful career writing low latency financial applications for the City of London, was captivated by the potential of distributed ledger technology. He moved to Oxford to study for his master’s degree and set up Extropy.io, a consultancy working with start- ups to develop applications on the Ethereum platform. Passionate about distributed technol- ogy, he now works as a developer, evangelist, and educator about Ethereum. Introduction This introduction answers the most important question that every author has to answer: Why should anyone read this book? Or more specifically: Why should anyone read another book about the blockchain? Continue reading and you will learn why this book was written, what you can expect from this book, what you cannot expect from this book, for whom the book was writ- ten, and how the book is structured.

Blockchain applications in the real world rarely utilize a constant difficulty level for all blocks. Instead they typically utilize a dynamic difficulty level based on the speed at which new blocks are added. 3 This ensures that the time needed to solve the hash puzzle stays at a level that prevents nodes from manipulating the history of transaction data while the actual computational effort may increase. 3Okupski, Krzysztof. Bitcoin developer reference. Working paper. 2014; Wood, Gavin. Ethereum: A secure decentralized generalized transaction ledger. 2014. http://gavwood. com/paper.pdf. Blockchain Basics 143 Outlook This step explained that the blockchain prevents the history of transaction data from being manipulated or forged by turning the blockchain-data-structure into an immutable append-only data store. The next step focuses on making that data store available to everyone in a distributed peer-to-peer system.

How It Works The idea of selecting a transaction history based on the computational effort that was spent for creating it has led to the following two criteria: • The longest-chain-criterion2 • The heaviest-chain-criterion3 The Longest-Chain-Criterion The longest-chain-criterion is based on the idea that the blockchain-data- structure that comprises the most blocks represents the most aggregated computational effort. In order to study this criterion, let’s consider an initial situation were all the nodes of a distributed system maintain and agree on 2Nakamoto, Satoshi. Bitcoin: A peer-to-peer electronic cash system. 2008. https://bitcoin. org/bitcoin.pdf. 3Wood, Gavin. Ethereum: A secure decentralized generalized transaction ledger. 2014. http://gavwood.com/paper.pdf; Okupski, Krzysztof. Bitcoin developer reference. Working paper. 2014. Blockchain Basics 169 the identical version of the blockchain-data-structure, as depicted in Figure 19-1, which presents a schematic blockchain-data-structure that omits many details for simplicity. Each of the boxes represents one block that is identified with a shortened hash value.


pages: 403 words: 111,119

Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist by Kate Raworth

"Robert Solow", 3D printing, Asian financial crisis, bank run, basic income, battle of ideas, Berlin Wall, bitcoin, blockchain, Branko Milanovic, Bretton Woods, Buckminster Fuller, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, choice architecture, clean water, cognitive bias, collapse of Lehman Brothers, complexity theory, creative destruction, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, dematerialisation, disruptive innovation, Douglas Engelbart, Douglas Engelbart, en.wikipedia.org, energy transition, Erik Brynjolfsson, Ethereum, ethereum blockchain, Eugene Fama: efficient market hypothesis, experimental economics, Exxon Valdez, Fall of the Berlin Wall, financial deregulation, Financial Instability Hypothesis, full employment, global supply chain, global village, Henri Poincaré, hiring and firing, Howard Zinn, Hyman Minsky, income inequality, Intergovernmental Panel on Climate Change (IPCC), invention of writing, invisible hand, Isaac Newton, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kickstarter, land reform, land value tax, Landlord’s Game, loss aversion, low skilled workers, M-Pesa, Mahatma Gandhi, market fundamentalism, Martin Wolf, means of production, megacity, mobile money, Mont Pelerin Society, Myron Scholes, neoliberal agenda, Network effects, Occupy movement, off grid, offshore financial centre, oil shale / tar sands, out of africa, Paul Samuelson, peer-to-peer, planetary scale, price mechanism, quantitative easing, randomized controlled trial, Richard Thaler, Ronald Reagan, Second Machine Age, secular stagnation, shareholder value, sharing economy, Silicon Valley, Simon Kuznets, smart cities, smart meter, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, statistical model, Steve Ballmer, The Chicago School, The Great Moderation, the map is not the territory, the market place, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, too big to fail, Torches of Freedom, trickle-down economics, ultimatum game, universal basic income, Upton Sinclair, Vilfredo Pareto, wikimedia commons

And since that record is stored on every computer in the network, it acts as a public ledger that cannot be altered, corrupted or deleted, making it a highly secure digital backbone for the future of e-commerce and transparent governance. One fast-rising digital currency that uses blockchain technology is Ethereum, which, among its many possible applications, is enabling electricity microgrids to set up peer-to-peer trading in renewable energy. These microgrids allow every nearby home, office or institution with a smart meter, Internet connection, and solar panel on its roof to hook in and sell or buy surplus electrons as they are generated, all automatically recorded in units of the digital currency. Such decentralised networks – ranging from a neighbourhood block to a whole city – build community resilience against blackouts and cut long-distance energy transmission losses at the same time. What’s more, the information embedded in every Ethereum transaction allows network members to put their values into action in the microgrid market, for example by opting to buy electricity from the nearest or greenest suppliers, or only from those that are community-owned or not-for-profit.59 And this is just one example of its potential.

Ruddick, W. (2015) ‘Kangemi-Pesa Launch Prep & More Currency News’, Grassroots Economics, available at: http://www.grassrootseconomics.org/kangemi-pesa-launch-prep 57. www.zeitvorsorge.ch/ 58. Strassheim, I. (2014) ‘Zeit statt Geld fürs Alter sparen’, Migros-Magazin, 1 September 2014. www.zeitvorsorge.ch/#!/DE/24/Medien.htm 59. DEVCON1 (2016) Transactive Grid: a decentralized energy management system. Presentation at Ethereum Developer Conference, 9–13 November 2015, London, available at: https://www.youtube.com/watch?v=kq8RPbFz5UU 60. Seaman, D. (2015) ‘Bitcoin vs. Ethereum explained for NOOBZ’, published 30 November 2015, available at: https://www.youtube.com/watch?v=rEJKLFH8q5c 61. Trades Union Congress (2012) The Great Wages Grab. London: TUC. https://www.tuc.org.uk/sites/default/files/tucfiles/TheGreatWagesGrab.pdf 62. Mishel, L. and Shierholz, H. (2013) A Decade of Flat Wages. EPI Briefing Paper no. 365, Washington, DC: Economic Policy Institute. http://www.epi.org/files/2013/BP365.pdf 63.

What’s more, the information embedded in every Ethereum transaction allows network members to put their values into action in the microgrid market, for example by opting to buy electricity from the nearest or greenest suppliers, or only from those that are community-owned or not-for-profit.59 And this is just one example of its potential. ‘Ethereum is a currency for the modern age,’ says the cryptocurrency expert David Seaman. ‘It’s a platform that could be really important to society down the road in ways that we can’t even predict yet.’60 These very different examples illustrate a few of the myriad possibilities of monetary redesign, involving the market, the state and the commons. But each one makes clear that the way that money is designed – its creation, its character, and its intended use – has far-reaching distributional implications. Recognising this invites us to escape the monoculture of money and put the potential of distributive design at the heart of a new financial ecosystem.


pages: 313 words: 91,098

The Knowledge Illusion by Steven Sloman

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

The success of these applications for collaboration depends on how well these problems are solved. Platforms to support this kind of decentralized collaborative activity are just coming into being with futuristic names like Ethereum, Sensorica, and Colony. Ethereum is inspired by the success of Bitcoin, an Internet currency that is decentralized, not administered by any single entity. The information about who owns how much Bitcoin is stored in a public ledger of transactions called a block chain. A block chain is a sophisticated technology for maintaining a record of all transactions that is updated and stored across the network of Bitcoin users. Distributing the ledger of transactions across the network is a good way to prevent mistakes and cheating. Ethereum uses a block chain method to allow collaboration via decentralized agreement of everyone involved in a project. The assumption is that information is safer if it is distributed across the community, preventing any one individual from having too much access.

See chaos theory consequences vs. values arguments, 182–87 contribution of individuals example of group thinking, 122 Copernicus, Nicolaus, 198–99 counterfactual thought, 64–65 Galileo’s experiments with dropping different weights, 65–66 imagining scenarios to figure out likely outcomes, 66 crowdsourcing expertise, 146–50 ox’s weight example, 148 Pallokerho-35 Finnish soccer club example, 148 prediction market, 149 user ratings, 148 crows ability to reason diagnostically, 62 CRT (Cognitive Reflection Test), 80–84 bat and ball problem, 81 lily pad problem, 81–82 machines and widgets problem, 82 crystallized intelligence, 202 cult communities, 260 cultural values and cognition, 160–63 reconciling conflicting beliefs, 161–62 “Science Mike” (Mike McHargue), 160–62 cumulative culture, 117–18 curse of knowledge, 128, 244 curving bullets example of physics, 69–70 Dalio, Ray, 253 Damasio, Antonio, 103 decentralized collaborative activity, 149–50 Bitcoin, 150 block chain technology, 150 Ethereum, 150 decision-making, 103–05, 240, 241, 248–49, 250–53 deficit model of science attitudes, 157–60 Dehghani, Morteza, 185–86 Descartes, René, 87 de Soto, Hernando, 244–45 DeVito, Danny, 45–46 Dewey, John, 216 diagnostic reasoning, 58–62 crow example, 62 lethargy example, 59–61 diSessa, Andrea, 71 disgust, feelings of, 104–05 division of cognitive labor, 14, 109–11, 120–21, 128–29 area of expertise example, 120 car analogy example, 207–08 in the field of science, 222–23 household finances, 247 wine expert example, 120 dogs Cassie example, 49–50 Pavlovian conditioning, 50–51 doorway example of optic flow, 99–100 driving ability example of ignorance, 257–58 Dunbar, Robin, 113 Dunning, David, 257–58 Dunning-Kruger effect, 258 Eastwood, Clint, 172 economics of science, 227–28 education application of classroom learning, 216–17 becoming a car mechanic example, 219–20 expressing desire to learn that which is unknown, 221 financial issues, 240–41 history of Spain example, 220 Ignorance course, 221 illusion of comprehension, 217–18 just-in-time, 251–52 learning to accept what you don’t know, 220–21 mathematical abilities of Brazilian children, 215–16 peer, 230–31 purpose of, 219–21 teaching science, 222, 225–32 Einstein, Albert, 199 embodied intelligence, 91–93 embodiment, 102 emotional responses that influence decision-making, 103–05, 240 engagement as a human concept, 117 environment, knowledge of your personal, 94–96 Ethereum, 150 expertise and crowdsourcing, 146–50 in scientific matters, 226–27 to understand community issues, 188–89 explanation foes and fiends, 237–39 advertising, 239–40, 241–42 Band-Aids example, 237–38 skin care example, 239–40 vesting service letter example, 243–44 explorers’ self-confidence, 263 eyesight.

See chaos theory consequences vs. values arguments, 182–87 contribution of individuals example of group thinking, 122 Copernicus, Nicolaus, 198–99 counterfactual thought, 64–65 Galileo’s experiments with dropping different weights, 65–66 imagining scenarios to figure out likely outcomes, 66 crowdsourcing expertise, 146–50 ox’s weight example, 148 Pallokerho-35 Finnish soccer club example, 148 prediction market, 149 user ratings, 148 crows ability to reason diagnostically, 62 CRT (Cognitive Reflection Test), 80–84 bat and ball problem, 81 lily pad problem, 81–82 machines and widgets problem, 82 crystallized intelligence, 202 cult communities, 260 cultural values and cognition, 160–63 reconciling conflicting beliefs, 161–62 “Science Mike” (Mike McHargue), 160–62 cumulative culture, 117–18 curse of knowledge, 128, 244 curving bullets example of physics, 69–70 Dalio, Ray, 253 Damasio, Antonio, 103 decentralized collaborative activity, 149–50 Bitcoin, 150 block chain technology, 150 Ethereum, 150 decision-making, 103–05, 240, 241, 248–49, 250–53 deficit model of science attitudes, 157–60 Dehghani, Morteza, 185–86 Descartes, René, 87 de Soto, Hernando, 244–45 DeVito, Danny, 45–46 Dewey, John, 216 diagnostic reasoning, 58–62 crow example, 62 lethargy example, 59–61 diSessa, Andrea, 71 disgust, feelings of, 104–05 division of cognitive labor, 14, 109–11, 120–21, 128–29 area of expertise example, 120 car analogy example, 207–08 in the field of science, 222–23 household finances, 247 wine expert example, 120 dogs Cassie example, 49–50 Pavlovian conditioning, 50–51 doorway example of optic flow, 99–100 driving ability example of ignorance, 257–58 Dunbar, Robin, 113 Dunning, David, 257–58 Dunning-Kruger effect, 258 Eastwood, Clint, 172 economics of science, 227–28 education application of classroom learning, 216–17 becoming a car mechanic example, 219–20 expressing desire to learn that which is unknown, 221 financial issues, 240–41 history of Spain example, 220 Ignorance course, 221 illusion of comprehension, 217–18 just-in-time, 251–52 learning to accept what you don’t know, 220–21 mathematical abilities of Brazilian children, 215–16 peer, 230–31 purpose of, 219–21 teaching science, 222, 225–32 Einstein, Albert, 199 embodied intelligence, 91–93 embodiment, 102 emotional responses that influence decision-making, 103–05, 240 engagement as a human concept, 117 environment, knowledge of your personal, 94–96 Ethereum, 150 expertise and crowdsourcing, 146–50 in scientific matters, 226–27 to understand community issues, 188–89 explanation foes and fiends, 237–39 advertising, 239–40, 241–42 Band-Aids example, 237–38 skin care example, 239–40 vesting service letter example, 243–44 explorers’ self-confidence, 263 eyesight. See vision facial recognition, 45–46 false information, spreading, 231–32 Faro, David, 164 fear, 104 Fernbach, Philip, 121–22 financial issues annuity paradox, 242–43 consumers’ lack of knowledge regarding, 233–37, 253 credit card debt, 235–36 economies as example of hive mind collaboration, 244–46 education programs to address, 240–41 household cognitive financial labor, 246–47 just-in-time education, 251–52 linear vs. nonlinear change, 234–37 mortgage rates and payments, 233, 236–37, 246 savings, growth of, 234–35 simple decision rules for, 250–51 value of currency, 245–46 Woodward, Susan, 233–34 Yap economy, 245 Fisher, Matt, 137 fluid intelligence, 202 fly ball example of gaze-direction strategy, 96–98 flying as an example of shared knowledge, 18 food choices example of libertarian paternalism, 248–49 hunting for, 108–10, 113 irradiation, 167–68 forward reasoning.


pages: 237 words: 67,154

Ours to Hack and to Own: The Rise of Platform Cooperativism, a New Vision for the Future of Work and a Fairer Internet by Trebor Scholz, Nathan Schneider

1960s counterculture, activist fund / activist shareholder / activist investor, Airbnb, Amazon Mechanical Turk, barriers to entry, basic income, bitcoin, blockchain, Build a better mousetrap, Burning Man, capital controls, citizen journalism, collaborative economy, collaborative editing, collective bargaining, commoditize, conceptual framework, crowdsourcing, cryptocurrency, Debian, deskilling, disintermediation, distributed ledger, Ethereum, ethereum blockchain, future of work, gig economy, Google bus, hiring and firing, income inequality, information asymmetry, Internet of things, Jacob Appelbaum, Jeff Bezos, job automation, Julian Assange, Kickstarter, lake wobegon effect, low skilled workers, Lyft, Mark Zuckerberg, means of production, minimum viable product, moral hazard, Network effects, new economy, offshore financial centre, openstreetmap, peer-to-peer, post-work, profit maximization, race to the bottom, ride hailing / ride sharing, SETI@home, shareholder value, sharing economy, Shoshana Zuboff, Silicon Valley, smart cities, smart contracts, Snapchat, TaskRabbit, technoutopianism, transaction costs, Travis Kalanick, Uber for X, uber lyft, union organizing, universal basic income, Whole Earth Catalog, WikiLeaks, women in the workforce, Zipcar

However, to deliver the AI-powered features that near-future users will demand, applications will need to draw upon sophisticated industrial-strength AI software services and harness powerful clusters of data-mining server farms. This stuff doesn’t come cheap. Free, open, and radically decentralized AI isn’t a thing yet, but blockchain-based platforms like Ethereum and Backfeed could offer decentralized alternatives to the corporate cloud. More libre but not gratis, as you’ll pay for decentralization with cryptocurrency. In its infancy, Ethereum is far more expensive than the Amazon cloud but with laughable performance and capability by comparison. Can you afford to wait for the decentralized solution or do you accept that a corporate cloud is presently your only viable high-performance and affordable option? Co-ops require novel legal frameworks.

