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

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

First we look at Church’s λ-calculus (lambda calculus), then Post’s tag systems, and finally cellular automata. All of these have been shown to be able to do computations. In fact, rather surprisingly, all have computational power equivalent to Turing machines. We start with the λ-calculus. This plays an important role in computer science, especially in the design of computer languages. After our brief foray into λ-calculus we move on to tag systems. Tag systems are easy to describe, but despite their simplicity, they are able to do any computation. Their simplicity is often useful in proving the equivalence of computational systems. For example, the proof that cellular automata can do anything that Turing machines can do involves emulating Turing machines by tag systems. The final topic is the study one-dimensional cellular automata. These are interesting because they yield two-dimensional pictures that show the entire computation.

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Quantum Computing since Democritus by Aaranson, The Beginning of Infinity: Explanations That Transform the World by Deutsch, and Gödel, Escher, Bach by Hofstadter are all fascinating. Cellular automata We only looked briefly looked at cellular automata, but they have a long and interesting history. They were first studied by Ulam and von Neumann as the first computers were built. Nils Barricelli was at Princeton during the 1950s and used the computer to simulate the interaction of cells. George Dyson’s Turing’s Cathedral gives a good historical description of this work John Conway, in 1970, defined Life involving two-dimensional cellular automata. These were popularized by Martin Gardner in Scientific American. William Poundstone’s The Recursive Universe is a good book on the history of these automata and how complexity can arise from simple rules.

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Chapter 5 In addition to Turing’s approach, there are several different ways at looking at computation. In this chapter we pause to examine at three of these. We begin with the lambda calculus (λ-calculus) of Alonzo Church, then look at an example of a tag system, finally we consider cellular automata. These views of computation seem very different, but each perspective has its own strengths. The λ-calculus leads to programming languages; tag systems are useful for proving different systems equivalent; cellular automata give pictures of complete computations. After this brief detour we return to Turing’s arguments. Chapter 6 Up until now, machines have been described by diagrams. This chapter starts by showing how finite automata and Turing machines can be described by finite sequences of digits, called encodings.

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Think Complexity
** by
Allen B. Downey

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Benoit Mandelbrot, cellular automata, Conway's Game of Life, Craig Reynolds: boids flock, discrete time, en.wikipedia.org, Frank Gehry, Gini coefficient, Guggenheim Bilbao, mandelbrot fractal, Occupy movement, Paul Erdős, peer-to-peer, Pierre-Simon Laplace, sorting algorithm, stochastic process, strong AI, Thomas Kuhn: the structure of scientific revolutions, Turing complete, Turing machine, Vilfredo Pareto, We are the 99%

This book is also about complexity science, which is an interdisciplinary field (at the intersection of mathematics, computer science, and natural science) that focuses on discrete models of physical systems. In particular, it focuses on complex systems, which are systems with many interacting components. Complex systems include networks and graphs, cellular automata, agent-based models and swarms, fractals and self-organizing systems, chaotic systems, and cybernetic systems. These terms might not mean much to you at this point. We will get to them soon, but you can get a preview at http://en.wikipedia.org/wiki/Complex_systems. A New Kind of Science In 2002, Stephen Wolfram published A New Kind of Science, where he presents his and others’ work on cellular automata and describes a scientific approach to the study of computational systems. We’ll get back to Wolfram in Chapter 6, but I want to borrow his title for something a little broader. I think complexity is a “new kind of science” not because it applies the tools of science to a new subject, but because it uses different tools, allows different kinds of work, and ultimately changes what we mean by “science.”

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Can you summarize one or more of the objections that philosophers and historians of science have raised to Popper’s claim? Do you get the sense that practicing philosophers think highly of Popper’s work? What Is This a Model Of? Some cellular automata are primarily mathematical artifacts. They are interesting because they are surprising, useful, or pretty, or because they provide tools for creating new mathematics (like the Church-Turing thesis). But it is not clear that they are models of physical systems. If they are, they are highly abstracted, which is to say that they are not very detailed or realistic. For example, some species of cone snail produce a pattern on their shells that resembles the patterns generated by cellular automata (see http://en.wikipedia.org/wiki/Cone_snail). It is natural to suppose that a CA is a model of the mechanism that produces patterns on shells as they grow.

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beetles, Falsifiability behavior, Explanatory Models BetterMap, Hashtables BFS, Connected Graphs, Analysis of Graph Algorithms, Dijkstra Big O notation, Order of Growth The Big Sort, Thomas Schelling bin size, Cumulative Distributions bisect module, Analysis of Search Algorithms bisection search, Analysis of Search Algorithms Bishop, Bill, Thomas Schelling boid, Boids bond percolation, Percolation bottom-up, A New Kind of Engineering bounded, Hashtables box-counting dimension, Fractals breadth-first search, Connected Graphs, Analysis of Graph Algorithms, Dijkstra brick wall, Emergence broadcast service, A New Kind of Engineering bubble sort, Analysis of Algorithms busy beaver, Universality C CA, Implementing CAs CADrawer, CADrawer caffeine, Paul Erdős: Peripatetic Mathematician, Speed Freak canonical ensemble, Percolation carrot, Boids causation, Determinism, SOC, Causation, and Prediction, Thomas Schelling Cdf class, Cumulative Distributions CDFs, Cumulative Distributions, Cumulative Distributions plotting, Cumulative Distributions cells, Universality cellular automaton, Cellular Automata centralized system, A New Kind of Engineering chaos, Determinism Church-Turing thesis, Universality circular buffer, FIFO Implementation CircularCA, CADrawer Class 3 behavior, Randomness Class 4 behavior, Universality, Conway’s Conjecture classifying cellular automata, Classifying CAs client-server architecture, A New Kind of Engineering clique, Watts and Strogatz clustering, Watts and Strogatz clustering coefficient, Watts and Strogatz color map, Implementing Life comparing algorithms, Analysis of Algorithms comparison sort, Analysis of Basic Python Operations complementary CDF, Zipf, Pareto, and Power Laws complementary distribution, Continuous Distributions complete graph, What’s a Graph?

