John von Neumann

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Turing's Cathedral by George Dyson

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

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

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

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

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

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

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

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

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

Darwin Among the Machines by George Dyson

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

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

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

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

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

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

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

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

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

The Man Who Invented the Computer by Jane Smiley

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

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

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

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

A Beautiful Mind by Sylvia Nasar

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Complexity: A Guided Tour by Melanie Mitchell

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

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

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

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

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

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

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

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

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

The Fractalist by Benoit Mandelbrot

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Thinking in Bets by Annie Duke

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Rise of the Machines: A Cybernetic History by Thomas Rid

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Licence to be Bad by Jonathan Aldred

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Making of the Atomic Bomb by Richard Rhodes

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Scientist as Rebel by Freeman Dyson

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

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

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

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

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

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

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

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

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

Smart Mobs: The Next Social Revolution by Howard Rheingold

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

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

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

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

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

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

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

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

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

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

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

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

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

Chaos: Making a New Science by James Gleick

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

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

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

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

Beyond Weird by Philip Ball

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Simulation Hypothesis by Rizwan Virk

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Transhumanist Reader by Max More, Natasha Vita-More

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

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

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

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

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

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

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

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

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

Beyond: Our Future in Space by Chris Impey

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

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

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

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

The Road to Conscious Machines by Michael Wooldridge

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

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

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

The Scandal of Money by George Gilder

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

When Things Start to Think by Neil A. Gershenfeld

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

I Am a Strange Loop by Douglas R. Hofstadter

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Ways of Being: Beyond Human Intelligence by James Bridle

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

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

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