Put differently, cooperatives tended to focus too much on how the value would be shared rather than on a compelling offer to create the value in the first place. Perhaps part of the solution will come from the possibility, created by blockchain technologies, of “distributed collaborative organizations,” or DCOs—new decentralized collectives that, in the eyes of pioneers like Matan Field of Backfeed and Vitalik Buterin of Ethereum, can use rules embedded in computer code to align the incentives of different contributors, of financial capital, of expertise, of labor, and of participation. These DCOs are connected intellectually to a variety of related decentralized ownership models. They range from the FairShare Model of Karl Sjogren, which proposes a structure of different classes of ownership shares for different contributors—for founders, people with a continuous working role, for users, and for investors—to the Swarm approach to “crypto-equity” crowdfunding developed by Joel Dietz.

We started with an approximately $1 million crowdfunding campaign around our own blockchain-issued asset, the Swarm coin. After much of the funds were exhausted in the process of our own legal research and the coin’s price fluctuations, we financed development through corporate partnerships. At this point we are re-engineering our initial proof of concepts (developed on Bitcoin) to release ready concepts on Ethereum. We are currently building a global ambassador network through training events in various cities across the globe. We are also currently exploring other projects that might bridge to a mainstream audience and serve as a proof of concepts for both the future of governance and community abundance. As with our original concept, we expect new forms of crowdfunding to have a major role in this, especially around blockchain-hosted organizations.


pages: 156 words: 15,746

Personal Finance with Python by Max Humber

asset allocation, backtesting, bitcoin, cryptocurrency, en.wikipedia.org, Ethereum, passive income, web application

Profit Max Humber1 (1)Toronto, Ontario, Canada You know, you got to spend money to make money. —Chief Keef A couple of weeks ago my grandma asked me if she should put some money into Bitcoin. I didn’t know what to tell her. But I knew that in a book about finance I would have to at least give Bitcoin and cryptocurrencies at least a little bit of lip service. For the uninitiated, cryptocurrencies like Bitcoin (and Ethereum, Dogecoin, and Zcash) are digital assets that are designed to function as a medium of exchange and that use cryptography to secure transactions, to control the creation of new money, and to verify asset transfer. Because I think it’s hilarious, I’m going to use Dogecoin1 as the glue for the rest of this chapter. But honestly, these ideas extend beyond Dogecoin (and crypto for that matter). They apply whenever you have to spend money to make money.

With everything now inside of a class, we can instantiate a currency converter with this: API_KEY = os.environ.get("OPX_KEY") c = CurrencyConverter(['CAD', 'USD'], API_KEY) Converting values now just requires us to use the .convert method. print(c.convert(3000, 'CAD', 'USD')) print(c.convert(5000, 'USD', 'CAD')) 2302.35 6515.08 show_alternative The Open Exchange Rates API is incredibly robust, and it actually includes access points for alternative cryptocurrencies. This means that it’s totally legit to instantiate a new CurrencyConverter with ETH (Ethereum), BTC (Bitcoin), and DOGE (Dogecoin) on top of CAD and USD. c = CurrencyConverter(['CAD', 'USD', 'DOGE', 'ETH', 'BTC'], API_KEY) With all the currencies stored inside of a dictionary attached to the CurrencyConverter object: c.rates_ {'BTC': 0.00013350885, 'CAD': 1.303016, 'DOGE': 289.975486957, 'ETH': 0.0017451855, 'USD': 1} we can, again, run the .convert method and find out that $3,000 CAD is equal to the following: c.convert(3000, 'CAD', 'DOGE') 667625.31 .apply The whole point of this chapter was to figure out what the values from previous chapter were in USD instead of CAD.


pages: 579 words: 183,063

Tribe of Mentors: Short Life Advice From the Best in the World by Timothy Ferriss

23andMe, A Pattern Language, agricultural Revolution, Airbnb, Albert Einstein, Bayesian statistics, bitcoin, Black Swan, blockchain, Brownian motion, Buckminster Fuller, Clayton Christensen, cloud computing, cognitive dissonance, Colonization of Mars, corporate social responsibility, cryptocurrency, David Heinemeier Hansson, dematerialisation, don't be evil, double helix, effective altruism, Elon Musk, Ethereum, ethereum blockchain, family office, fear of failure, Gary Taubes, Geoffrey West, Santa Fe Institute, Google Hangouts, Gödel, Escher, Bach, haute couture, helicopter parent, high net worth, In Cold Blood by Truman Capote, income inequality, index fund, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Lao Tzu, Law of Accelerating Returns, Lyft, Mahatma Gandhi, Marc Andreessen, Marshall McLuhan, Mikhail Gorbachev, minimum viable product, move fast and break things, move fast and break things, Naomi Klein, non-fiction novel, Peter Thiel, profit motive, Ralph Waldo Emerson, Ray Kurzweil, Saturday Night Live, side project, Silicon Valley, Skype, smart cities, smart contracts, Snapchat, Steve Jobs, Steven Pinker, Stewart Brand, TaskRabbit, Tesla Model S, too big to fail, Turing machine, uber lyft, web application, Whole Earth Catalog, Y Combinator

–W “I’d rather give an understated good recommendation: be interdisciplinary . . . the interactions between [fields] tend to very often inform strategic and protocol decisions.” Vitalik Buterin TW: @VitalikButerin Reddit: /u/vbuterin VITALIK BUTERIN is the creator of Ethereum. He first discovered blockchain and cryptocurrency technologies through Bitcoin in 2011, and was immediately excited by the technology and its potential. He co-founded Bitcoin magazine in September 2011, and after two and a half years looking at what the existing blockchain technology and applications had to offer, wrote the Ethereum white paper in November 2013. He now leads Ethereum’s research team, working on future versions of the Ethereum protocol. In 2014, Vitalik was a recipient of the two-year Thiel Fellowship, tech billionaire Peter Thiel’s project that awards $100,000 to 20 promising innovators under 20 so they can pursue their inventions in lieu of a post-secondary institution

It’s not super cool, and it’s more about the habit. But I do want to get that culty Japanese journal that all the designers use, a Hobonichi Techo. It’s the kind of thing you see in Japan: a notebook turned into a high art. Maybe next year. . . . “No one is qualified to tell you how you experience the world.” Vlad Zamfir TW: @VladZamfir Medium: @vlad_zamfir vladzamfir.com VLAD ZAMFIR is a blockchain architect and researcher at Ethereum, working on blockchain efficiency and scaling. Vlad is interested in governance and privacy solutions, and he was also the first person to introduce me to absurdism. He is a frequent contributor on Medium and lives in Antarctica (or so he wants us to believe). What is the book (or books) you’ve given most as a gift, and why? Or what are one to three books that have greatly influenced your life?

., 289 EDventure Holdings, 243 Effective Altruism, 300 Efferding, Mark, 318 Efferding, Stan, 318 Egg boxing, 516 Einstein, Albert, 51, 232, 356, 375, 515 Ek, Daniel, 286–88 Eligible, 243 Elizabeth Arden, 87 Ellison, Larry, 446 El Rey Network, 541, 544 Emerson, Ralph Waldo, 21, 123, 178, 253, 528–29 Eminem, 239 Emotional intelligence, 557–58 Endeavor Global, 349–51 Enlightenment Intensive, 343 Enneagram, 456–57 Environmental Institute for Golf, 283 Epicurus, 418 Epinions.com, 31 Epitaph Test, 47, 49 Erwin, Brian, 221 Ethereum, 153, 501 Évora, Cesária, 12 Exercise, 493, 522. See also specific forms, e.g.: CrossFit for basic fitness, 422, 465–66 to improve life, 217, 222, 290, 490 investing in, 497 as investing in yourself, 212–13 outdoors, 98 to refocus, 535 for stress relief, 530, 531 sweating during, 393 F Facebook, 82 Fallon, Jimmy, 175–77 Fame, 149–50 farWord Inc., 79 Fasting, 448 Fatalism, 119–20 Fear, 21, 547–48, 552–53 Fenway Strategies, 353 Ferdowsi, Arash, 456 Festool, 381 Fidgitz, 405 FINIS swim paddles, 59 First Aid Only H5041-AMP Ammonia Inhalant Ampoules, 387 First Look Media, 141 Fischer, Bobby, 186 Fisher, Adam, 428–30 Fitness, 290, 422, 465 The Five-Minute Journal, 306 Five whys, 67–68 Flexibility training, 388 Floodgate, 64, 65, 200 Florenz, Gabriel, 51 Food(s).


pages: 361 words: 97,787

The Curse of Cash by Kenneth S Rogoff

Andrei Shleifer, Asian financial crisis, bank run, Ben Bernanke: helicopter money, Berlin Wall, bitcoin, blockchain, Boris Johnson, Bretton Woods, business cycle, capital controls, Carmen Reinhart, cashless society, central bank independence, cryptocurrency, debt deflation, disruptive innovation, distributed ledger, Edward Snowden, Ethereum, ethereum blockchain, eurozone crisis, Fall of the Berlin Wall, fiat currency, financial exclusion, financial intermediation, financial repression, forward guidance, frictionless, full employment, George Akerlof, German hyperinflation, illegal immigration, inflation targeting, informal economy, interest rate swap, Isaac Newton, Johann Wolfgang von Goethe, Johannes Kepler, Kenneth Rogoff, labor-force participation, large denomination, liquidity trap, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, moveable type in China, New Economic Geography, offshore financial centre, oil shock, open economy, payday loans, price stability, purchasing power parity, quantitative easing, RAND corporation, RFID, savings glut, secular stagnation, seigniorage, The Great Moderation, the payments system, The Rise and Fall of American Growth, transaction costs, unbanked and underbanked, unconventional monetary instruments, underbanked, unorthodox policies, Y2K, yield curve

Because the technology is evolving so rapidly, I am hesitant to go into much more detail, beyond saying that phasing out paper currency does not really move the needle much on society’s vulnerability to cybercrime. Some of the present-day obstacles to improving security are really more political than economic. Some innovations in security, such as the potentially disruptive distributed-ledger technology embodied in cryptocurrencies like Bitcoin or Ethereum, may eventually lead to major improvements in financial security, at least at the core of the payment system, as discussed further in chapter 14. It is particularly hard to see in any of these arguments why large-denomination notes are important. Probably they would be looked on askance after a power outage, earthquake, or other kind of catastrophe. I won’t deny there are going to be residual issues that simply take time to sort out.

Already, digital currencies are far cheaper for transmitting money internationally than wire services, where the charges can often run as much as 10–15% of the amount transmitted. And some applications of distributed-ledger technology offer the promise of cutting out intermediaries in transactions between, say, two banks. This would substantially reduce costs, particularly in international transactions. The approach can also be used to save on legal contracting costs. Some of Bitcoin’s competitors, notably the newer Ethereum platform, aim to offer the possibility of creating secure exchanges for transactions of almost any type. People sometimes ask whether the cryptocurrency Bitcoin could be a currency (supposing that the government does not interfere). The answer is certainly yes, Bitcoin (or perhaps one of its present or future competitors) can fulfill many of the basic functions of currency, including unit of account and medium of exchange, with or without government adherence.3 In fact, digital currencies in some ways offer the capacity for much more complex kinds of transactions and contracts than traditional paper currency offers, precisely because the former embed so much information, including the history of transactions.

The answer is certainly yes, Bitcoin (or perhaps one of its present or future competitors) can fulfill many of the basic functions of currency, including unit of account and medium of exchange, with or without government adherence.3 In fact, digital currencies in some ways offer the capacity for much more complex kinds of transactions and contracts than traditional paper currency offers, precisely because the former embed so much information, including the history of transactions. Already, markets are forming to exploit this capacity, for example, in applications surrounding Ethereum.4 That distributed-ledger technology could in theory someday produce a superior currency, however, hardly means that the world is already there in practice. One problem is that the value of Bitcoin 1.0 fluctuates wildly (figure 14.1), so it hardly fulfills the function of a stable store of value. In principle, it could become more stable if it gained more widespread monetary acceptance. Figure 14.2 shows that the price of gold in terms of dollars was much more stable under the gold standard, even in real (purchasing-power) terms.


pages: 463 words: 105,197

Radical Markets: Uprooting Capitalism and Democracy for a Just Society by Eric Posner, E. Weyl

3D printing, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, anti-communist, augmented reality, basic income, Berlin Wall, Bernie Sanders, Branko Milanovic, business process, buy and hold, carbon footprint, Cass Sunstein, Clayton Christensen, cloud computing, collective bargaining, commoditize, Corn Laws, corporate governance, crowdsourcing, cryptocurrency, Donald Trump, Elon Musk, endowment effect, Erik Brynjolfsson, Ethereum, feminist movement, financial deregulation, Francis Fukuyama: the end of history, full employment, George Akerlof, global supply chain, guest worker program, hydraulic fracturing, Hyperloop, illegal immigration, immigration reform, income inequality, income per capita, index fund, informal economy, information asymmetry, invisible hand, Jane Jacobs, Jaron Lanier, Jean Tirole, Joseph Schumpeter, Kenneth Arrow, labor-force participation, laissez-faire capitalism, Landlord’s Game, liberal capitalism, low skilled workers, Lyft, market bubble, market design, market friction, market fundamentalism, mass immigration, negative equity, Network effects, obamacare, offshore financial centre, open borders, Pareto efficiency, passive investing, patent troll, Paul Samuelson, performance metric, plutocrats, Plutocrats, pre–internet, random walk, randomized controlled trial, Ray Kurzweil, recommendation engine, rent-seeking, Richard Thaler, ride hailing / ride sharing, risk tolerance, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, Rory Sutherland, Second Machine Age, second-price auction, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, special economic zone, spectrum auction, speech recognition, statistical model, stem cell, telepresence, Thales and the olive presses, Thales of Miletus, The Death and Life of Great American Cities, The Future of Employment, The Market for Lemons, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thorstein Veblen, trade route, transaction costs, trickle-down economics, Uber and Lyft, uber lyft, universal basic income, urban planning, Vanguard fund, women in the workforce, Zipcar

Alisha Holland, Square Miles: The Spatial Politics of Mass Infrastructure, American Political Science Association Working Paper, 2017. 46. Liran Einav, Chiara Farronato, & Jonathan Levin, Peer-to-Peer Markets, 8 Annual Review of Economics 615 (2016). 47. Chris Nosko & Steven Tadelis, The Limits of Reputation in Platform Markets: An Empirical Analysis and Field Experiment (National Bureau of Economic Research, Working Paper No. 20830, 2015). 48. Andrew Quentson, Can Ethereum-Based Akasha Revolutionize Social Networks? Cryptocoins News, January 29, 2017, https://www.cryptocoinsnews.com/can-ethereum-based-akasha-revolutionize-social-networks/. 49. See Eric A. Posner & E. Glen Weyl, Quadratic Voting as Efficient Corporate Governance, 81 University of Chicago Law Review 251 (2014), for more on the application to corporate governance. 50. For a more detailed elaboration of these ideas, see Eric A. Posner & E. Glen Weyl, Voting Squared: Quadratic Voting in Democratic Politics, 68 Vanderbilt Law Review 441 (2015); Eric A.