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

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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, Benoit Mandelbrot, Bill Joy: nanobots, bioinformatics, brain emulation, Brewster Kahle, Brownian motion, business intelligence, c2.com, call centre, carbon-based life, cellular automata, Claude Shannon: information theory, complexity theory, conceptual framework, Conway's Game of Life, cosmological constant, cosmological principle, cuban missile crisis, data acquisition, Dava Sobel, David Brooks, Dean Kamen, disintermediation, double helix, Douglas Hofstadter, en.wikipedia.org, epigenetics, factory automation, friendly AI, George Gilder, Gödel, Escher, Bach, informal economy, information retrieval, invention of the telephone, invention of the telescope, invention of writing, Isaac Newton, 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, Mikhail Gorbachev, mouse model, Murray Gell-Mann, mutually assured destruction, natural language processing, Network effects, new economy, Norbert Wiener, oil shale / tar sands, optical character recognition, pattern recognition, phenotype, premature optimization, randomized controlled trial, Ray Kurzweil, remote working, reversible computing, Richard Feynman, Richard Feynman, Robert Metcalfe, Rodney Brooks, Search for Extraterrestrial Intelligence, selection bias, semantic web, Silicon Valley, Singularitarianism, speech recognition, statistical model, stem cell, Stephen Hawking, Stewart Brand, strong AI, superintelligent machines, technological singularity, Ted Kaczynski, telepresence, The Coming Technological Singularity, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Y2K, Yogi Berra

However, expressing continuous formulas in this way is an inherent complication and would violate Einstein's dictum to express things "as simply as possible, but no simpler." So the real question is whether we can express the basic relationships that we are aware of in more elegant terms, using cellular-automata algorithms. One test of a new theory of physics is whether it is capable of making verifiable predictions. In at least one important way, that might be a difficult challenge for a cellular automata-based theory because lack of predictability is one of the fundamental features of cellular automata. Wolfram starts by describing the universe as a large network of nodes. The nodes do not exist in "space," but rather space, as we perceive it, is an illusion created by the smooth transition of phenomena through the network of nodes. One can easily imagine building such a network to represent "naive" (Newtonian) physics by simply building a three-dimensional network to any desired degree of granularity.

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I don't have in hand, but I know he's there....What I see is so compelling that it can't be a creature of my imagination.62 In commenting on Fredkin's theory of digital physics, Wright writes, Fredkin ... is talking about an interesting characteristic of some computer programs, including many cellular automata: there is no shortcut to finding out what they will lead to. This, indeed, is a basic difference between the "analytical" approach associated with traditional mathematics, including differential equations, and the "computational" approach associated with algorithms. You can predict a future state of a system susceptible to the analytic approach without figuring out what states it will occupy between now and then, but in the case of many cellular automata, you must go through all the intermediate states to find out what the end will be like: there is no way to know the future except to watch it unfold....Fredkin explains: "There is no way to know the answer to some question any faster than what's going on. "...

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It sounds like a good-news/bad-news joke: the good news is that our lives have purpose; the bas news is that their purpose is to help some remote hacker estimate pi to nine jillion decimal places. 63 Fredkin went on to show that although energy is needed for information storage and retrieval, we can arbitrarily reduce the energy required to perform any particular example of information processing. and that this operation has no lower limit.64 That implies that information rather than matter and energy may be regarded as the more fundamental reality.65 I will return to Fredkin's insight regarding the extreme lower limit of energy required for computation and communication in chapter 3, since it pertains to the ultimate power of intelligence in the universe. Wolfram builds his theory primarily on a single, unified insight. The discovery that has so excited Wolfram is a simple rule he calls cellular automata rules 110 and its behavior. (There are some other interesting automata rules, but rule 110 makes the point well enough.) Most of Wolfram's analyses deal with the simplest possible cellular automata, specifically those that involve just a one-dimensional line of cells, two possible colors (black and white), and rules based only on the two immediately adjacent cells. For each transformation, the color of a cell depends only on its own previous color and that of the cell on the left and the cell on the right.

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

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

The mathematics of these reactions involves recursive computations emerging spontaneously at the edge of chaos. It looks as if nature is a lover of extreme sports. It adores pushing everything that is precious to the point of breaking up. This deeper link between the emergence of complex behaviour at criticality and recursive computations has also been demonstrated in digital computers using cellular automata, another great invention by John von Neumann. Cellular automata are patterns of 0s and 1s that evolve step-by-step according to a simple set of rules. A new pattern, or ‘generation’, of a cellular automaton emerges after each step. Points on the new patterns will be either 0 or 1 depending on their current value as well as the value of their neighbours. In the early 1980s, the English mathematician Stephen Wolfram conjectured that a particular cellular automaton called ‘Rule 110’ might be ‘Turing complete’,21 a conjecture that was later proved by Matthew Cook.

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Platonic thinking, so deeply entrenched in mathematical culture, is evidently at play here! Nevertheless, the correlation between computation and life is indisputable. It is the interpretation of this connection that polarises empiricists and idealists. Perhaps the discovery of Rule 110 is one giant step towards the discovery of a general, mathematical, law for life. There are too many things about cellular automata that make them profoundly similar to physical, living, things. By operating near the edge of chaos, cellular automata evolve with time by responding to their changing environment. They look like a form of ‘artificial life’ existing in the computer that runs the calculations that make and sustain it. Could this artificial life evolve to the point of becoming conscious? And, if so, how similar would this artificial consciousness be to ours? Imagining true AI Let us summarise what we have explored so far.

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The journey of the individual parts towards forming a self-organised system appears then to be algorithmically determined: they are ‘attracted’ to self-organisation and, ultimately, to life. We do not yet know whether this attraction is governed by a general law for biology. However, we have discovered something that seems to point towards such a law: Rule 110, a recursive algorithm that is Turing complete and lifelike – and there might be more.23 This profound correlation between cellular automata and biological phenomena suggests that life is governed by recursive computations, probably similar – or identical – to cellular automata. There is one more special feature of complex computations that is worth noting. They are fractal-like and scale-invariant. This means that they repeat themselves at every scale. From microscopic organisms to weather systems and the formation of galactic clusters nature creates similar patterns of organisation and behaviour.

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

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Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Albert Michelson, anesthesia awareness, anthropic principle, brain emulation, cellular automata, Claude Shannon: information theory, cloud computing, computer age, Dean Kamen, discovery of DNA, double helix, en.wikipedia.org, epigenetics, George Gilder, Google Earth, Isaac Newton, iterative process, Jacquard loom, Jacquard loom, John von Neumann, Law of Accelerating Returns, linear programming, Loebner Prize, mandelbrot fractal, Norbert Wiener, optical character recognition, 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

Most incompatibilists would find the concept of free will to also be incompatible with our decisions’ being essentially accidental. Free will seems to imply purposeful decision making. Dr. Wolfram proposes a way to resolve the dilemma. His book A New Kind of Science (2002) presents a comprehensive view of the idea of cellular automata and their role in every facet of our lives. A cellular automaton is a mechanism in which the value of information cells is continually recomputed as a function of the cells near it. John von Neumann created a theoretical self-replicating machine called a universal constructor that was perhaps the first cellular automaton. Dr. Wolfram illustrates his thesis with the simplest possible cellular automata, a group of cells in a one-dimensional line. At each point in time, each cell can have one of two values: black or white. The value of each cell is recomputed for each cycle. The value of a cell for the next cycle is a function of its current value as well as the value of its two adjacent neighbors.

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The reason that his book is titled A New Kind of Science is because this theory contrasts with most other scientific laws. If there is a satellite orbiting Earth, we can predict where it will be five years from now without having to run through each moment of a simulated process by using the relevant laws of gravity and solve where it will be at points in time far in the future. But the future state of class IV cellular automata cannot be predicted without simulating every step along the way. If the universe is a giant cellular automaton, as Dr. Wolfram postulates, there would be no computer big enough—since every computer would be a subset of the universe—that could run such a simulation. Therefore the future state of the universe is completely unknowable even though it is deterministic. Thus even though our decisions are determined (because our bodies and brains are part of a deterministic universe), they are nonetheless inherently unpredictable because we live in (and are part of) a class IV automaton.

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., 96–97, 98 auditory association, 77 auditory cortex, 7, 77, 97, 128 auditory information processing, 96–97, 97 auditory nerve, 97, 128 data reduction in, 138 auditory pathway, 97 autoassociation, 59–61, 133, 173 automobiles, self-driving, 7, 159, 261, 274 axons, 36, 42, 43, 66, 67, 90, 100, 113, 150, 173 as digital processors, 191 Babbage, Charles, 189–90 Bainbridge, David, 179 bandwidth, of Internet, 254 basis functions, 103–4 Bedny, Marina, 87 Bell System Technical Journal, 184 Berger, Theodore, 102 Berners-Lee, Tim, 172 Bernoulli’s principle, 5, 8 Better Angels of Our Nature: Why Violence Has Declined (Pinker), 27 Bierce, Ambrose, 66 BINAC, 189 Bing, 171 biology, 37 DNA as unifying theory of, 17 reverse-engineering of, 4–5 biomedicine, LOAR and, 251, 252, 253 Blackmore, Susan, 211 Blade Runner (film), 210 Blakeslee, Sandra, 73, 156 Blue Brain Project, 63, 80, 124–28, 125 Bombe, 187 Bostrom, Nick, 129–30, 222 Boyden, Ed, 126 brain, evolution of, 2 brain, human: analog computing in, 274 complexity of, 8–9, 181, 272 digital implants in, 243–44 digital neocortex as extension of, 172, 276 hemispheres of, 77, 224–49 LOAR as applied to, 261–63, 263, 264, 265 prediction by, 250 redundancy of, 9 reverse-engineering of, see brain, human, computer emulation of; neocortex, digital structure of, 77 brain, human, computer emulation of, 5, 7, 179–98, 273, 280 invariance and, 197 memory requirements of, 196–97 parallel processing in, 197 processing speed in, 195–96 redundancy in, 197 singularity and, 194 Turing test and, 159–60, 169, 170, 178, 191, 213, 214, 233, 276, 298n von Neumann on, 191–95 see also neocortex, digital brain, mammalian: hierarchical thinking as unique to, 2–3, 35 neocortex in, 78, 93, 286n brain plasticity, 79, 87–89, 91, 182, 193, 197, 225, 280 as evidence of universal neocortical processing, 86, 88, 152 limitations on, 88–89 brain scanning, 7, 263, 308n destructive, 264, 265, 309n–11n LOAR and, 262–63, 263, 264, 265 nondestructive, 127, 129, 264, 312n–13n noninvasive, 273 Venn diagram of, 262 brain simulations, 124–31, 262 brain stem, 36, 99 Bremermann, Hans, 316n Britain, Battle of, 187 Brodsky, Joseph, 199 Burns, Eric A., 113 busy beaver problem, 207 Butler, Samuel, 62, 199–200, 224, 248–49 Byron, Ada, Countess of Lovelace, 190, 191 California, University of, at Berkeley, 88 “CALO” project, 162 carbon atoms, information structures based on, 2 Carroll, Lewis, 109 cells, replacement of, 245, 246 cellular automata, 236–39 cerebellum, 7, 77, 103–4 uniform structure of, 103 cerebral cortex, 7–8 see also neocortex Chalmers, David, 201–2, 218, 241 “chatbots,” 161 chemistry, 37 chess, AI systems and, 6, 38–39, 165–66, 257 chimpanzees: language and, 3, 41 tool use by, 41 “Chinese room” thought experiment, 170, 274–75 Chomsky, Noam, 56, 158 Church, Alonzo, 186 Church-Turing thesis, 186 civil rights, 278 cloud computing, 116–17, 123, 246, 279–80 cochlea, 96, 97, 135, 138 cochlear implants, 243 Cockburn, David, 214 Cold Spring Harbor Laboratory, 129 Colossus, 187, 188 “common sense,” 40 communication, reliability of, 182–85, 190 communication technology, LOAR and, 253, 254 compatibilism, 234 complexity, 198, 233 of human brain, 8–9, 181, 272 modeling and, 37–38 true vs. apparent, 10–11 computation: price/performance of, 4–5, 250–51, 257, 257, 267–68, 301n–3n thinking compared with to, 26–27 universality of, 26, 181–82, 185, 188, 192, 207 Computer and the Brain, The (von Neumann), 191 computers: brain emulated by, see brain, human, computer emulation of consciousness and, 209–11, 213–15, 223 intelligent algorithms employed by, 6–7 knowledge base expanded by, 4, 246, 247 logic gates in, 185 memory in, 185, 259, 260, 268, 301n–3n, 306n–7n reliability of communication by, 182–85, 190 see also neocortex, digital “Computing Machinery and Intelligence” (Turing), 191 conditionals, 65, 69, 153, 189, 190 confabulation, 70, 217, 227, 228, 229 connectionism, 133, 191 “connectome,” 262 consciousness, 11, 199–209 cerebral hemispheres and, 226–29 computers and, 209–11, 213–15, 223, 233 Descartes on, 221–22 dualist views of, 202–3 Eastern vs.

**
Some Remarks
** by
Neal Stephenson

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

In particular, the monads’ production rule scheme clearly presages the modern concept of cellular automata. Quoting from Mercer’s work: “The Production Rule of F is a rule for the continuous production of the discrete states of F so that it instructs F about exactly what to think at every moment of F’s existence. Following Leibniz’s suggestion, if F exists from t1 to tn and has a different thought at each moment of its existence, then at every moment, there will be an instruction about what to think next. The present thought occurring at t1, together with the Production Rule, will determine what F will think at t2.” Combined with the monadic property of being able to perceive the states of all other monads, this comes close to being a mathematically formal definition of cellular automata, a branch of mathematics generally agreed to have been invented by Stanislaw Ulam and John von Neumann during the 1940s as an outgrowth of work at Los Alamos.