The cost of votes pro and con would grow quadratically and participants could save their credits for future interactions or use saved credits for those about which they feel more strongly at present. Such a system combines the best of both tipping and rating, creating a real cost to expressing enthusiasm, but also discouraging free-riding and allowing other participants to benefit from the feedback. A version of this system is being implemented by a social network called Akasha, based on the increasingly prominent Ethereum cryptocurrency.48 QV fits with the framework of cryptocurrencies, which require formal governance rules to allow for the decentralized management they rely on, so using it also for social aggregation in such a context is natural. However, the exact implementation is unclear at the time of this writing, and not available to the public; much in the world of cryptocurrencies is secretive. However, we hope that broader use of QV in these contexts will provide a more powerful test than political polling of how QV would work if adopted in social settings where norms and values would adapt to its use.

., 78 Cabral, Luís, 202 Cadappster app, 31 Caesar, Julius, 84 Canada, 10, 13, 159, 182 capitalism, xvi; basic structure of, 24–25; competition and, 17 (see also competition); corporate planning and, 39–40; cultural consequences of, 270, 273; Engels on, 239–40; freedom and, 34–39; George on, 36–37; growth and, 3 (see also growth, economic); industrial revolution, 36, 255; inequality and, 3 (see also inequality); labor and, 136–37, 143, 159, 165, 211, 224, 231, 239–40, 316n4; laissez-faire, 45; liberalism and, 3, 17, 22–27; markets and, 278, 288, 304n36; Marx on, 239–40; monopolies and, 22–23, 34–39, 44, 46–49, 132, 136, 173, 177, 179, 199, 258, 262; monopsony and, 190, 199–201, 223, 234, 238–41, 255; ownership and, 34–36, 39, 45–49, 75, 78–79; property and, 34–36, 39, 45–49, 75, 78–79; Radical Markets and, 169, 180–85, 203, 273; regulations and, 262; Schumpeter on, 47; shareholders and, 118, 170, 178–84, 189, 193–95; technology and, 34, 203, 316n4; wealth and, 45, 75, 78–79, 136, 143, 239, 273 Capitalism and Freedom (Friedman), xiii Capitalism for the People, A (Luigi), 203 Capra, Frank, 17 Carroll, Lewis, 176 central planning: computers and, 277–85, 288–93; consumers and, 19; democracy and, 89; governance and, 19–20, 39–42, 46–48, 62, 89, 277–85, 288–90, 293; healthcare and, 290–91; liberalism and, 19–20; markets and, 277–85, 288–93; property and, 39–42, 46–48, 62; recommendation systems and, 289–90; socialism and, 39–42, 47, 277, 281 Chetty, Raj, 11 Chiang Kai-shek, 46 China, 15, 46, 56, 133–34, 138 Christensen, Clayton, 202 Chrysler, 193 Citigroup, 183, 184, 191 Clarke, Edward, 99, 102, 105 Clayton Act, 176–77, 197, 311n25 Clemens, Michael, 162 Coase, Ronald, 40, 48–51, 299n26 Cold War, xix, 25, 288 collective bargaining, 240–41 collective decisions: democracy and, 97–105, 110–11, 118–20, 122, 124, 273, 303n17, 304n36; manipulation of, 99; markets for, 97–105; public goods and, 98; Quadratic Voting (QV) and, 110–11, 118–20, 122, 124, 273, 303n17, 304n36; Vickrey and, 99, 102, 105 colonialism, 8, 131 Coming of the Third Reich, The (Evans), 93 common ownership self-assessed tax (COST): broader application of, 273–76; cybersquatters and, 72; education and, 258–59; efficiency and, 256, 261; equality and, 258; globalization and, 269–70; growth and, 73, 256; human capital and, 258–61; immigrants and, 261, 269, 273; inequality and, 256–59; international trade and, 270; investment and, 258–59, 270; legal issues and, 275; markets and, 286; methodology of, 63–66; monopolies and, 256–61, 270, 300n43; objections to, 300n43; optimality and, 61, 73, 75–79, 317n18; personal possessions and, 301n47, 317n18; political effects of, 261–64; predatory outsiders and, 300n43; prices and, 62–63, 67–77, 256, 258, 263, 275, 300n43, 317n18; property and, 31, 61–79, 271–74, 300n43, 301n47; public goods and, 256; public leases and, 69–72; Quadratic Voting (QV) and, 123–25, 194, 261–63, 273, 275, 286; Radical Markets and, 79, 123–26, 257–58, 271–72, 286; taxes and, 61–69, 73–76, 258–61, 275, 317n18; technology and, 71–72, 257–59; true market economy and, 72–75; voting and, 263; wealth and, 256–57, 261–64, 269–70, 275, 286 communism, 19–20, 46–47, 93–94, 125, 278 competition: antitrust policies and, 23, 48, 174–77, 180, 184–86, 191, 197–203, 242, 255, 262, 286; auctions and, xv–xix, 49–51, 70–71, 97, 99, 147–49, 156–57; bargaining and, 240–41, 299n26; democracy and, 109, 119–20; by design, 49–55; elitism and, 25–28; equilibrium and, 305n40; eternal vigilance and, 204; horizontal concentration and, 175; imperfect, 304n36; indexing and, 185–91, 302n63; innovation and, 202–3; investment and, 196–97; labor and, 145, 158, 162–63, 220, 234, 236, 239, 243, 245, 256, 266; laissez-faire and, 253; liberalism and, 6, 17, 20–28; lobbyists and, 262; monopolies and, 174; monopsony and, 190, 199–201, 223, 234, 238–41, 255; ownership and, 20–21, 41, 49–55, 79; perfect, 6, 25–28, 109; prices and, 20–22, 25, 173, 175, 180, 185–90, 193, 200–201, 204, 244; property and, 41, 49–55, 79; Quadratic Voting (QV) and, 304n36; regulations and, 262; resale price maintenance and, 200–201; restoring, 191–92; Section 7 and, 196–97, 311n25; selfishness and, 109, 270–71; Smith on, 17; tragedy of the commons and, 44 complexity, 218–20, 226–28, 274–75, 279, 281, 284, 287, 313n15 “Computer and the Market, The” (Lange), 277 computers: algorithms and, 208, 214, 219, 221, 281–82, 289–93; automation of labor and, 222–23, 251, 254; central planning and, 277–85, 288–93; data and, 213–14, 218, 222, 233, 244, 260; Deep Blue, 213; distributed computing and, 282–86, 293; growth in poor countries and, 255; as intermediaries, 274; machine learning (ML) and, 214 (see also machine learning [ML]); markets and, 277, 280–93; Mises and, 281; Moore’s Law and, 286–87; Open-Trac and, 31–32; parallel processing and, 282–86; prices of, 21; recommendation systems and, 289–90 Condorcet, Marquis de, 4, 90–93, 303n15, 306n51 conspicuous consumption, 78 Consumer Reports magazine, 291 consumers: antitrust suits and, 175, 197–98; central planning and, 19; data from, 47, 220, 238, 242–44, 248, 289; drone delivery to, 220; as entrepreneurs, 256; goods and services for, 27, 92, 123, 130, 175, 280, 292; institutional investment and, 190–91; international culture for, 270; lobbyists and, 262; machine learning (ML) and, 238; monopolies and, 175, 186, 197–98; preferences of, 280, 288–93; prices and, 172 (see also prices); recommendation systems and, 289–90; robots and, 287; sharing economy and, 117; Soviet collapse and, 289; technology and, 287 cooperatives, 118, 126, 261, 267, 299n24 Corbyn, Jeremy, 12, 13 corruption, 3, 23, 27, 57, 93, 122, 126, 157, 262 Cortana, 219 cost-benefit analysis, 2, 244 “Counterspeculation, Auctions and Competitive Sealed Tenders” (Vickrey), xx–xxi Cramton, Peter, 52, 54–55, 57 crowdsourcing, 235 crytocurrencies, 117–18 cybersquatters, 72 data: algorithms and, 208, 214, 219, 221, 281–82, 289–93; big, 213, 226, 293; computers and, 213–14, 218, 222, 233, 244, 260; consumer, 47, 220, 238, 242–44, 248, 289; diamond-water paradox and, 224–25; diminishing returns and, 226, 229–30; distribution of complexity and, 228; as entertainment, 233–39, 248–49; Facebook and, 28, 205–9, 212–13, 220–21, 231–48; feedback and, 114, 117, 233, 238, 245; free, 209, 211, 220, 224, 231–35, 239; Google and, 28, 202, 207–13, 219–20, 224, 231–36, 241–42, 246; investment in, 212, 224, 232, 244; labeled, 217–21, 227, 228, 230, 232, 234, 237; labor movement for, 241–43; Lanier and, 208, 220–24, 233, 237, 313n2, 315n48; marginal value and, 224–28, 247; network effects and, 211, 236, 238, 243; neural networks and, 214–19; online services and, 211, 235; overfitting and, 217–18; payment systems for, 210–13, 224–30; photographs and, 64, 214–15, 217, 219–21, 227–28, 291; programmers and, 163, 208–9, 214, 217, 219, 224; Radical Markets for, 246–49; reCAPTCHA and, 235–36; recommendation systems and, 289–90; rise of data work and, 209–13; sample complexity and, 217–18; siren servers and, 220–24, 230–41, 243; social networks and, 202, 212, 231, 233–36; technofeudalism and, 230–33; under-employment and, 256; value of, 243–45; venture capital and, 211, 224; virtual reality and, 206, 208, 229, 251, 253; women’s work and, 209, 313n4 Declaration of Independence, 86 Deep Blue, 213 DeFoe, Daniel, 132 Demanding Work (Gray and Suri), 233 democracy: 1p1v system and, 82–84, 94, 109, 119, 122–24, 304n36, 306n51; artificial intelligence (AI) and, 219; Athenians and, 55, 83–84, 131; auctions and, 97, 99; basic structure of, 24–25; central planning and, 89; check and balance systems and, 23, 25, 87, 92; collective decisions and, 97–105, 110–11, 118–20, 122, 124, 273, 303n17, 304n36; collective mediocrity and, 96; competition and, 109, 119–20; Declaration of Independence and, 86; efficiency and, 92, 110, 126; elections and, 22, 80, 93, 100, 115, 119–21, 124, 217–18, 296n20; elitism and, 89–91, 96, 124; Enlightenment and, 86, 95; Europe and, 90–96; France and, 90–95; governance and, 84, 117; gridlock and, 84, 88, 122–24, 261, 267; Hitler and, 93–94; House of Commons and, 84–85; House of Lords and, 85; impossibility theorem and, 92; inequality and, 123; Jury Theorem and, 90–92; liberalism and, 3–4, 25, 80, 86, 90; limits of, 85–86; majority rule and, 27, 83–89, 92–97, 100–101, 121, 306n51; markets and, 97–105, 262, 276; minorities and, 85–90, 93–97, 101, 106, 110; mixed constitution and, 84–85; multi-candidate, single-winner elections and, 119–20; origins of, 83–85; ownership and, 81–82, 89, 101, 105, 118, 124; public goods and, 28, 97–100, 107, 110, 120, 123, 126; Quadratic Voting (QV) and, 105–22; Radical Markets and, 82, 106, 123–26, 203; supermajorities and, 84–85, 88, 92; tyrannies and, 23, 25, 88, 96–100, 106, 108; United Kingdom and, 95–96; United States and, 86–90, 93, 95; voting and, 80–82, 85–93, 96, 99, 105, 108, 115–16, 119–20, 123–24, 303n14, 303n17, 303n20, 304n36, 305n39; wealth and, 83–84, 87, 95, 116 Demosthenes, 55 Denmark, 182 Department of Justice (DOJ), 176, 186, 191 deregulation, 3, 9, 24 Desmond, Matthew, 201–2 Dewey, John, 43 Dickens, Charles, 36 digital economy: data producers and, 208–9, 230–31; diamond-water paradox and, 224–25; as entertainment, 233–39; facial recognition and, 208, 216, 218–19; free access and, 211; Lanier and, 208, 220–24, 233, 237, 313n2, 315n48; machine learning (ML) and, 208–9, 213–14, 217–21, 226–31, 234–35, 238, 247, 289, 291, 315n48; payment systems for, 210–13, 221–30, 243–45; programmers and, 163, 208–9, 214, 217, 219, 224; rise of data work and, 209–13; siren servers and, 220–24, 230–41, 243; spam and, 210, 245; technofeudalism and, 230–33; virtual reality and, 206, 208, 229, 251, 253 diversification, 171–72, 180–81, 185, 191–92, 194–96, 310n22, 310n24 dot-com bubble, 211 double taxation, 65 Dupuit, Jules, 173 Durkheim, Émile, 297n23 Dworkin, Ronald, 305n40 dystopia, 18, 191, 273, 293 education, 114; common ownership self-assessed tax (COST) and, 258; data and, 229, 232, 248; elitism and, 260; equality in, 89; financing, 276; free compulsory, 23; immigrants and, 14, 143–44, 148; labor and, 140, 143–44, 148, 150, 158, 170–71, 232, 248, 258–60; Mill on, 96; populist movements and, 14; Stolper-Samuelson Theorem and, 143 efficient capital markets hypothesis, 180 elections, 80; data and, 217–18; democracy and, 22, 93, 100, 115, 119–21, 124, 217–18, 296n20; gridlock and, 124; Hitler and, 93; multi-candidate, single-winner, 119–20; polls and, 13, 111; Quadratic Voting (QV) and, 115, 119–21, 268, 306n52; U.S. 2016, 93, 296n20 Elhauge, Einer, 176, 197 elitism: aristocracy and, 16–17, 22–23, 36–38, 84–85, 87, 90, 135–36; bourgeoisie and, 36; bureaucrats and, 267; democracy and, 89–91, 96, 124; education and, 260; feudalism and, 16, 34–35, 37, 41, 61, 68, 136, 230–33, 239; financial deregulation and, 3; immigrants and, 146, 166; liberalism and, 3, 15–16, 25–28; minorities and, 12, 14–15, 19, 23–27, 85–90, 93–97, 101, 106, 110, 181, 194, 273, 303n14, 304n36; monarchies and, 85–86, 91, 95, 160 Emergency Economic Stabilization Act, 121 eminent domain, 33, 62, 89 Empire State Building, 45 Engels, Friedrich, 78, 240 Enlightenment, 86, 95 entrepreneurs, xiv; immigrants and, 144–45, 159, 256; labor and, 129, 144–45, 159, 173, 177, 203, 209–12, 224, 226, 256; ownership and, 35, 39 equality: common ownership self-assessed tax (COST) and, 258; education and, 89; immigrants and, 257; labor and, 147, 166, 239, 257; liberalism and, 4, 8, 24, 29; living standards and, 3, 11, 13, 133, 135, 148, 153, 254, 257; Quadratic Voting (QV) and, 264; Radical Markets and, 262, 276; trickle down theories and, 9, 12 Espinosa, Alejandro, 30–32 Ethereum, 117 Europe, 177, 201; democracy and, 88, 90–95; European Union and, 15; fiefdoms in, 34; government utilities and, 48; income patterns in, 5; instability in, 88; labor and, 11, 130–31, 136–47, 165, 245; social democrats and, 24; unemployment rates in, 11 Evans, Richard, 93 Evicted (Desmond), 201–2 Ex Machina (film), 208 Facebook, xxi; advertising and, 50, 202; data and, 28, 205–9, 212–13, 220–21, 231–48; monetization by, 28; news service of, 289; Vickrey Commons and, 50 facial recognition, 208, 216–19 family reunification programs, 150, 152 farms, 17, 34–35, 37–38, 61, 72, 135, 142, 179, 283–85 Federal Communications Commission (FCC), 50, 71 Federal Trade Commission (FTC), 176, 186 feedback, 114, 117, 233, 238, 245 feudalism, 16, 34–35, 37, 41, 61, 68, 136, 230–33, 239 Fidelity, 171, 181–82, 184 financial crisis of 2008, 3, 121 Fitzgerald, F.