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Combined with the monadic property of being able to perceive the states of all other monads, this comes close to being a mathematically formal definition of cellular automata, a branch of mathematics generally agreed to have been invented by Stanislaw Ulam and John von Neumann during the 1940s as an outgrowth of work at Los Alamos. The impressive capabilities of such systems have, in subsequent decades, drawn the attention of many luminaries from the worlds of mathematics and physics, some of whom have proposed that the physical universe might, in fact, consist of cellular automata carrying out a calculation—a hypothesis known as Digital Physics, or It from Bit. 4. Leibniz insisted that each monad perceived the states of all of the others, a premise that runs counter to intuition, given that this would seem to require that an infinite amount of information be transmitted to and stored in each monad. Of all the claims of monadology, this must have seemed the easiest to refute a hundred years ago. Since then, however, it has been given a new lease on life by quantum mechanics.

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That’s a description of how all science has been done for a long time. He’s making the argument that a lot of science doesn’t necessarily fit that mold: biological science, psychology. There are plenty of cases you can point to, even in mathematics, where being able to break things down into its smallest components doesn’t really get you anywhere. It doesn’t give you an explanation that’s really worth anything. If you look at cellular automata, for example: Sure, each automaton can be explained as a unit, but that’s not what’s interesting. What’s interesting is the really complicated emergent behaviors that you can get out of a whole bunch of these things acting at once. There’s really no grid to cross that gap. Yet we’re often led to believe that these things are better understood than they are. Biologists complain that it doesn’t make much sense to talk about having “decoded” the genome when how the coding in genes is used to make proteins is still something of a mystery.

**
When Things Start to Think
** by
Neil A. Gershenfeld

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3D printing, Ada Lovelace, Bretton Woods, cellular automata, Claude Shannon: information theory, Dynabook, Hedy Lamarr / George Antheil, I think there is a world market for maybe five computers, invention of movable type, Iridium satellite, Isaac Newton, Jacquard loom, Jacquard loom, John von Neumann, 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

Like the checkers on a checkerboard, tokens that each represent a collection of molecules get moved among sites based on how the neighboring sites are occupied. This idea has come to be known as Cellular Automata (CAs). From the 1970s onward, the group of Ed Fredkin, Tomaso Toffoli, and Norm Margolus at MIT started to make special-purpose computers designed for CAs. Because these machines entirely dispense with approximations of continuous functions, they can be much simpler and faster. And because a Turing machine can be described this way, a CA can do anything that can be done with a conventional computer. A cellular automata model of the universe is no less fundamental than one based on calculus. It's a much more natural description if a computer instead of a pencil is used to work with the model. BIT BELIEFS + 133 And the discretization solves another problem: a continuous quantity can represent an infinite amount of information.

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Index adding machine, Pascal's, 131-32 Adelson, Ted, 180-81 affective states, computer's perception of, 53-54 agents, 107, 109, 116-17 airbag, smart, 170-71, 180 analog circuits, 165, 166 Analytical Engine, 125 Any Thing project, 70, 71, 73 Apple Macintosh, 139 Argonne National Laboratory, 158 ARPANET, 79 artificial intelligence, 108, 128, 129-30, 135, 201 sensory perception and, 135, 201 assembly line, 180 AT&T, 158, 203 autonomy and wearable computers, 57-58 Babbage, Charles, 124-27, 132 Barings Bank, 77, 86 bassoon, 29-32 Begin Again Again, 34 Bell Labs, 36, 162, 174 Bender, Walter, 202-3 Benioff, Paul, 158 Bennett, Charles, 159, 176, 177 Benton, Steve, 14 2 Bill of Rights, 98-99 Bill of Things' Rights, 104 Bill of Things Users' Rights, 102 Birnbaum, Joel, 52 Bitnet, 89 "bit" of information, 176 "blessing of dimensionality," 164-65 Boltzmann, Ludwig, 175 books, printed, 13-25 competing technologies, 10, 13-25 dimensions of, 20 future of computing, lesson to be derived for, 14 Gutenberg and movable metal type, 18-19 as historical artifacts, 23-24 libraries and electronic book, 20-23 lighting for reading, 15 papal bull to require certification of, 96 paper for, 15 specifications of, 13-14 state of book business, 13 universal book, 18-20 Borden, David, 30-31 218 +INDEX Boyden, Edward, 196, 197 brain, 212 brain, human, 135, 163-64 Brain Opera, 206-7 Bretton Woods Agreement, 79 Bunka Fashion College, 55 Bush, Vannevar, 139,171-74,180 Buxton, Bill, 140 buzz words, technology, 107-21 CAD software, 73 calculus, 131, 132 Caltech, 158 carbonless copy paper, 15-16 card catalogs, 20-22 Carnegie Mellon, 129 CD-ROM, 10 as competitor of printed book, 13 cello: comparison of computer mouse to violin bow, 142-43 critical reaction to digital cello, 37-38 designing a smart, 27-44, 143-44, 187 limits of classic, 33, 37 Cellular Automata (CAs), 132-33 Census Bureau, 78 central planning, 88-89 chaos theory, 109, 112-16 chess-playing computer programs, 128-30, 134-35 children: learning methods of, 137-38 LOGO programming language, 138, 147 China, Internet access in, 99 Chuang, Isaac, 160-61 Chung, joe, 34 Citron, Robert, 78 Clarke, Arthur C., 51 Clausius, Rudolf, 175 clocks, 104 clothing and wearable computers, 50, 52,55-56,61,102-3,179 coffeemaker, intelligent, 201 communications: imposing on our lives, 95, 100-2 performance limit of a channel of, 176 privacy issues and, 100-1 regulation of, 99-100 see also specific forms of communication, e.g. e-mail; telephones Communications Act of 1934, 99 Communications Assistance for Law Enforcement Act (CALEA), 208 compact disc players, 4 Compumachine, 67 computer chips: entropy and, 177 future uses of, 152 lowering the cost of, 152-56 computers: affective states and, 53-54 Babbage's contribution in developing, 124-25, 132 battle of operating systems, 146 chips, see computer chips cost of, 4, 103 desktop, 5 difficulty using, 4, 7, 103 division of industry into software and hardware, 7 ease of use, 4, 7, 103 educational use of, 201 expectations from, 4 inability to anticipate your needs, 7-8 interfaces, see interfaces, computer irritation with, 199-200 laptop, see laptop computers mainframes, see mainframes minicomputers, 52, 138 Moore's law, 155-57, 163 music and, see musiC and computers parallel, 68, 157 PCs, see personal computers (PCs) peripherals, 52-53 INDEX+ pnvacy issue and, 56-57, 100-1 productivity and, 7 pyramid of information technology, 151 quantum, 157-63, 177 software, see software speed of, 7 standards, 88-90, 126 supercomputers, 151, 177, 199 unobtrusive computing, 44, 200, 211 upgrades, 98 wearable, see wearable computers "Computing Machinery and Intelligence," 128, 135 consciousness, quantum mechanics to describe human, 130-31 Constitution, U.S., 98-99 Copernicus, 113-14 copyrights, 181 Creapole, 55 credit cards: electronic commerce and, 80-81 privacy and use of, 100-1 reflective holograms on, 142 cryptography, 80-81, 156, 207-8 "curse of dimensionality," 164 Daiwa Bank, 77, 86 Darwin, Charles, 125 Data Glove, 49 "Deep Blue," 129-30 "Deep Thought," 129 Defense Advanced Research Projects Agency (DARPA), 79, 129 derivative~ 78, 85-86 Deutsch, David, 158 Deutsche Telekom, 203 developing countries, 210-11 Dickinson, Becton, 204 Difference Engine, 124-25, 132 digital evolution, 10 digital money, see smart money digital representation, effect of time and use on, 5-6 219 Digital Revolution: disturbance resulting from, 10 promise and reality of, 3, 5 disabled, wearable computers and, 58 discovery, the business of, 169-84 Disney, 203 distance learning, 19 3 distribution of wealth, 78 division of labor between people and machines, 8 DNA molecules, 157 Domus, 55 Doom (computer game), 89 Dynabook, 138 e-broidery, 55 Economist, 115 economy, electronic, 79 education: classroom, 188, 197 departmental organization of, 190-91 distance learning, 193 just-in-time, 192 local learning, 193 at Massachusetts Institute of Technology (MIT) Media Lab, 187-97 use of computers for, 201 Einstein's theory of relativity, 178 electronic books, 15-25, 38, 72 electronic commerce, 80-81, 152, 156 cryptography and, 80-81 paying-as-you-go, 82 electronic funds transfers, 80 electronic ink, 16, 17, 200 universal book and, 18-20 e-mail, 101-2, 104-6 encryption, 80-81 Engelhart, Doug, 139 English Bill of Rights, 98 entanglement, 159 entropy, 175, 176, 177, 188-90 "Entschedidungsproblem," 127 Equifax, 101 220 + Ernst, Richard R.