pages: 302 words: 95,965

How to Be the Startup Hero: A Guide and Textbook for Entrepreneurs and Aspiring Entrepreneurs by Tim Draper

3D printing, Airbnb, Apple's 1984 Super Bowl advert, augmented reality, autonomous vehicles, basic income, Berlin Wall, bitcoin, blockchain, Buckminster Fuller, business climate, carried interest, connected car, crowdsourcing, cryptocurrency, Deng Xiaoping, discounted cash flows, disintermediation, Donald Trump, Elon Musk, Ethereum, ethereum blockchain, family office, fiat currency, frictionless, frictionless market, high net worth, hiring and firing, Jeff Bezos, Kickstarter, low earth orbit, Lyft, Mahatma Gandhi, Mark Zuckerberg, Menlo Park, Metcalfe's law, Metcalfe’s law, Mikhail Gorbachev, Minecraft, Moneyball by Michael Lewis explains big data, Nelson Mandela, Network effects, peer-to-peer, Peter Thiel, pez dispenser, Ralph Waldo Emerson, risk tolerance, Robert Metcalfe, Ronald Reagan, Rosa Parks, Sand Hill Road, school choice, school vouchers, self-driving car, sharing economy, short selling, Silicon Valley, Skype, smart contracts, Snapchat, sovereign wealth fund, stealth mode startup, stem cell, Steve Jobs, Tesla Model S, Uber for X, uber lyft, universal basic income, women in the workforce, Y Combinator, zero-sum game

People discovered that the blockchain could be used to raise funds for projects and startups. In effect, people found that they could create their own currencies using Bitcoin as a model. These would be known as decentralized autonomous organizations (DAOs). The first of these, DAO Maker, had an inauspicious beginning. The company used Ethereum (a decentralized currency built using a protocol similar to the Bitcoin blockchain) as its platform. A hacker figured out that when money was moving from one entity to another, they could siphon off the Ethereum currency, called Ether, collected from the sale of the tokens. The hacker managed to steal 3.6 million Ether (at the time valued around $72 million) and the price of Ether dropped from $20 to about $13. DAO offerings came to an abrupt end. But then more people saw potential in these offerings.

Industries transformed by the Internet: Information (Google), Shopping (Amazon), Communications (Skype), Entertainment (Netflix), Media (iTunes), Gaming (Minecraft), Community (Facebook) Industries transformed by the marketplace: Transportation (Uber), Hotels (Airbnb), Startups (AngelList), Workforce (Thumbtack), Lawyers (LawTrades), PR (PRx), Brokerage (Robinhood), Interior Decorating (Laurel and Wolf), Stock Market (Equidate, EquityZen), Cap Tables (eShares, Capshare), Gaming (Twitch) Industries transformed by Bitcoin: Currencies (Bitcoin), Government (Tezos), Contracts (Ethereum), Banking (Ripple), Real Estate (BenBen), Insurance (Augur), Finance (Bancor) Industries transformed by AI: Automotive (Cruise Automation), Identity (Neurala) In addition to the industries and transformations listed above, VR/AR promise to challenge education, drones will likely challenge surveillance, and Tesla will challenge utilities Understanding Trends It can also be a good exercise to study trends in and around your industry.


pages: 237 words: 66,545

The Money Tree: A Story About Finding the Fortune in Your Own Backyard by Chris Guillebeau

"side hustle", Bernie Madoff, Ethereum, financial independence, global village, hiring and firing, housing crisis, passive income, race to the bottom, rent-seeking, ride hailing / ride sharing, Steve Jobs, telemarketer

* * * — Breaking: Controversial Decision-Making Service Under Attack Reuters Newswire — Sources indicate a new service that advises users on their decisions has been hacked. More than 250,000 users have allowed the service to access their personal information, including email and financial accounts. There is no word yet as to whether those accounts are at risk. This is a developing story and will be updated. * * * — From: KQuanChangi97@robomail.com To: lolzhackbuzz@hushmail.com What is Ethereum? And why would I pay you $100,000? Who are you? * * * — But What Could Possibly Go Wrong? By Katlyn Everett Valley News Pop quiz time again! Who plays with fire and acts surprised when their house burns down? Ding ding! You guessed it . . . Buzzard Co., that’s who. The popular “do no good” startup is shocked that they would be a target for hackers. They are horrified at such maliciousness.

While I would not be surprised if this emerged as its new logo, for now it seems to be an action taken by the hackers. There’s a good reason why messages that delete themselves upon being viewed are so popular. Stay tuned for updates on the house burning. I’m running out to get popcorn. * * * — From: KQuanChangi97@robomail.com To: Finance How do I transfer a large amount of money? And do you know what Ethereum is?? * * * — UPDATED: Decision-Making Service Resolves Attempted Hacking Reuters Newswire — The concern that hackers had gained control of a startup’s full set of user accounts turned into a false alarm. Users breathed a sigh of relief as experts learned that only the service’s home page and founder’s email account had been compromised. He regained access after paying the hackers an undisclosed sum in the form of a ransom payment.


pages: 290 words: 72,046

5 Day Weekend: Freedom to Make Your Life and Work Rich With Purpose by Nik Halik, Garrett B. Gunderson

Airbnb, bitcoin, Buckminster Fuller, business process, clean water, collaborative consumption, cryptocurrency, delayed gratification, diversified portfolio, en.wikipedia.org, estate planning, Ethereum, fear of failure, fiat currency, financial independence, glass ceiling, Grace Hopper, Home mortgage interest deduction, Isaac Newton, litecoin, Lyft, market fundamentalism, microcredit, minimum viable product, mortgage debt, mortgage tax deduction, Nelson Mandela, passive income, peer-to-peer, peer-to-peer rental, Ponzi scheme, quantitative easing, Ralph Waldo Emerson, ride hailing / ride sharing, sharing economy, side project, Skype, TaskRabbit, traveling salesman, uber lyft

They regulate themselves and are governed by the laws of mathematics. Cryptocurrencies make it easier to transfer funds between two parties in a transaction, and with minimal processing fees compared to the steep fees charged by most financial institutions. The adoption rate of cryptocurrencies is increasing daily with banks, corporations, and governments recognizing its mainstream popularity. The current leading cryptocurrencies are Bitcoin, Ethereum, Litecoin, Monero, Dash, and Ripple. A popular way to buy and sell cryptocurrencies and create your own digital currency “wallet” is to use a platform like Coinbase.com or Bittrex.com. Speculative investors should be aware there are risks involved in the investment and use of cryptocurrencies, such as fraud and security of the platforms. Cryptocurrencies can be electronically stolen, and there is no recourse for the individual.

Harv Elder, Larry email, and productivity rituals emergency preparedness, as protective expense Emerson, Ralph Waldo emotional attachment, and Momentum investments and real estate investments emotional energy energy, amplifying entertainment, as tax deduction entrepreneurship, and academic systems and active income analyzing income opportunities and cash flow and continuous improvement direct sales/network marketing opportunities domain trading opportunities e-commerce opportunities and embracing failure and experimentation fix and flip opportunities and freedom and Growth investments and hiring employees and income growth lack of resources for and letting go and leverage online opportunities and opportunities presented by technology and passion and perfectionism personal service opportunities and quick adjustments to feedback and quitting your job and risk and scalability of businesses and self-employment sharing economy opportunities starting small and strong mindset three levels of and value creation equity growth, and real estate investments estate planning, as protective expense Ethereum Evans, Richard Paul excellence, replacing perfectionism with exercise, and energy amplification exit strategies, for Growth investments for real estate investments expense ratios expenses, and Active Income Ratio cutting and Passive Income Ratio experimentation F Facebook failure, and productivity fear, and building your inner circle and economic cycles and entrepreneurship and opportunity and procrastination and purpose and real estate investments and the Rockefeller Formula and security and strengthening your mindset of taxes federal government assistance, and loans for real estate investments Federal Housing Administration (FHA) feelings of entrapment, and weekend/workweek structure financial capital, and entrepreneurship financial independence, and Passive Income Ratio financial wealth, and Passive Income Ratio 5 Day Weekend, changing your mindset toward work contract for creating a vision for free-time activities five steps of importance of following correct sequence and “mailbox money” myth manifesto and passive vs. active income streams and security vs. freedom and thinking outside the box universal availability of weekend/workweek paradigm 5DayWeekend.com, and Passport codes 5-Second Rule, for impulse buying Fiverr.com fix and flip opportunities fix-up costs, for real estate investments Fon Ford, Henry foreclosure, and tax lien certificates Forleo, Marie foundation step (keep more money) Francis of Assisi (saint) Frank, Ben Frank, Joyce Franklin, Benjamin fraud, and cryptocurrencies freedom, and active vs. passive income creation and boredom and entrepreneurship and generosity and learning when to say no and lifestyle and peace and perfectionism and purpose sacrificing for security and simplicity Freedom Lifestyle freelancing, as entrepreneurial opportunity frequency of work requirements, business ownership (not managing) business ownership (working and managing) royalties and overrides sales subscriptions wage or salary employment Frost, Robert fulfillment, and purpose Fuller, Buckminster G Gardner, Chris generosity Gerber, Michael Gibbs, Marshall goal setting, and Passive Income Ratio and purpose Godin, Seth gold, as Momentum investment opportunity Golightly, Craig Google government social welfare programs, and retirement Grameen Bank gratitude Graybiel, Ann Gretzky, Wayne Groupon Growth investments, and active vs. passive income streams aggressive and conservative strategies for Bank Strategy and cash flow description of and economic cycles for funding Momentum investments minimum criteria for opportunities for Sharelord Strategy storage units tax lien certificates Guitar Institute of Technology (GIT) Gunderson, Garrett H habits, fortifying Halik, Nik happiness, and generosity and materialism hard money lenders, and loans for real estate investments health, and habits health savings accounts (HSA) “HELL YEAH” philosophy Hendrix, Jimi Herodotus Hicks, Bill hidden fees Hill, Napoleon hiring employees hiring your children, as tax deduction hobbies Holland, Danny home expenses, as tax deduction home office deductions homeowner’s insurance Hopper, Grace Hori, Jim hugedomains.com Hulu HyreCar.com I Idea Optimizer impulse buying income, and Active Income Ratio increasing with entrepreneurship and Passive Income Ratio See also cash flow income growth step (make more money) Income Opportunity Score Sheet incorporation Industrial Revolution, vs.


pages: 1,136 words: 73,489

Working in Public: The Making and Maintenance of Open Source Software by Nadia Eghbal

Amazon Web Services, barriers to entry, Benevolent Dictator For Life (BDFL), bitcoin, Clayton Christensen, cloud computing, commoditize, continuous integration, crowdsourcing, cryptocurrency, David Heinemeier Hansson, death of newspapers, Debian, disruptive innovation, en.wikipedia.org, Ethereum, Firefox, Guido van Rossum, Hacker Ethic, Induced demand, informal economy, Jane Jacobs, Jean Tirole, Kevin Kelly, Kickstarter, Kubernetes, Mark Zuckerberg, Menlo Park, Network effects, node package manager, Norbert Wiener, pirate software, pull request, RFC: Request For Comment, Richard Stallman, Ronald Coase, Ruby on Rails, side project, Silicon Valley, Snapchat, social graph, software as a service, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, The Death and Life of Great American Cities, The Nature of the Firm, transaction costs, two-sided market, urban planning, web application, wikimedia commons, Zimmermann PGP

But JavaScript, including Node.js, is designed to be modular, where each maintainer has a limited ability to affect other components of the ecosystem, so JavaScript developers are more likely to prioritize moving fast and accepting contributions. In cryptocurrency, these philosophies play out as visible differences in how the Bitcoin and Ethereum projects are managed. Bitcoin’s community, like Clojure’s, prioritizes stability and security, preferring to move slowly and with care, even if it means including fewer features and contributors. Ethereum is more like Node.js: it’s a platform for others to develop on, flinging itself far and wide. It resembles a sprawling city like Los Angeles, comprised of many neighborhoods and subcultures. Despite impassioned rants to the contrary (if there’s one thing I’ve learned, it’s that developers have opinions), there’s no one right way of doing things, just different communities that each have their own cultural norms.


pages: 309 words: 81,975

Brave New Work: Are You Ready to Reinvent Your Organization? by Aaron Dignan

"side hustle", activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, bitcoin, Black Swan, blockchain, Buckminster Fuller, Burning Man, butterfly effect, cashless society, Clayton Christensen, clean water, cognitive bias, cognitive dissonance, corporate governance, corporate social responsibility, correlation does not imply causation, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, David Heinemeier Hansson, deliberate practice, DevOps, disruptive innovation, don't be evil, Elon Musk, endowment effect, Ethereum, ethereum blockchain, Frederick Winslow Taylor, future of work, gender pay gap, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, hiring and firing, hive mind, income inequality, information asymmetry, Internet of things, Jeff Bezos, job satisfaction, Kevin Kelly, Kickstarter, Lean Startup, loose coupling, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, minimum viable product, new economy, Paul Graham, race to the bottom, remote working, Richard Thaler, shareholder value, Silicon Valley, six sigma, smart contracts, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, source of truth, Stanford marshmallow experiment, Steve Jobs, TaskRabbit, the High Line, too big to fail, Toyota Production System, uber lyft, universal basic income, Y Combinator, zero-sum game

“Imagine a vending machine that not only takes money from you and gives you a snack in return but also uses that money to automatically re-order the goods. This machine also orders cleaning services and pays its rent all by itself. Moreover, as you put money into that machine, you and its other users have a say in what snacks it will order and how often it should be cleaned. It has no managers, all of those processes were pre-written into code.” Developers, leveraging what they have learned in creating cryptocurrencies such as Bitcoin and Ethereum, are pioneering a new generation of decentralized applications that allow organizations to operate like that magical vending machine. Through a series of rules called smart contracts, founders can create, fund, and operate an entire organization independent of hierarchical management. Everything, from paying contributors for their work to making decisions about investment, is managed in a distributed way.

known as the Rochdale Principles: “The Rochdale Principles,” Co-operative Heritage Trust, accessed September 1, 2018, www.rochdalepioneersmuseum.coop/about-us/the-rochdale-principles. one study of cooperatives: Virginie Pérotin, “What Do We Really Know About Worker Co-operatives?” Co-operatives UK, no date, www.uk.coop/resources/what-do-we-really-know-about-worker-co-operatives. “pre-written into code”: “What Is DAO,” Cointelegraph, accessed July 31,2016, https://cointelegraph.com/ethereum-for-beginners/what-is-dao#how-daos-work. becomes valuable when it moves: Charles Eisenstein, Sacred Economics: Money, Gift, and Society in the Age of Transition (Berkeley, CA: North Atlantic Books, 2011). producer/philanthropist Jeff Skoll: “A New Global Impact Fund,” The Rise Fund, accessed September 1, 2018, http://therisefund.com. $390 million Double Impact Fund: “Scaling Mission-Driven Companies,” Bain Capital Double Impact, accessed September 1, 2018, www.baincapitaldoubleimpact.com.


pages: 390 words: 109,870

Radicals Chasing Utopia: Inside the Rogue Movements Trying to Change the World by Jamie Bartlett

Andrew Keen, back-to-the-land, Bernie Sanders, bitcoin, blockchain, blue-collar work, Boris Johnson, brain emulation, centre right, clean water, cryptocurrency, Donald Trump, drone strike, Elon Musk, energy security, Ethereum, ethereum blockchain, failed state, gig economy, hydraulic fracturing, income inequality, Intergovernmental Panel on Climate Change (IPCC), Jaron Lanier, job automation, John Markoff, Joseph Schumpeter, Kickstarter, life extension, Occupy movement, off grid, Peter Thiel, post-industrial society, postnationalism / post nation state, precariat, QR code, Ray Kurzweil, RFID, Rosa Parks, Ross Ulbricht, Satoshi Nakamoto, self-driving car, Silicon Valley, Silicon Valley startup, Skype, smart contracts, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, technoutopianism

Ninety-nine per cent voted in favour, and the UN unanimously recognised the new country. * Bitcoins can be divided into eight decimal places. The smallest non-divisible unit is known as a ‘Satoshi’. * In 2015 a company called the DAO (decentralised autonomous organisation) was founded as an investor-directed capital fund, which exists only virtually, as a series of public smart contracts. Investors can buy shares in the DAO using Ethereum’s (another blockchain) currency, which gives votes on investments. Anyone anywhere in the world can invest, it’s all transparent, there is no board or employees at all, and shareholders receive any profits directly. One month after it was launched to great fanfare, hackers and/or investors managed to exploit a vulnerability by inserting some code that redirected shares into their personal wallets, allowing them to walk off with millions of dollars of investors’ money.


pages: 501 words: 114,888

The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives by Peter H. Diamandis, Steven Kotler

Ada Lovelace, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, blood diamonds, Burning Man, call centre, cashless society, Charles Lindbergh, Clayton Christensen, clean water, cloud computing, Colonization of Mars, computer vision, creative destruction, crowdsourcing, cryptocurrency, Dean Kamen, delayed gratification, dematerialisation, digital twin, disruptive innovation, Edward Glaeser, Edward Lloyd's coffeehouse, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental economics, food miles, game design, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, gravity well, hive mind, housing crisis, Hyperloop, indoor plumbing, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the telegraph, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kickstarter, late fees, Law of Accelerating Returns, life extension, lifelogging, loss aversion, Lyft, M-Pesa, Mary Lou Jepsen, mass immigration, megacity, meta analysis, meta-analysis, microbiome, mobile money, multiplanetary species, Narrative Science, natural language processing, Network effects, new economy, New Urbanism, Oculus Rift, out of africa, packet switching, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, QR code, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Florida, ride hailing / ride sharing, risk tolerance, Satoshi Nakamoto, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, smart contracts, smart grid, Snapchat, sovereign wealth fund, special economic zone, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, supercomputer in your pocket, supply-chain management, technoutopianism, Tesla Model S, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, urban planning, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, X Prize

Via an app, Lemonade brings together small groups of policyholders who pay premiums into a central “claim pool.” Artificial intelligence does the rest. The entire experience is mobile, simple, and fast. Ninety seconds to get insured, three minutes to get a claim paid, and zero paperwork. Adding more technology to this arrangement, companies like the Swiss firm Etherisc sell “bespoke insurance products” on the Ethereum blockchain. Because smart contracts remove the need for employees, paperwork, and all the rest, all sorts of new insurance products are being created. Etherisc’s first offering is something not covered by traditional insurers: flight delays and cancellations. Individuals sign up via credit card, and if their plane is more than forty-five minutes late, they’re paid instantly, automatically, and without the need for any paperwork.

Eric, 63, 231 drones: disaster relief and, 48 increasing demand for, 10 package delivery and, 47–48, 107 reforestation and, 224, 227 drought, 242 drug development: AI and, 165–67 quantum computing and, 30, 167 Duplex (AI assistant), 35 DxtER, 157 dynamic risk, 187–89 Eagleman, David, 134 Easter Island (Rapa Nui), 174 Echo, 35, 101, 132 e-commerce revolution, 98–100 economy: new business models for, 83–87, 111–13 paradigm shifts in, 97–98 technological unemployment and, 227–30 ecosystems, ecosystem services, collapse of, 223–24 Edison, Thomas, 61 educational system: computer-aided self-teaching and, 144–47 customization of, 150 future of, 143–50 impact of exponential technologies on, 23 multisensory learning in, 148 outmoded models for, 143–44 standardized testing in, 144 teacher shortages in, 143 VR and, 51–52, 147–49, 248 e-governance, 234–35 Ekocenters, 214 electric cars, 10, 16–17, 221–23 electroencephalogram (EEG) sensors, 141 Elevian, 90, 178 emotional intelligence: AI and, 135–38 computers and, 103 robots and, 107 empathy, VR and, 148 endorphins, 247 energy: demonetization and, 78 new sources of, and economic paradigm shifts, 98 renewable, 78, 214, 215–18; see also specific technologies storage of, 218–20 Engines of Creation (Drexler), 63–64 Enlightenment, 82 entertainment: affective computing and, 136–38 content in, see content, entertainment future of, 125–42 streaming and, 126–27 entrepreneurship, immigrants and, 239–40 environment, as global and exponential, 12, 22–24 environmental threats, 211, 240 biodiversity crisis and, 48, 207, 212, 223–27 convergence and, 226–27 deforestation and, 48, 206, 207, 223, 224, 226 extreme weather and, 212, 223, 226 pollution and, 212, 226 water scarcity and, 212–15 see also climate change EOS token, 76 epigenetic alterations, 170 Essex, University of, 203 Estonia, e-governance in, 234–35 Ethereum, 187 Etherisc, 187 Ethiopia, Negroponte’s self-teaching experiment in, 144–46 evolution, trajectory of, 258–59 eVTOLs (electric vertical take-off and landing vehicles), 6, 9–10, 11 see also flying cars Exceptional People (Goldin and Cameron), 237–38 existential risks, 230–36, 240 Exo Imaging, 157 experience economy, 86, 111–13 exponential technologies, xi, 31–33, 39, 200, 215 abundance and, 261–63 brains as poorly adapted to, 12 convergence of, see convergence existential risks and, 230–36 healthcare and, 155, 156–67 Moore’s Law and, 7–8 Netflix and, 126 eXp Realty, 196–97 extreme weather, 212, 223, 226, 241–42 FAA, 6 Facebook, 51, 81, 256 advertising revenue of, 117–18 facial recognition, 120 fakes, fakery, digital, 121–23, 131–32 Federal Judicial Center, 49 Feynman, Richard, 63 Filecoin, 76 Final Frontier Medical Devices, 157 finance industry, 181–82 AI and, 194–96 blockchain and, 193, 194 convergence and, 189–96 Fintech, 194 Fitbit, 41–42 5G networks, 39–40, 119, 149 floating cities, 199–200 Floating Island Project, 200 FLOPS (floating operations per second), 28 Florida, Richard, 244 flow, flow states, 81, 257–58 VR and, 247–48 flow batteries, 219–20 Flow Research Collective, xii, 265 flying cars, 3–7, 26 convergence and, 9–12 healthcare and, 154 prime real estate redefined by, 199 ridesharing and, 4, 19 fMRI studies, 21–22 food chain, 202–3 food industry, 181, 201–8 Forbes, 35, 129 Ford, Henry, 12–13 Ford Motor Company, 221 foreign currency exchange, 194 Forest (quantum developer’s kit), 30, 32 Form Energy, 220 fossil fuels, 215–16 Foster, Richard, 23 Fox News, 247 free/data economy, 84–85 Freestyle Foundation Beverage Dispenser, 214 Friis, Janus, 106 Fukushima Daiichi nuclear plant disaster, 45 future, thinking about, 21–22 Gagarin, Yuri, 73 Garcetti, Eric, 20 Gates, Bill, 203, 214, 220 GDF11 (growth differentiation factor 11), 90, 178–79 Gelsinger, Jesse, 65–66 General Motors (GM), 14, 226 generative adversarial networks (GANs), 165–66, 167 gene sequencing, 78 gene therapy, 65–66, 67, 68 genetic diseases, 65–68 genetics, longevity and, 172–73 genius, nurturing of, 79–82 genome, 66–67 editing of, 67–68, 160 epigenetic alterations to, 170 instability in, 170 Genome Project-Write, 159 genomics, personalized, 158–60 Georgia Institute of Technology, 130 Germany, electric cars in, 221 Germany, Nazi, 238–39 germline engineering, 67–68 Giegel, Josh, 17–18 Gigafactory, 219, 222 GitHub, 146 Glaxo, 152 Global Learning XPRIZE, 146 Global Risks Report (World Economic Forum), 212 global warming, see climate change Gmail, Smart Compose feature of, 35 GM Cruise, 14 Go, 36 Goddard, Robert, 17 Goldin, Ian, 237–38 Goldman Sachs, 230 Good Money, 190–91 Google, 8, 36, 51, 71, 89, 100, 128, 146, 156 advertising revenue of, 117–18 Talk to Books program of, 35 see also Alphabet Google Duplex, 101–2 Google Home, 35 Google Lens, 120 Google Now, 100 governance, existential risks and, 234–36 GPS, 43 graphics processing units (GPUs), 34 Great Recession of 2008, 196, 228 greenhouse gases, 206, 207, 215–16, 221, 226 Gross, Neil, 42–43 group flow, 257–58 Groupon, 4 Guardian, 242, 246 Hagler, Brett, 55–56 Haiti, 58 2010 earthquake in, 55 Hanyecz, Laszlo, 57 haptic sensation, 25, 26, 134–35 Hardy, G.


pages: 138 words: 40,525

This Is Not a Drill: An Extinction Rebellion Handbook by Extinction Rebellion

3D printing, autonomous vehicles, banks create money, bitcoin, blockchain, Buckminster Fuller, car-free, carbon footprint, clean water, Colonization of Mars, crowdsourcing, David Attenborough, David Graeber, decarbonisation, deindustrialization, Donald Trump, Elon Musk, Ethereum, ethereum blockchain, feminist movement, full employment, gig economy, global pandemic, ice-free Arctic, Intergovernmental Panel on Climate Change (IPCC), job automation, mass immigration, Peter Thiel, place-making, quantitative easing, Ray Kurzweil, Sam Altman, smart grid, supply-chain management, the scientific method, union organizing, urban sprawl, wealth creators

But instead of being wired with a microphone or taken to a stage, I just sat there at a plain round table as my audience was brought to me: five super-wealthy guys – yes, all men – from the upper echelon of the hedge-fund world. After a bit of small talk, I realized they had no interest in the information I had prepared about the future of technology. They had come with questions of their own. They started out innocuously enough. Ethereum or bitcoin? Is quantum computing a real thing? Slowly but surely, however, they edged into their real topics of concern. Which region will be less impacted by the coming climate crisis: New Zealand or Alaska? Is Google really building Ray Kurzweil a home for his brain, and will his consciousness live through the transition, or will it die and be reborn as a whole new one? Finally, the CEO of a brokerage house explained that he had nearly completed building his own underground bunker system and asked, ‘How do I maintain authority over my security force after the event?’


pages: 499 words: 144,278

Coders: The Making of a New Tribe and the Remaking of the World by Clive Thompson

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 4chan, 8-hour work day, Ada Lovelace, AI winter, Airbnb, Amazon Web Services, Asperger Syndrome, augmented reality, Ayatollah Khomeini, barriers to entry, basic income, Bernie Sanders, bitcoin, blockchain, blue-collar work, Brewster Kahle, Brian Krebs, Broken windows theory, call centre, cellular automata, Chelsea Manning, clean water, cloud computing, cognitive dissonance, computer vision, Conway's Game of Life, crowdsourcing, cryptocurrency, Danny Hillis, David Heinemeier Hansson, don't be evil, don't repeat yourself, Donald Trump, dumpster diving, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, Ethereum, ethereum blockchain, Firefox, Frederick Winslow Taylor, game design, glass ceiling, Golden Gate Park, Google Hangouts, Google X / Alphabet X, Grace Hopper, Guido van Rossum, Hacker Ethic, HyperCard, illegal immigration, ImageNet competition, Internet Archive, Internet of things, Jane Jacobs, John Markoff, Jony Ive, Julian Assange, Kickstarter, Larry Wall, lone genius, Lyft, Marc Andreessen, Mark Shuttleworth, Mark Zuckerberg, Menlo Park, microservices, Minecraft, move fast and break things, move fast and break things, Nate Silver, Network effects, neurotypical, Nicholas Carr, Oculus Rift, PageRank, pattern recognition, Paul Graham, paypal mafia, Peter Thiel, pink-collar, planetary scale, profit motive, ransomware, recommendation engine, Richard Stallman, ride hailing / ride sharing, Rubik’s Cube, Ruby on Rails, Sam Altman, Satoshi Nakamoto, Saturday Night Live, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, single-payer health, Skype, smart contracts, Snapchat, social software, software is eating the world, sorting algorithm, South of Market, San Francisco, speech recognition, Steve Wozniak, Steven Levy, TaskRabbit, the High Line, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, universal basic income, urban planning, Wall-E, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y Combinator, Zimmermann PGP, éminence grise

It took the slow-moving, long-term patience of a government to produce the core inventions that make it possible for us to hold a phone and order one of Kalanick’s Uber cars. Nonetheless, the libertarian protestations of a certain set of coders continues apace. In recent years, blockchain technology has been the latest site of tech’s anti-government fervor. That ranges from Bitcoin—a currency specifically designed to create money that couldn’t be controlled by dough-printing central banks—to Ethereum, a way of creating “smart contracts” that, its adherents hope, would allow commerce so frictionless and decentralized that even lawyers wouldn’t be necessary: The instant someone performed the service you’d contracted them to do for you, the digital cash would arrive in their digital wallet. One survey of people in the cryptocurrency community found that fully 27 percent called themselves libertarian, more than double the rate Pew Research Center found in the general population.