**
Accelerando
** by
Stross, Charles

Amazon: amazon.com — amazon.co.uk — amazon.de — amazon.fr

call centre, carbon-based life, cellular automata, cognitive dissonance, commoditize, Conway's Game of Life, dark matter, dumpster diving, Extropian, finite state, Flynn Effect, glass ceiling, gravity well, John von Neumann, knapsack problem, Kuiper Belt, Magellanic Cloud, mandelbrot fractal, market bubble, means of production, packet switching, performance metric, phenotype, planetary scale, Pluto: dwarf planet, reversible computing, Richard Stallman, SETI@home, Silicon Valley, Singularitarianism, slashdot, South China Sea, stem cell, technological singularity, telepresence, The Chicago School, theory of mind, Turing complete, Turing machine, Turing test, upwardly mobile, Vernor Vinge, Von Neumann architecture, web of trust, Y2K, zero-sum game

He's not sure Pamela ever let him see her fully naked: She thought skin was more sexy when it was covered. Annette squeezes him again, and he stiffens. "More!" By the time they finish, he's aching, and she shows him how to use the bidet. Everything is crystal clear, and her touch is electrifying. While she showers, he sits on the toilet seat lid and rants about Turing-completeness as an attribute of company law, about cellular automata and the blind knapsack problem, about his work on solving the Communist Central Planning problem using a network of interlocking unmanned companies. About the impending market adjustment in integrity, the sinister resurrection of the recording music industry, and the still-pressing need to dismantle Mars. When she steps out of the shower, he tells her that he loves her. She kisses him and slides his glasses and earpieces off his head so that he's really naked, sits on his lap, and fucks his brains out again, and whispers in his ear that she loves him and wants to be his manager.

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Each of these companies – and there are currently more than sixteen thousand of them, although the herd is growing day by day – has three directors and is the director of three other companies. Each of them executes a script in a functional language Manfred invented; the directors tell the company what to do, and the instructions include orders to pass instructions on to their children. In effect, they are a flock of cellular automata, like the cells in Conway's Game of Life, only far more complex and powerful. Manfred's companies form a programmable grid. Some of them are armed with capital in the form of patents Manfred filed, then delegated rather than passing on to one of the Free Foundations. Some of them are effectively nontrading, but occupy directorial roles. Their corporate functions (such as filing of accounts and voting in new directors) are all handled centrally through his company-operating framework, and their trading is carried out via several of the more popular B2B enabler dot-coms.

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Boris lumbers round in place to face her; today he's wearing a velociraptor, and they don't turn easily in confined spaces. He snarls irritably: "Give me some space!" He coughs, a threatening noise from the back of his wattled throat, "Searching the sail's memory now." The back of the soap-bubble-thin laser sail is saturated with tiny nanocomputers spaced micrometers apart. Equipped with light receptors and configured as cellular automata, they form a gigantic phased-array detector, a retina more than a hundred meters in diameter. Boris is feeding them patterns describing anything that differs from the unchanging starscape. Soon the memories will condense and return as visions of darkness in motion – the cold, dead attendants of an aborted sun. "But where is it going to be?" asks Sadeq. "Do you know what you are looking for?"

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

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

Emergence relates to the dynamic nature of interactions between components in a system (Gallegati and Kirman, 2012). The dynamic character of emergent phenomena is not a property of a pre-established, given whole - but arises and becomes apparent as a complex system evolves over time (Goldstein, 1999). Complexity in a system can arise, after all, from simple rules - this is seen in examples such as cellular automata, neural networks and genetic algorithms (Refer Notes). This is because of the non-linearity of the systems relations. As the system becomes complex, emergence manifests itself in the form of self- organization. In other words, no external forces are needed for the system to take on certain properties and traits and these systemic properties arise from far-fromequilibrium conditions (Morçöl, 2008).