., ref1 Ellis, Kelly, ref1, ref2 encasement strategy, ref1 encryption Clipper Chip, ref1 criminal/terrorist use of, cypherpunk views on, ref1 entertainment and copyright law and, ref1 munitions law, ref1, ref2 public/private key crypto and, ref1 Zimmermann’s creation of Pretty Good Privacy, ref1 See also cypherpunks engagement (compulsive use) advertising and, ref1 Like button (Facebook) and, ref1 psychological lures to encourage, ref1 English Electric, ref1 ENIAC computer, ref1, ref2 ENIAC Girls, ref1 Ensmenger, Nathan, ref1, ref2 entertainment industry, ref1 decoding software and, ref1 digital rights management (DRM) software, ref1, ref2, ref3 Erickson, Carolina, ref1 Ethereum, ref1 Everingham, James, ref1, ref2, ref3, ref4 expert systems, ref1 “Exploratory Experimental Studies Comparing Online and Offline Programming Performance” (Sackman et al.), ref1 Facebook, ref1, ref2, ref3, ref4, ref5, ref6 ad tech, civic impacts of, ref1 Cambridge Analytica scandal, ref1 content moderation, ref1, ref2 deep-learning model at, ref1 free-to-use model of, ref1 Like button, ref1 News Feed feature of (See News Feed [Facebook]) purchases Instagram, ref1 Sanghvi hired at, ref1 scale and, ref1 tracking of user activities by, ref1 women and minority coders at, percentage of, ref1 work atmosphere at, ref1 Fancy Bear, ref1 Fan Hui, ref1, ref2 Fast Company, ref1 feature creep, ref1 Ferrucci, Dave, ref1, ref2 file-sharing tools, ref1 Firefox, ref1 Fisher, Allan, ref1, ref2, ref3, ref4 Fitzpatrick, Brad, ref1, ref2 Flatiron School, ref1, ref2, ref3 Flickr, ref1 Flombaum, Avi, ref1 FLOW-MATIC computer language, ref1 flow state, ref1 Foer, Franklin, ref1 Fogg, B.


pages: 807 words: 154,435

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

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

But central banks report many different quantitative measures of ‘the money supply’ and the expression M in a mathematical model is as imprecise as the confused references to ‘money supply’ in much popular writing. And what is meant by ‘money’ is temporally and geographically specific. Money is dollars in the US, and euros in Europe. Not so long ago, money was gold and silver. For the inhabitants of Yap in the Caroline Islands, money was Rai, heavy circles of limestone with a hole in the middle. Some people think that crypto-currencies such as Bitcoin and Ethereum are ‘money’. Numbers are essential to economic analysis. But economic data and economic models are never descriptive of ‘the world as it really is’. Economic interpretation is always the product of a social context or theory. Expressing uncertainty When we are wondering whether the man in the compound is bin Laden or what happened to the Mary Celeste , whether the second Smith child is a girl or whether Joyce met Lenin, probabilities are unhelpful.

., 279 , 282 , 292 , 293–4 Eliot, George, Middlemarch , 220 Elizabeth II, Queen, 382–3 , 393 Ellsberg, Daniel, 135 , 136 , 282 emerging economies, 315–16 engineering, 23–4 , 33 , 383 , 384 , 390–1 , 399 Enlightenment, eighteenth-century, 163 , 187 , 387 entrepreneurship, 15 , 49 , 74 , 170 , 258 , 275–6 , 337 , 405 , 430–2 environmentalism, 220 , 361 , 362 Equitable Life Assurance Society, 56 , 328 Ethereum, 96 eugenics, 158 European Central Bank, 350 European Monetary System, 319 European Monetary Union, 45 , 316 European Union, 369–70 , 372 eusociality, 172–3 , 274 evolutionary science: adaptation, 401 ; application to economics, 158 ; and behavioural economics, 154–5 ; co-evolution, 163–4 , 429 , 430–1 ; coping strategies for uncertainty, 47 , 155 ; and decision making, 47 , 171–2 , 177 , 272 , 401 ; discovery and development of, 156 , 157–8 ; an essentially continuous process, 407 , 428–9 , 430–1 ; evolutionary psychology, 416–17 ; and extinctions, 32 ; false association with far-right causes, 158 , 161 ; and intentionality, 431 ; language and communication, 159 , 161–2 , 272 ; and learning of complex skills, 268 , 274–5 , 408 ; nature and nurture, 164–5 ; non-scientific mechanisms of, 158–9 ; optimism and confidence, 167–70 , 330 , 427–8 ; parable of the scorpion and the frog, 164 ; predispositions influencing behaviour, 163–5 ; and rationality, 16–17 , 47 , 152–3 , 155 , 157 , 162 , 171–3 , 272 , 401 ; and risk, 129 , 160–1 , 162 , 166 , 170 , 171 ; the ‘selfish gene’, 156 ; social and cultural practices, 156–65 , 408 ; and survival, 165–7 , 401 ; and trust, 162–3 , 165 ; uncertainty as essential, 428–9 , 431 executive pay, xiv , 409 expected value , concept of, 60 , 106–9 , 114–16 , 124–5 ‘expert’ forecasters, 21–2 , 221–2 Falklands War (1982), 291 , 295 falsificationism, 259–60 Fama, Eugene, 252 , 318 , 320 Fauchard, Pierre, 387 Federal Reserve, US, 103 , 317–18 Ferguson, Adam, 163 , 343 Ferguson, Sir Alex, 273 Fermat, Pierre de, 53 , 56 , 57 , 59–60 , 106 Fermi, Enrico, 84 , 129 Feynman, Richard, 373 , 374 fiction, works of, 92–3 , 212–13 , 219 , 220 , 224–6 , 344 , 397 finance theory: beta coefficients, 332–3 ; capital asset pricing model (CAPM), 307–8 , 309 , 320 , 332 , 334 ; covariances , 332–3 , 366–7 ; definition of risk, 420–1 ; efficient market hypothesis, 252 , 254 , 308–9 , 318 , 320 , 332 , 336–7 ; efficient portfolio model, 307–8 , 309 , 318 , 320 , 332–4 , 366 ; limits of, 318–21 ; quest for large-world model, 392 ; risk as volatility, 124–5 , 310 , 333 , 336 ; three pillars of, 309–10 , 320 , 332 financial crisis (2007–08): and Bank of England ‘fan charts’, 105 ; bankers attribute to chance, 266–7 ; and evolutionary theory, 158–9 ; failure of economic models, xv , 6–7 , 260 , 311–12 , 319 , 339 , 349–50 , 357 , 367–8 , 399 , 407 , 423–4 ; financial sector output after, 95 ; Goldman Sachs risk models, 6–7 , 9 , 68 , 202 , 246–7 ; greedy bankers as risk averse, 127–8 ; and historical narratives, 356–7 ; as intellectual failure, 12 , 319 , 320–1 ; and narrative reasoning, 5–6 ; as not unpredictable/unavoidable, 402–3 ; and pernicious narrative, 410–11 ; prevailing narrative changed by, 351 ; the Queen on, 382–3 , 393 ; and ‘real business cycle’ models, 348 ; recession after, 338–9 ; and ‘thick description’, 193–4 ; volatility and risk, 422–3 financial instruments, 6 , 351 , 366–7 , 401 financial sector: and assumptions of stationarity, 333 , 339 , 340–1 , 349 , 350 , 366–7 ; Basel regulations, 310 , 311 ; broad asset categories, 333–4 ; broad portfolio diversification, 333–5 ; ‘call’ and ‘put’ options, 422–3 ; correlations based on historic data sets, 333 , 366–7 , 390 , 406 ; dominance of narratives, 229–30 , 314–16 , 410–11 ; Dr Evil strategy, 229 , 255 ; executive pay, xiv , 409 ; and expected utility theory, 127 ; failure of finance theory, 318–21 ; government index-linked bonds, 330–1 ; inadequacy of forecasting models, 347–50 , 353–4 , 403–4 ; LIBOR scandal, 192 ; need for strong regulation, 313–14 ; as non-stationary, 16 , 202–3 , 268–9 , 320–1 , 331 , 333 , 339 , 366–8 , 402–3 , 406 ; and normal distribution, 233 ; and power laws, 238–9 ; rescue from collapse (2008), 95 , 311 ; risk and volatility, 124–5 , 310 , 333 , 335–7 , 421–3 ; securitisation, 311 , 316 – 18 , 366–7 , 401 ; securitised mortgages, 311 , 317 , 367 , 372 , 390 , 422–3 ; stock market crashes, 238 , 331 , 354 ; US stock market crash (19 October 1987), 238 ; US subprime mortgage market, 317 , 367 , 390 , 422–3 ; Value at risk models (VaR), 366–8 , 405 , 424 ; see also securities trading Financial Times , xiii Finetti, Bruno de, 73 , 80 , 135 First World War, 357 , 361 Fisher, R.


pages: 533

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

3D printing, additive manufacturing, affirmative action, agricultural Revolution, Airbnb, airport security, Andrew Keen, artificial general intelligence, augmented reality, automated trading system, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, bitcoin, blockchain, brain emulation, British Empire, business process, Capital in the Twenty-First Century by Thomas Piketty, cashless society, Cass Sunstein, cellular automata, cloud computing, computer age, computer vision, continuation of politics by other means, correlation does not imply causation, crowdsourcing, cryptocurrency, digital map, distributed ledger, Donald Trump, easy for humans, difficult for computers, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ethereum, ethereum blockchain, Filter Bubble, future of work, 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, lifelogging, Metcalfe’s law, mittelstand, more computing power than Apollo, move fast and break things, move fast and break things, natural language processing, Network effects, new economy, night-watchman state, Oculus Rift, Panopticon Jeremy Bentham, pattern recognition, payday loans, 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 Jobs, Steve Wozniak, Steven Levy, technological singularity, the built environment, The Structural Transformation of the Public Sphere, The Wisdom of Crowds, Thomas L Friedman, universal basic income, urban planning, Watson beat the top human players on Jeopardy!, working-age population

A ‘smart contract’, for instance, is a piece of blockchain software that executes itself automatically under pre-agreed circumstances— like a purchase agreement which automatically transfers the ownership title of a car to a customer once all loan payments have been made.27 There are early ‘Decentralised Autonomous Organisations’ (DAOs) that seek to solve problems of collective action without a centralized power structure.28 Imagine services like Uber or Airbnb, but without any formal organization at the centre pulling the strings.29 The developers of the Ethereum blockchain, among ­others, have said they want to use DAOs to replace the state altogether. Blockchain still presents serious challenges of scale, governance, and even security, which are yet to be overcome.30 Yet for a youthful technology it is already delivering some interesting results. The governments of Honduras, Georgia, and Sweden are trialling the use of blockchain to handle land titles,31 and the government of Estonia is using it to record more than 1 million patient health records.32 In the UK, the Department for Work and Pensions is piloting a blockchain solution for the payment of welfare benefits.33 In the US, the Defense Advanced Research Projects Agency (DARPA) is looking into using blockchain technology to protect its military networks and communications.34 Increasingly connective technology is not just about people connecting with other people.

S. 57 Elster, Jon 304, 425 EMC 386, 387 Emerging Technology from the arXiv 422 emotions affective computing 52–3 perception-control 148–9 Enchassi, Nadia Judith 370, 420 encryption 182–4 Engels, Friedrich 310, 326–7, 362, 426, 429, 436 England Levellers 215–16 Luddites 13 Revolution 77, 167–8 Entous, Adam 433 entrenchment, rule-based injustice 284 Epicenter 51 epidermal electronics 44 Epstein, Robert 398 equality 10 Data Democracy 247 Deliberative Democracy 234 democracy 223, 225–6 Direct Democracy 240 distributive justice 262–3 human nature 364–5 and justice, difference between 259 of opportunity 260, 261, 263, 270, 294 Esteva, Andre 372 Estonia 47, 220 Ethereum 47 ethics Data Deal 339 human enhancement 363 see also morality European Convention on Human Rights 326 European Court of Human Rights 31, 109 European Court of Justice 138 European Parliament 184 European Union (EU) Brexit 4, 233, 239 competition law 357 General Data Protection Regulation 138, 433 Google fine 357 personal data laws 138 right to explanation 354 taxation 328 everyware see smart devices Executive Office of the President 421, 422 exploitation 273 Eyefluence 319 Facebook acceptable/unacceptable posts 190 acquisitions 318, 319–20 artificial intelligence 116 ban on far-right groups 236 commercial value 66 concentration of tech industry 318, 319, 320, 321 democracy 359 embarrassing photographs 137 fake news 230 fragmented reality 230 friends 284 job applicants 267 Kurds 236 ‘Likes’ 132, 149, 221, 248 machine learning 35 Messenger 318 new media 77 news platform 147 Newsroom 406 Oculus Rift 59 personal data about users 64–5 photograph upload numbers 63 power 350 rules 116 OUP CORRECTED PROOF – FINAL, 28/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS Index user emotions 148–9 user-generated content 315 user numbers 45, 65 users as unpaid workforce 338 US presidential election (2016) 354 Faception 173 facial analysis 52 facial recognition 30, 51 data-based injustice 282 machine learning 36 rule-based injustice 285–6 totalitarianism 178 fact-checking 234 Fairfield, Joshua A.


pages: 352 words: 80,030

The New Silk Roads: The Present and Future of the World by Peter Frankopan

active measures, Berlin Wall, bitcoin, blockchain, Boris Johnson, cashless society, clean water, cryptocurrency, Deng Xiaoping, don't be evil, Donald Trump, Ethereum, ethereum blockchain, F. W. de Klerk, failed state, Fall of the Berlin Wall, global supply chain, illegal immigration, income inequality, invisible hand, land reform, Mark Zuckerberg, mass incarceration, Nelson Mandela, purchasing power parity, ransomware, Rubik’s Cube, smart cities, South China Sea, sovereign wealth fund, trade route, trickle-down economics, UNCLOS, urban planning, WikiLeaks, zero-sum game

There are real dangers in concentrating only on matters that are of parachial importance when so many other more significant and challenging problems require and demand attention. * The rapid development of new technologies is also a significant difficulty to address, in terms of trying to predict the impact these will have in the coming years – and working out how to prepare accordingly for a world where artificial intelligence (AI), robotics, machine learning, Blockchain, Ethereum and more will change the way we live, love, work and communicate. Then there are cryptocurrencies like Bitcoin, which, while exciting for digital pioneers, seem most obviously of interest to those who seek to keep their transactions secure and away from prying eyes – including those who deal in illicit substances or goods, or who prefer to keep potentially taxable revenue away from the authorities.


pages: 273 words: 72,024

Bitcoin for the Befuddled by Conrad Barski

Airbnb, AltaVista, altcoin, bitcoin, blockchain, buttonwood tree, cryptocurrency, Debian, en.wikipedia.org, Ethereum, ethereum blockchain, fiat currency, Isaac Newton, MITM: man-in-the-middle, money: store of value / unit of account / medium of exchange, Network effects, node package manager, p-value, peer-to-peer, price discovery process, QR code, Satoshi Nakamoto, self-driving car, SETI@home, software as a service, the payments system, Yogi Berra

Paul Krugman, “The Antisocial Network,” New York Times, April 14, 2013, http://www.nytimes.com/2013/04/15/opinion/krugman-the-antisocial-network.html 12. http://www.federalreserve.gov/faqs/how-long-is-the-life-span-of-us-paper-money.htm 13. Named after John Maynard Keynes, the economist who is most strongly identified with this particular approach to monetary policy 14. One well-articulated version of this argument is given by Paul Krugman in the article “Bitcoin Is Evil,” New York Times, December 28, 2013, http://krugman.blogs.nytimes.com/2013/12/28/bitcoin-is-evil/. 15. http://ethereum.org/ 16. http://bitmessage.org/ Chapter 7: The Cryptography Behind Bitcoin 1. This term is used in addition to the many others for Bitcoin, such as digital currency, math-based currency, and among those who don’t think bitcoins are real money, virtual currency. 2. An integer is a number that can be written without a fractional or decimal component (e.g., −4, 2, or 17 but not 4.23 or 1.5). 3.


pages: 252 words: 78,780

Lab Rats: How Silicon Valley Made Work Miserable for the Rest of Us by Dan Lyons

Airbnb, Amazon Web Services, Apple II, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, business process, call centre, Clayton Christensen, clean water, collective bargaining, corporate governance, corporate social responsibility, creative destruction, cryptocurrency, David Heinemeier Hansson, Donald Trump, Elon Musk, Ethereum, ethereum blockchain, full employment, future of work, gig economy, Gordon Gekko, greed is good, hiring and firing, housing crisis, income inequality, informal economy, Jeff Bezos, job automation, job satisfaction, job-hopping, John Gruber, Joseph Schumpeter, Kevin Kelly, knowledge worker, Lean Startup, loose coupling, Lyft, Marc Andreessen, Mark Zuckerberg, McMansion, Menlo Park, Milgram experiment, minimum viable product, Mitch Kapor, move fast and break things, move fast and break things, new economy, Panopticon Jeremy Bentham, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, precariat, RAND corporation, remote working, RFID, ride hailing / ride sharing, Ronald Reagan, Rubik’s Cube, Ruby on Rails, Sam Altman, Sand Hill Road, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, Skype, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, Stanford prison experiment, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, TaskRabbit, telemarketer, Tesla Model S, Thomas Davenport, Tony Hsieh, Toyota Production System, traveling salesman, Travis Kalanick, tulip mania, Uber and Lyft, Uber for X, uber lyft, universal basic income, web application, Whole Earth Catalog, Y Combinator, young professional

They’ve seen other big old companies get killed off by Silicon Valley, and they would rather not have this happen to them. They seem to believe that some magic elixir exists here, some recipe for innovation that floats in the air and can be absorbed if you drive around with your windows open, smelling the eucalyptus trees. They see people getting rich on things they don’t even understand. Blockchain? Ethereum? Initial coin offerings? So they fly out and have drinks at the Rosewood Hotel on Sand Hill Road in Menlo Park, where venture capitalists hang around, as do expensive “companions,” many with Eastern European accents. They eat lunch at the Battery, a members-only private club for social-climbing parvenus in San Francisco. They wangle an invitation to a Bitcoin party and rub shoulders with the scammers, hustlers, Ponzi schemers, and obnoxious knobs who are trying to cash in on a modern-day tulip mania based around a cryptocurrency that Warren Buffett describes as “rat poison squared.”


pages: 292 words: 85,151

Exponential Organizations: Why New Organizations Are Ten Times Better, Faster, and Cheaper Than Yours (And What to Do About It) by Salim Ismail, Yuri van Geest

23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Ben Horowitz, bioinformatics, bitcoin, Black Swan, blockchain, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, Dean Kamen, dematerialisation, discounted cash flows, disruptive innovation, distributed ledger, Edward Snowden, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Joi Ito, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, low earth orbit, Lyft, Marc Andreessen, Mark Zuckerberg, market design, means of production, minimum viable product, natural language processing, Netflix Prize, NetJets, Network effects, new economy, Oculus Rift, offshore financial centre, PageRank, pattern recognition, Paul Graham, paypal mafia, peer-to-peer, peer-to-peer model, Peter H. Diamandis: Planetary Resources, Peter Thiel, prediction markets, profit motive, publish or perish, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, subscription business, supply-chain management, TaskRabbit, telepresence, telepresence robot, Tony Hsieh, transaction costs, Travis Kalanick, Tyler Cowen: Great Stagnation, uber lyft, urban planning, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

In the same way that Internet communications have seen costs drop to near zero, we expect to see internal organizational and transactions costs also fall to near zero as we increasingly information-enable and distribute our organizational structures. Ultimately, in the face of such low transaction costs, we anticipate what we’re calling a Cambrian Explosion in organizational design—everything from community-based structures to virtual organizations (see Ethereum) that will be small, nimble and extensible. It is also becoming increasingly clear that, like the Internet, the ExO paradigm is not just for business. It can just as easily be applied to all sorts of enterprises and organizations, from academia to non-profits to government. In short, it is not just a system of commerce, but also a philosophy of action. For example, what would an exponential government look like?


pages: 366 words: 94,209

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

activist fund / activist shareholder / activist investor, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, 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, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, loss aversion, 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, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, TaskRabbit, The Future of Employment, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, uber lyft, unpaid internship, Y Combinator, young professional, zero-sum game, Zipcar

Mark Gimein, “Virtual Bitcoin Mining Is a Real-World Environmental Disaster,” bloomberg.com, April 12, 2013. 39. Michael Carney, “Bitcoin Has a Dark Side: Its Carbon Footprint,” pando.com, December 16, 2013. 40. Lawler, “Bitcoin Miners Are Racking Up $150,000 a Day.” 41. Jon Evans, “Enter the Blockchain: How Bitcoin Can Turn the Cloud Inside Out,” techcrunch.com, March 22, 2014. 42. Vitalik Buterin, “DAOs, DACs, DAs and More: An Incomplete Terminology Guide,” blog.ethereum.org, May 6, 2014. 43. David Johnston, Sam Onat Yilmaz, Jeremy Kandah, Nikos Bentenitis, Farzad Hashemi, Ron Gross, Shawn Wilkinson, and Steven Mason, “The General Theory of Decentralized Applications, Dapps,” github.com, June 9, 2014. 44. Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System.” 45. National Patient Advocate Foundation, “Issue Brief: Medical Debt, Medical Bankruptcy and the Impact on Patients,” npaf.org, September 2012. 46.


pages: 330 words: 91,805

Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism by Robin Chase

Airbnb, Amazon Web Services, Andy Kessler, banking crisis, barriers to entry, basic income, Benevolent Dictator For Life (BDFL), bitcoin, blockchain, Burning Man, business climate, call centre, car-free, cloud computing, collaborative consumption, collaborative economy, collective bargaining, commoditize, congestion charging, creative destruction, crowdsourcing, cryptocurrency, decarbonisation, different worldview, do-ocracy, don't be evil, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, Ferguson, Missouri, Firefox, frictionless, Gini coefficient, hive mind, income inequality, index fund, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jane Jacobs, Jeff Bezos, jimmy wales, job satisfaction, Kickstarter, Lean Startup, Lyft, means of production, megacity, Minecraft, minimum viable product, Network effects, new economy, Oculus Rift, openstreetmap, optical character recognition, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, smart cities, smart grid, Snapchat, sovereign wealth fund, Steve Crocker, Steve Jobs, Steven Levy, TaskRabbit, The Death and Life of Great American Cities, The Future of Employment, The Nature of the Firm, transaction costs, Turing test, turn-by-turn navigation, Uber and Lyft, uber lyft, Zipcar

Matan, and other Bitcoin innovators and entrepreneurs, are pushing the envelope. Much more content can be embedded in the transaction “Payer X wants to send Y Bitcoins to payee Z.” See the Bitcoin transaction as a subject-verb-object command. All kinds of important data relating to the subject and object (name, address, ratings, contingencies), and all types of actions (rent, buy, barter, rideshare, publish) could be substituted in. Budding companies—LaZooz, Swarm, and Ethereum, to name three—are fleshing out this idea. Any kind of business or personal transaction needing standard contracts, for standard actions, with standard rules could all be sent, appended, and amended using the block chain. Every transaction can have its own special combination built using standard building blocks. Rule-making and standards adoption is all accomplished through decentralized leader-free “voting” based on market signals.


Martin Kleppmann-Designing Data-Intensive Applications. The Big Ideas Behind Reliable, Scalable and Maintainable Systems-O’Reilly (2017) by Unknown

active measures, Amazon Web Services, bitcoin, blockchain, business intelligence, business process, c2.com, cloud computing, collaborative editing, commoditize, conceptual framework, cryptocurrency, database schema, DevOps, distributed ledger, Donald Knuth, Edward Snowden, Ethereum, ethereum blockchain, fault tolerance, finite state, Flash crash, full text search, general-purpose programming language, informal economy, information retrieval, Internet of things, iterative process, John von Neumann, Kubernetes, loose coupling, Marc Andreessen, microservices, natural language processing, Network effects, 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, statistical model, undersea cable, web application, WebSocket, wikimedia commons

A transaction log can be made tamper-proof by periodically signing it with a hardware security module, but that does not guarantee that the right transactions went into the log in the first place. It would be interesting to use cryptographic tools to prove the integrity of a system in a way that is robust to a wide range of hardware and software issues, and even poten‐ tially malicious actions. Cryptocurrencies, blockchains, and distributed ledger tech‐ nologies such as Bitcoin, Ethereum, Ripple, Stellar, and various others [71, 72, 73] have sprung up to explore this area. I am not qualified to comment on the merits of these technologies as currencies or mechanisms for agreeing contracts. However, from a data systems point of view they contain some interesting ideas. Essentially, they are distributed databases, with a data model and transaction mechanism, in which different replicas can be hosted by mutually untrusting organizations.

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!


pages: 1,237 words: 227,370

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann

active measures, Amazon Web Services, bitcoin, blockchain, business intelligence, business process, c2.com, cloud computing, collaborative editing, commoditize, conceptual framework, cryptocurrency, database schema, DevOps, distributed ledger, Donald Knuth, Edward Snowden, Ethereum, ethereum blockchain, fault tolerance, finite state, Flash crash, full text search, general-purpose programming language, informal economy, information retrieval, Infrastructure as a Service, Internet of things, iterative process, John von Neumann, Kubernetes, loose coupling, Marc Andreessen, microservices, natural language processing, Network effects, 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, statistical model, undersea cable, web application, WebSocket, wikimedia commons

A transaction log can be made tamper-proof by periodically signing it with a hardware security module, but that does not guarantee that the right transactions went into the log in the first place. It would be interesting to use cryptographic tools to prove the integrity of a system in a way that is robust to a wide range of hardware and software issues, and even potentially malicious actions. Cryptocurrencies, blockchains, and distributed ledger technologies such as Bitcoin, Ethereum, Ripple, Stellar, and various others [71, 72, 73] have sprung up to explore this area. I am not qualified to comment on the merits of these technologies as currencies or mechanisms for agreeing contracts. However, from a data systems point of view they contain some interesting ideas. Essentially, they are distributed databases, with a data model and transaction mechanism, in which different replicas can be hosted by mutually untrusting organizations.

multi-object transactions, need for, The need for multi-object transactions versus relational modelconvergence of models, Convergence of document and relational databases data locality, Data locality for queries document-partitioned indexes, Partitioning Secondary Indexes by Document, Summary, Building search indexes domain-driven design (DDD), Event Sourcing DRBD (Distributed Replicated Block Device), Leaders and Followers drift (clocks), Clock Synchronization and Accuracy Drill (query engine), The divergence between OLTP databases and data warehouses Druid (database), Deriving several views from the same event log Dryad (dataflow engine), Dataflow engines dual writes, problems with, Keeping Systems in Sync, Dataflow: Interplay between state changes and application code duplicates, suppression of, Duplicate suppression(see also idempotence) using a unique ID, Operation identifiers, Multi-partition request processing durability (transactions), Durability, Glossary duration (time), Unreliable Clocksmeasurement with monotonic clocks, Monotonic clocks dynamic partitioning, Dynamic partitioning dynamically typed languagesanalogy to schema-on-read, Schema flexibility in the document model code generation and, Code generation and dynamically typed languages Dynamo-style databases (see leaderless replication) E edges (in graphs), Graph-Like Data Models, Reduce-Side Joins and Groupingproperty graph model, Property Graphs edit distance (full-text search), Full-text search and fuzzy indexes effectively-once semantics, Fault Tolerance, Exactly-once execution of an operation(see also exactly-once semantics) preservation of integrity, Correctness of dataflow systems elastic systems, Approaches for Coping with Load Elasticsearch (search server)document-partitioned indexes, Partitioning Secondary Indexes by Document partition rebalancing, Fixed number of partitions percolator (stream search), Search on streams usage example, Thinking About Data Systems use of Lucene, Making an LSM-tree out of SSTables ElephantDB (database), Key-value stores as batch process output Elm (programming language), Designing Applications Around Dataflow, End-to-end event streams encodings (data formats), Encoding and Evolution-The Merits of SchemasAvro, Avro-Code generation and dynamically typed languages binary variants of JSON and XML, Binary encoding compatibility, Encoding and Evolutioncalling services, Data encoding and evolution for RPC using databases, Dataflow Through Databases-Archival storage using message-passing, Distributed actor frameworks defined, Formats for Encoding Data JSON, XML, and CSV, JSON, XML, and Binary Variants language-specific formats, Language-Specific Formats merits of schemas, The Merits of Schemas representations of data, Formats for Encoding Data Thrift and Protocol Buffers, Thrift and Protocol Buffers-Datatypes and schema evolution end-to-end argument, Cloud Computing and Supercomputing, The end-to-end argument-Applying end-to-end thinking in data systemschecking integrity, The end-to-end argument again publish/subscribe streams, End-to-end event streams enrichment (stream), Stream-table join (stream enrichment) Enterprise JavaBeans (EJB), The problems with remote procedure calls (RPCs) entities (see vertices) epoch (consensus algorithms), Epoch numbering and quorums epoch (Unix timestamps), Time-of-day clocks equi-joins, Reduce-Side Joins and Grouping erasure coding (error correction), MapReduce and Distributed Filesystems Erlang OTP (actor framework), Distributed actor frameworks error handlingfor network faults, Network Faults in Practice in transactions, Handling errors and aborts error-correcting codes, Cloud Computing and Supercomputing, MapReduce and Distributed Filesystems Esper (CEP engine), Complex event processing etcd (coordination service), Membership and Coordination Services-Membership serviceslinearizable operations, Implementing Linearizable Systems locks and leader election, Locking and leader election quorum reads, Implementing linearizable storage using total order broadcast service discovery, Service discovery use of Raft algorithm, Using total order broadcast, Distributed Transactions and Consensus Ethereum (blockchain), Tools for auditable data systems Ethernet (networks), Cloud Computing and Supercomputing, Unreliable Networks, Can we not simply make network delays predictable?packet checksums, Weak forms of lying, The end-to-end argument Etherpad (collaborative editor), Collaborative editing ethics, Doing the Right Thing-Legislation and self-regulationcode of ethics and professional practice, Doing the Right Thing legislation and self-regulation, Legislation and self-regulation predictive analytics, Predictive Analytics-Feedback loopsamplifying bias, Bias and discrimination feedback loops, Feedback loops privacy and tracking, Privacy and Tracking-Legislation and self-regulationconsent and freedom of choice, Consent and freedom of choice data as assets and power, Data as assets and power meaning of privacy, Privacy and use of data surveillance, Surveillance respect, dignity, and agency, Legislation and self-regulation, Summary unintended consequences, Doing the Right Thing, Feedback loops ETL (extract-transform-load), Data Warehousing, Example: analysis of user activity events, Keeping Systems in Sync, Glossaryuse of Hadoop for, Diversity of storage event sourcing, Event Sourcing-Commands and eventscommands and events, Commands and events comparison to change data capture, Event Sourcing comparison to lambda architecture, The lambda architecture deriving current state from event log, Deriving current state from the event log immutability and auditability, State, Streams, and Immutability, Designing for auditability large, reliable data systems, Operation identifiers, Correctness of dataflow systems Event Store (database), Event Sourcing event streams (see streams) events, Transmitting Event Streamsdeciding on total order of, The limits of total ordering deriving views from event log, Deriving several views from the same event log difference to commands, Commands and events event time versus processing time, Event time versus processing time, Microbatching and checkpointing, Unifying batch and stream processing immutable, advantages of, Advantages of immutable events, Designing for auditability ordering to capture causality, Ordering events to capture causality reads as, Reads are events too stragglers, Knowing when you’re ready, The lambda architecture timestamp of, in stream processing, Whose clock are you using, anyway?