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All equations are closely based on assumptions that households maximize their own welfare and firms maximize profits. Examples are models developed by Kydland and Prescott and by Christiano and Eichenbaum. Vector autoregression (VAR) models employ a small number of estimated equations to summarize the dynamic behaviour of the entire macroeconomy, with few restrictions from economic theory beyond the choice of variables to include in the model. Sims is the original proponent of this type of model. Cellular automata (CA): “Automaton” (plural: “automata") is a technical term used in computer science and mathematics for a hypothetical machine that changes its internal state based on inputs and its previous state. (Sayama, 2015). A cellular automaton consists of a regular grid of cells, each in one of a finite number of states, such as on and off. Each cell is surrounded by a set of cells called it neighbourhood.

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Bheemaiah, The Blockchain Alternative, DOI 10.1007/978-1-4842-2674-2 241 ■ INDEX Capitalism (cont.) cashlessenvironment (see (Multiple currencies)) categories, 88 classification, 88 definition of, 83 de-skilling process, 91 economic hypothesis, 86 education and training levels, 89 EMN, 88 fiat currency, 123 CBDC, 129 commercial banks, 129 debt-based money, 124 digital cash, 129 digital monetary framework, 125 fractional banking system, 124 framework, 124 ideas and methods, 130 non-bank private sector, 124 sovereign digital currency, 125–128 transition, 124 fiscal policy, 136 cashless environment, 136 central bank, 136 concept of, 136 control spending, 138 definition of, 140 exogenous and endogenous function, 137 fractional banking system, 137 Kelton, Stephanie, 139 near-zero interest rates, 136 policy instrument, 136 QE and QQE, 138 tendency, 136 ultra-low inflation, 136 helicopter drops business insider, 141 ceteris paribus, 142 Chatbots, 140–141 Chicago Plan, 145 comparative charts, 142 fractional banking, 145 keywords, 140 technology, 143 UBI, 143–144, 146 higher-skilled workers, 91 ICT technology, 85 industry categories, 90 242 Jiggery Pokery accounts, 106 advantages, 111 bias information, 106 Blockchain, 107 CFTC, 109 digital environment, 108 Enron scandal, 106 limitations, 107 private/self-regulation, 107 public function, 107 regulatory framework, 108 tech-led firms, 109 lending and payments CAMELS evaluation, 94 consumers and SMEs, 95 cryptographic laws, 97 fundamental limitations, 96 governments, 98 ILP, 97 KYB process, 97 lending sector, 95 mobile banking, 96 payments industry, 96 regulatory pressures, 95 rehypothecation, 96 ripple protocol, 97 sectors share, 94 leveraging effect technology, 88 marketing money, 119 cashless system, 120 crime and taxation, 123 economy, 122 IRS, 121 money, 119 Seigniorage, 122 tax evasion, 121 markets and regulation, 84 market structure, 92–93 multiple currency mechanisms, 153 occupational categories, 90 ONET database, 89 policies, 112 economic landscape, 112 financialization, 113 monetary and fiscal policy, 112 money creation methods, 114 The Chicago Plan, 114 transformation, 113 probabilities, 148 regulation, 105 routine and non-routine, 88 ■ INDEX routinization hypothesis, 88 Sarbanes-Oxley Act, 153 SBTC, 92 scalability issue, 152 skill-biased employment, 89 skills and technological advancement, 87 skills downgrading process, 91 trades (see (Trade finance)) UBI Alaska, 147 deployment, 148 Mincome, Canada, 147 Namibia, 147 Cashless system, 120 Cellular automata (CA), 221 Central bank digital currency (CBDC), 125–128 Centre for Economic Policy Research (CEPR), 177 Chicago Plan, 145 Clearing House Interbank Payments System (CHIPS), 48 Collateralised Debt Obligations (CDOs), 29 Collateralized Loan Obligations (CLOs), 29 Complexity economics agent, 193–195 challenges, 184 consequential decisions, 184 deterministic and axiomatized models, 184 dynamics, 187 education, 186 emergence, 192 exogenous and endogenous changes, 184 feedback loops, 191 information affects agents, 185 macroeconoic movements, 182 network science, 189–190 non-linearity, 187 path dependence, 192 power laws, 188 self-adapting individual agents, 185 technology andinvention (see (Technology and invention)) Walrasian approach, 185 Computing, 218–220 Congressional Research Service (CRS), 2 Constant absolute risk aversion (CARA), 206 Contingent convertible (CoCo), 95, 151 Credit Default Swaps (CDSs), 29, 32 CredyCo, 69 Cryptid, 69 Cryptographic law, 97 Currency mechanisms, 153 Current Account Switching System (CASS), 73 D Data analysis techniques, 163 Debt and money broad and base money, 10 China’s productivity, 18 credit, 14 economic pressures, 13 export-led growth, 17 fractional banking,13 (see also (Fractional Reserve banking)) GDP growth, 18 households, 14–15 junk bonds, 11 long-lasting effects, 15 private and public sectors, 16 problems, 19 pubilc and private level, 17 reaganomics, 11 real estate industry, 14, 19 ripple effects, 18 security and ownership, 13 societal level, 17 UK, 10 DigID, 78 Digital trade documents (DOCS), 99 Dodd-Frank Act, 34, 35, 105 Dynamic Stochastic General Equilibrium (DSGE) model, 22, 167, 168 E EBM.

pages: 410 words: 119,823

**
Radical Technologies: The Design of Everyday Life
** by
Adam Greenfield

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

These copies would immediately set about making further copies, underwriting an exponential increase in production capacity. Von Neumann’s constructors existed in an entirely virtual universe of possibility. At the time he imagined them, there wasn’t enough computing power in the world to simulate their behavior, let alone physically realize them as anything other than painstakingly inked grids of pen on paper, so-called cellular automata.2 But with its implication of a continuously and geometrically expanding productivity, his vision of a universal constructor inspired generations of engineers. Sometime around the turn of the twenty-first century, one of them—a mechanical engineering professor at the University of Leeds named Adrian Bowyer, troubled by the thought of a world riven by material scarcity—finally took von Neumann at his word.

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Casey Newton, “Seattle dive bar becomes first to ban Google Glass,” CNET, March 8, 2013. 23.Dan Wasserman, “Google Glass Rolls Out Diane von Furstenberg frames,” Mashable, June 23, 2014. 4Digital fabrication 1.John Von Neumann, Theory of Self-Reproducing Automata, Urbana: University of Illinois Press, 1966, cba.mit.edu/events/03.11.ASE/docs/VonNeumann.pdf. 2.You may be familiar with cellular automata from John Conway’s 1970 Game of Life, certainly the best-known instance of the class. See Bitstorm.org, “John Conway’s Game of Life,” undated, bitstorm.org. 3.Adrian Bowyer, “Wealth Without Money: The Background to the Bath Replicating Rapid Prototyper Project,” February 2, 2004, reprap.org/wiki/Wealth_Without_Money; RepRap Project, “Cost Reduction,” December 30, 2014, reprap.org/wiki/Cost_Reduction.

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., 103 Brown, Joshua, 223–4, 254 Brown, Michael, 231 “buddy punching,” 198 bullshit jobs, 203, 205 Bui, Quoctrung, 192–3 bushido, 266–7 Bushido Project, the, 266 Business Microscope, 197 Buterin, Vitalik, 147–50, 152, 154, 162–4, 167, 169, 172, 175, 177, 179, 303, 311 Byzantium, 69 CAD-Coin, 157 Californian Ideology, the, 283 Carmack, John, 82 cartography, 20 cats, 214 CCTV, 49–50, 54, 241 cellular automata, 86 Champs-Élysées, 1 Chaum, David, 121 Checkpoint Charlie, 70 chess, 263 Chevrolet Camaro, 216–18 Chicago Police Department, 230–1 China, 87, 102, 190, 194, 278–9, 286, 290, 306 Churchill, Winston, 28 circular economy, 92, 96, 99, 288 Ciutat Meridiana, Barcelona neighborhood, 109 climax community, 289 Cockney rhyming slang, 311 code library, 274–5 commons, the, 171–3 computer numerical control, CNC milling, 86, 93, 95, 97, 108, 110, 273 Container Store, 196 cooperatives, 171 cooperative motility, 80 Copenhagen, 31, 51 Cornell Law School, 151 Cortana virtual assistant, 39 Costco, 45 cozy catastrophe, 291 cradle-to-cradle industrial ecosystem.

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

Amazon: amazon.com — amazon.co.uk — amazon.de — amazon.fr

Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, Brownian motion, cellular automata, Claude Shannon: information theory, Columbine, cosmic microwave background, cosmological constant, cosmological principle, dark matter, dematerialisation, double helix, en.wikipedia.org, gravity well, Harlow Shapley and Heber Curtis, Henri Poincaré, Isaac Newton, John von Neumann, Lao Tzu, lone genius, New Journalism, Norbert Wiener, pets.com, Pierre-Simon Laplace, Richard Feynman, Richard Feynman, Richard Stallman, Schrödinger's Cat, Slavoj Žižek, Stephen Hawking, stochastic process, the scientific method, wikimedia commons

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

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bosons bouncing-universe cosmology boundary conditions and cause and effect described and initial conditions of the universe and irreversibility and Maxwell’s Demon and recurrence theorem and time symmetry Bousso, Raphael Brahe, Tycho branes Brillouinéon brown dwarfs Brownian motion Bruno, Giordano bubbles of vacuum Buddhism Bureau of Longitude Callender, Craig Callisto caloric Calvin, John Calvino, Italo Carnot, Lazare Carnot, Nicolas Léonard Sadi Carrey, Jim Carroll, Lewis cause and effect celestial mechanics cellular automata CERN C-field Chandrasekhar Limit chaotic dynamics The Character of Physical Law (Feynman) charge charge conjugation checkerboard world exercise and arrow of time background of and conservation of information and Hawking radiation and holographic principle and information loss and interaction effects and irreversibility and Principle of Indifference and symmetry and testing hypotheses chemistry Chen, Jennifer choice Chronology Protection Conjecture circles in time.

**
Chaos
** by
James Gleick

Amazon: amazon.com — amazon.co.uk — amazon.de — amazon.fr

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

When Yaneer Bar-Yam wrote a kilopage textbook, Dynamics of Complex Systems, in 2003, he took care of chaos proper in the first section of the first chapter. (“The first chapter, I have to admit, is 300 pages, okay?” he says.) Then came Stochastic Processes, Modeling Simulation, Cellular Automata, Computation Theory and Information Theory, Scaling, Renormalization, and Fractals, Neural Networks, Attractor Networks, Homogenous Systems, Inhomogenous Systems, and so on. Bar-Yam, the son of a high-energy physicist, had studied condensed matter physics and become an engineering professor at Boston University, but he left in 1997 to found the New England Complex Systems Institute. He had been exposed to Stephen Wolfram’s work on cellular automata and Robert Devaney’s work in chaos and discovered that he was less interested in polymers and superconductors than in neural networks and—he says this with no sense of grandiosity—the nature of human civilization.

**
Is God a Mathematician?
** by
Mario Livio

Amazon: amazon.com — amazon.co.uk — amazon.de — amazon.fr

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

Most mathematicians agree that mathematics as we know it has evolved from the basic branches of geometry and arithmetic that were practiced by the ancient Babylonians, Egyptians, and Greeks. However, was it truly inevitable that mathematics would start with these particular disciplines? Computer scientist Stephen Wolfram argued in his massive book A New Kind of Science that this was not necessarily the case. In particular, Wolfram showed how starting from simple sets of rules that act as short computer programs (known as cellular automata), one could develop a very different type of mathematics. These cellular automata could be used (in principle, at least) as the basic tools for modeling natural phenomena, instead of the differential equations that have dominated science for three centuries. What was it, then, that drove the ancient civilizations toward discovering and inventing our special “brand” of mathematics? I don’t really know, but it may have had much to do with the particulars of the human perceptual system.

pages: 293 words: 88,490

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

asset allocation, bank run, bitcoin, butterfly effect, 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, disintermediation, Edward Lorenz: Chaos theory, epigenetics, feminist movement, financial innovation, fixed income, Flash crash, Henri Poincaré, 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, Richard Feynman, risk/return, Saturday Night Live, self-driving car, 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

“Investment under Uncertainty.” Econometrica 39, no. 5: 659–81. doi: 10.2307/1909571. Luria, A. R. 1968. The Mind of a Mnemonist: A Little Book about a Vast Memory. Trans. Lynn Solotaroff. New York: Basic Books. Lynch, Peter. 2008. “The Origins of Computer Weather Prediction and Climate Modeling.” Journal of Computational Physics 227: 3431–44. doi: 10.1016/j.jcp.2007.02.034. Maerivoet, Sven, and Bart De Moor. 2005. “Cellular Automata Models of Road Traffic.” Physics Report 419, no. 1: 1–64. doi: 10.1016/j.physrep.2005.08.005. Majdandzic, Antonio, Boris Podobnik, Sergey V. Buldyrev, Dror Y. Kenett, Shlomo Havlin, and H. Eugene Stanley. 2014. “Spontaneous Recovery in Dynamical Networks.” Nature Physics 10, no. 1: 34–38. doi: 10.1038/nphys2819. Martel, Robert. 1996. “Heterogeneity, Aggregation, and a Meaningful Macroeconomics.”