pages: 903 words: 235,753

The Stack: On Software and Sovereignty by Benjamin H. Bratton

1960s counterculture, 3D printing, 4chan, Ada Lovelace, additive manufacturing, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, basic income, Benevolent Dictator For Life (BDFL), Berlin Wall, bioinformatics, bitcoin, blockchain, Buckminster Fuller, Burning Man, call centre, carbon footprint, carbon-based life, Cass Sunstein, Celebration, Florida, charter city, clean water, cloud computing, connected car, corporate governance, crowdsourcing, cryptocurrency, dark matter, David Graeber, deglobalization, dematerialisation, disintermediation, distributed generation, don't be evil, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, Eratosthenes, Ethereum, ethereum blockchain, facts on the ground, Flash crash, Frank Gehry, Frederick Winslow Taylor, future of work, Georg Cantor, gig economy, global supply chain, Google Earth, Google Glasses, Guggenheim Bilbao, High speed trading, Hyperloop, illegal immigration, industrial robot, information retrieval, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, Joan Didion, John Markoff, Joi Ito, Jony Ive, Julian Assange, Khan Academy, liberal capitalism, lifelogging, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, MITM: man-in-the-middle, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, peer-to-peer, performance metric, personalized medicine, Peter Eisenman, Peter Thiel, phenotype, Philip Mirowski, Pierre-Simon Laplace, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Robert Bork, Sand Hill Road, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, smart cities, smart grid, smart meter, social graph, software studies, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Startup school, statistical arbitrage, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, Superbowl ad, supply-chain management, supply-chain management software, TaskRabbit, the built environment, The Chicago School, the scientific method, Torches of Freedom, transaction costs, Turing complete, Turing machine, Turing test, undersea cable, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, Westphalian system, WikiLeaks, working poor, Y Combinator

Would it do more to ground money in a marking fabrication of total debt that is more relevant to economies defined by the paradoxes of Anthropocenic growth? Speaking of reserve currencies, Bitcoin introduces addressable scarcity not in direct relation to the sum of mined minerals or national currencies, but by the mathematics of solving increasingly difficult problems toward an eventual arbitrary limit of 21 million “coins.” There is much to explore with Bitcoin, blockchains and related initiatives, such as Ethereum, but it is also the monetary platform of choice of secessionist projects for which the metaphysical expulsion of externalities is the paramount program, as important if not more than the disintermediation of central banks. The version of Bitcoin that we have (other currencies may fork or follow) is exemplary of the future-archaic quality of many Stack innovations. It is, as Paul Krugman puts it, “both a 17th century and 21st century currency at once,” a currency mechanism that would freeze the sum total of possible liquid value tokens in the world, now and forever.64 In this regard, for certain persuasions, it is better than magic rocks (like gold) because incrementally more gold can always be mined, allowing rootless cosmopolitans to upset “the natural order” of hierarchical hereditary accumulation.

See also platform economics Anthropocenic, 58, 103 of borders, 173 capitalist, 56 City layer, 159–160 Cloud model, 137 electronics, mining and trading in, 82–83 zero-sum, 336 economy of additive manufacturing, 202 of cognitive capital, 110, 116 computational, 328 computer-controlled, 58–60 of contemporary warfare, 248 digital, 196 of energy, 92, 106–107 Facebook, 127 Google, 136–138, 159, 444n26 of identity, 270 of information, 199 of mobility, 280 of prostheticization, 273 of reversible partitions, 21 of scarcity, 208 and sovereignty and territory, 114, 316 ecopolitics, 100 ecosystems, 129, 178, 185, 336, 456n6 Ecumenopolis (Dioxiadis), 178 Eisenman, Peter, 410n50 Elden, Stewart, 335, 379n12 electricity, 93, 95, 141 electronics, mining and trading in, 82–83 electronic waste, 83 Elysium (Blomkamp), 311, 323, 444n27 emergency accommodating, 103–104 designing for/designing with, 101–104, 321, 325 ecojurisdictions in response to, 99–100 ecological, 105–106, 295, 305 ecopolitics emerging by, 100 exceptional, 103–104, 173, 321–322 permanent, 104 progress in response to, 321 sovereign decision and, 20, 32, 102–103 state of, 32–33, 99 emergent, the, 9 empty space, 30, 380n20 enclosure and escape, 22, 32–33, 149–150, 172–176, 303 “end of history,” 321 “End of Sykes-Picot, The” 430n65 energy alternative sources, 259 ecologies of, 98–104 economy, 92 efficiencies, 140–141 energy-information network, 93, 95 footprint, of planetary-scale computing, 82–83, 92–96, 106–107, 113, 140–141, 258–260, 303–304 grid, 92–96, 140, 152, 201, 294–295 needs, predicted, 113 political loyalty and availability, 141 polities, subdivided, 99–100 post-Anthropocene, 217 Eneropa, 99 Engelbart, Douglas, 343 Enlightenment, 251, 426n46 entertaining securitization, 156 entertainment identifier registry (EIDR), 207 entrance/exit, 149–150, 313, 315, 317, 371 envelope-interface borders, 172–173 envelopes airports, 156–157 architectural, 23, 165–167, 195, 303, 311–313, 323 cars as, 238 City layer, 12, 70, 148–149, 152, 154–155, 163–171, 173 as interface, 167 mixed, designing for, 168–172 paper, 46, 195 physical, 167 software, 167 urban, 168–172 urban platform, 180 User position in relation to, 252 environmental migrants/refugees, 100–101 Epicureanism, inverse, 358 equilibrium, cybernetic, 59, 158 error detection, 50 espionage, 398n21 Estates of The Oaks, 311 Estonia, 399n36, 446n42 Ethereum, 336 ethics, 258, 285, 362 European nomos of World Wars I and II, 25–26 European Space Agency, 181 European Union, 309 exception in Apple model, 130 automation of, 33 becomes the rule, 102–103, 111 emergency, 103–104, 173, 321–322 emergent order of, 110–111 inside and outside the law, 102 interface, 357 legitimate state of, 104 normalizing, 23, 32–33, 39, 103–104 reversibility of, 21, 32–33, 39, 145 sovereignty over, 20–21, 32, 105, 341 state of emergency as, 99, 105 territories of, 114 exclusion agency and, 173–175 augmented reality and, 236, 241–242 elective, 316–317 societal, 308–309, 311–312, 317 exclusive totalities, 245 exit.


pages: 611 words: 130,419

Narrative Economics: How Stories Go Viral and Drive Major Economic Events by Robert J. Shiller

agricultural Revolution, Albert Einstein, algorithmic trading, Andrei Shleifer, autonomous vehicles, bank run, banking crisis, basic income, bitcoin, blockchain, business cycle, butterfly effect, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, central bank independence, collective bargaining, computerized trading, corporate raider, correlation does not imply causation, cryptocurrency, Daniel Kahneman / Amos Tversky, debt deflation, disintermediation, Donald Trump, Edmond Halley, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, full employment, George Akerlof, germ theory of disease, German hyperinflation, Gunnar Myrdal, Gödel, Escher, Bach, Hacker Ethic, implied volatility, income inequality, inflation targeting, invention of radio, invention of the telegraph, Jean Tirole, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, litecoin, market bubble, money market fund, moral hazard, Northern Rock, nudge unit, Own Your Own Home, Paul Samuelson, Philip Mirowski, plutocrats, Plutocrats, Ponzi scheme, publish or perish, random walk, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Reagan, Rubik’s Cube, Satoshi Nakamoto, secular stagnation, shareholder value, Silicon Valley, speech recognition, Steve Jobs, Steven Pinker, stochastic process, stocks for the long run, superstar cities, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, theory of mind, Thorstein Veblen, traveling salesman, trickle-down economics, tulip mania, universal basic income, Watson beat the top human players on Jeopardy!, We are the 99%, yellow journalism, yield curve, Yom Kippur War

Narrative economics, the study of the viral spread of popular narratives that affect economic behavior, can improve our ability to anticipate and prepare for economic events. It can also help us structure economic institutions and policy. To get a feel for where we are going, let’s begin by considering one such popular narrative, recently in full swing. Bitcoin, the first of thousands of privately issued cryptocurrencies—including Litecoin, Ripple, Ethereum, and Libra—has generated enormous levels of talk, enthusiasm, and entrepreneurial activity. These narratives surrounding Bitcoin, the most remarkable cryptocurrency in history as judged by the speculative enthusiasm for it and its market price rather than its actual use in commerce, provide an intuitive basis for discussing the basic epidemiology of narrative economics (which we explore in detail in chapter 3).


pages: 589 words: 147,053

The Age of Em: Work, Love and Life When Robots Rule the Earth by Robin Hanson

8-hour work day, artificial general intelligence, augmented reality, Berlin Wall, bitcoin, blockchain, brain emulation, business cycle, business process, Clayton Christensen, cloud computing, correlation does not imply causation, creative destruction, demographic transition, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental subject, fault tolerance, financial intermediation, Flynn Effect, hindsight bias, information asymmetry, job automation, job satisfaction, John Markoff, Just-in-time delivery, lone genius, Machinery of Freedom by David Friedman, market design, meta analysis, meta-analysis, Nash equilibrium, new economy, prediction markets, rent control, rent-seeking, reversible computing, risk tolerance, Silicon Valley, smart contracts, statistical model, stem cell, Thomas Malthus, trade route, Turing test, Vernor Vinge

Bureau of Labor Statistics. 2013. “Time Spent in Primary Activities and Percent of the Civilian Population Engaging in Each Activity, Averages per Day by Sex, 2012 Annual Averages.” Bureau of Labor Statistics Economic News Release. June 20. http://www.bls.gov/news.release/atus.t01.htm. Buterin, Vitalik. 2014. “White Paper: A Next-Generation Smart Contract and Decentralized Application Platform.” April. https://www.ethereum.org/pdfs/EthereumWhitePaper.pdf. Caplan, Bryan. 2008. “The Totalitarian Threat.” In Global Catastrophic Risks, edited by Nick Bostrom and Milan Ćirković, 504–519. Oxford University Press, July 17. Caplan, Bryan, and Stephen Miller. 2010. “Intelligence Makes People Think Like Economists: Evidence from the General Social Survey.” Intelligence 38(6): 636–647. Card, Orson Scott. 2011. Elements of Fiction Writing—Characters and Viewpoint, 2nd ed.


pages: 497 words: 144,283

Connectography: Mapping the Future of Global Civilization by Parag Khanna

"Robert Solow", 1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 9 dash line, additive manufacturing, Admiral Zheng, affirmative action, agricultural Revolution, Airbnb, Albert Einstein, amateurs talk tactics, professionals talk logistics, Amazon Mechanical Turk, Asian financial crisis, asset allocation, autonomous vehicles, banking crisis, Basel III, Berlin Wall, bitcoin, Black Swan, blockchain, borderless world, Boycotts of Israel, Branko Milanovic, BRICs, British Empire, business intelligence, call centre, capital controls, charter city, clean water, cloud computing, collateralized debt obligation, commoditize, complexity theory, continuation of politics by other means, corporate governance, corporate social responsibility, credit crunch, crony capitalism, crowdsourcing, cryptocurrency, cuban missile crisis, data is the new oil, David Ricardo: comparative advantage, deglobalization, deindustrialization, dematerialisation, Deng Xiaoping, Detroit bankruptcy, digital map, disruptive innovation, diversification, Doha Development Round, edge city, Edward Snowden, Elon Musk, energy security, Ethereum, ethereum blockchain, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, forward guidance, global supply chain, global value chain, global village, Google Earth, Hernando de Soto, high net worth, Hyperloop, ice-free Arctic, if you build it, they will come, illegal immigration, income inequality, income per capita, industrial cluster, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, LNG terminal, low cost airline, low cost carrier, low earth orbit, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, mittelstand, Monroe Doctrine, mutually assured destruction, New Economic Geography, new economy, New Urbanism, off grid, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Parag Khanna, Peace of Westphalia, peak oil, Pearl River Delta, Peter Thiel, Philip Mirowski, plutocrats, Plutocrats, post-oil, post-Panamax, private military company, purchasing power parity, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, six sigma, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, Stuxnet, supply-chain management, sustainable-tourism, TaskRabbit, telepresence, the built environment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, Tim Cook: Apple, trade route, transaction costs, UNCLOS, uranium enrichment, urban planning, urban sprawl, WikiLeaks, young professional, zero day

With the Bali Trade Facilitation Agreement of 2013, the harmonization of customs administration (cutting red tape) could add $1 trillion to world GDP and create twenty million jobs. A study undertaken by the World Economic Forum and Bain estimates that further aligning supply chain standards would boost world GDP by an enormous 5 percent, while implementation of all current WTO accords would deliver only 1 percent growth. The Ethereum blockchain platform will allow for standardized and transparent contracts between trading parties beyond any single jurisdiction and, when combined with real-time data sharing on supply chain transactions, can substantially reduce the cost of insuring trade. Open trade and open borders further reorganize the world into functional circuits. Despite widely divergent geography and wealth, Canada, Argentina, South Africa, Indonesia, Australia, and other countries coalesced into the Cairns Group to push for free trade in agriculture: They are the “farm circuit” of global trade.