…

See bank/dealer bank/dealer, 135; derivatives desk of, 135–136; during crises, 187; failure of, 135; and funding, 135–136; and heuristics, 135–136; market making by, 135–136; prime broker of, 135; structure of, 131; trading desk of, 135–136 Basel Committee on Banking Supervision, 156 Bear Stearns, 10, 160; Goldman Sachs and the failure of, 167; market’s loss of confidence in, 167; use of repo for funding, 166 Bear Stearns Asset Management (BSAM), 161; collateral seized by Merrill Lynch, 162–163; Enhanced Leverage Fund, 162–163; hedge funds’ bankruptcy, 166–167 Becker, Gary, 81, 182 behavioral economics, 42, 102 Beinhocker, Eric, 89–90, 114, 175 Bentham, Jeremy, 6 Bernanke, Ben, 10–11 Big Short, The, 185 boids, 104 Borges, Jorge Luis, 182; The Art of Cartography, 25; Funes, the Memorious, 75 (see also Funes, the Memorious); The Library of Babel, 61–63 (see also Library of Babel); and example of Suarez Miranda, 25; Tlön, Uqbar, Orbis Tertius, 92–93 Bousquet, Antoine, 174 Boyd, John, 173–174; at the Air War College, 173; and ambiguity in warfare, 174; and Boyd Cycle, 119 (see also OODA loop); F-86 sabre strategy and, 119; at Fighter Weapons School, 119; and development of the OODA loop, 119, 179 (see also Boyd Cycle); and the Strategic Game of ? and ?, 118–119, 174 Calvinism, 58 Cambridge University Press, 52 cascades: and the financial crisis of 2008, 159–160 (see also financial crisis of 2008); fire sales and, 140; liquidity during, 128, 152 (see also liquidity); margin calls during, 14; occurrence of, 159; portfolio insurance and, 146–147; cash providers, 136 CDOs, 161, 164 cellular automata, 37, 95, 97–98 chaos, 29; limits to knowledge and, 51 chatbot. See MGonz Chernobyl, nuclear accident of, 112 Church, Alonzo, 54 Citigroup, 11, 166 Clower, Robert, 85 cockroach, 68, 74; defense mechanism of, 66; and omniscient planner, 66–67 Coleman, Henry, 5 collateral: haircuts and, 131; risk reduction of, 204; transformations of, 131 commercial paper, 136 Commodity Futures Trading Commission (CFTC), 147–148 complexity: and chaos theory, 110–111; in comparison to computational irreducibility, 108, 122; description of, 109–112; and emergence, 108, 122; and ergodicity, 111, 122; and financial crises, 112 (see also financial crises); and informational irreducibility, 109–110; investigation of by Gotfried Wilhelm Leibniz, 109; and neoclassical economics, 123–124 (see also neoclassical economics); and network theory, 110; and nonlinear systems, 110–111; and the OODA loop, 122 (see also OODA Loop); and radical uncertainty, 112, 122; and strategic complexity, 122–124 computational irreducibility, 12, 18, 33; crises and, 105; and heuristics, 65; and the Library of Babel, 62–63; and maps, 26; and mathematical shortcuts, 26; and neoclassical economics, 83 (see also neoclassical economics); and three-body problem, 27–28 (see also three-body problem); and Turing’s halting problem, 55 computers, and the universal Turing machine, 54.

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

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

His description (posthumously published, 1966) of how an automaton would read its own blueprint and then copy it into its new creation anticipated in impressive detail many of the later discoveries about the mechanisms of DNA expression and replication, but in order to make his proof of the possibility of a self-reproducing automaton mathematically rigorous and tractable, von Neumann had switched to simple, two-dimensional abstractions, now known as cellular automata. Conway's Life-world cells are a particularly agreeable example of cellular automata. Conway and his students wanted to confirm von Neumann's proof in detail by actually constructing a two-dimensional world with a simple physics in which such a self-replicating construction would be a stable, working structure. Like von Neumann, they wanted their answer to be as general as possible, and hence as independent as possible of actual (Earthly?

…

The task of the wise God required to put this world into motion is a task of discovery, not creation, a job for a Newton, not a Shakespeare. What Newton found — and what Conway found — are eternal Platonic fixed points that anybody else in principle could have discovered, not idiosyncratic creations that depend in any way on the particularities of the minds of their authors. If Conway had never turned his hand to designing cellular-automata worlds — if Conway had never even existed — some other mathematician might very well have hit upon exactly the Life world that Conway gets the credit for. So, as we follow the Darwinian down this path, God the Artificer turns first into God the Lawgiver, who now can be seen to merge with God the Lawfinder. God's hypothesized contribution is thereby becoming less personal — and hence more readily performable by something dogged and mindless!

**
Singularity Sky
** by
Stross, Charles

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anthropic principle, cellular automata, Conway's Game of Life, cosmological constant, Doomsday Clock, Extropian, gravity well, Kuiper Belt, life extension, means of production, new economy, phenotype, prisoner's dilemma, skinny streets, technological singularity, uranium enrichment

She'd spoken to Martin about it, piecing together his information with her own. Together they'd pieced together a terrifying hypothesis. "Herman was unusually vague about it," Martin admitted. "Normally he has a lot of background detail. Every word means something. But it's as if he doesn't want to say too much about the Festival. They're—he called them, uh, glider-gun factories. I don't know if you know about Life—" "Cellular automata, the game?" "That's the one. Glider guns are mobile cellular automata. There are some complex life structures that replicate themselves, or simpler cellular structures; a glider-gun factory is a weird one. It periodically packs itself into a very dense mobile system that migrates across the grid for a couple of hundred squares, then it unpacks itself into two copies that then pack down and fly off in opposite directions. Herman said that they're a real-space analogue: he called them a Boyce-Tipler robot.

**
Practical OCaml
** by
Joshua B. Smith

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cellular automata, Debian, domain-specific language, general-purpose programming language, Grace Hopper, hiring and firing, John Conway, Paul Graham, slashdot, text mining, Turing complete, type inference, web application, Y2K

The third is the logical and of the sample and the random (Figure 27-4). Figure 27-2. Random BMP 620Xch27final.qxd 9/22/06 1:22 AM Page 389 CHAPTER 27 ■ PROCESSING BINARY FILES Figure 27-3. xor BMP Figure 27-4. and BMP 389 620Xch27final.qxd 390 9/22/06 1:22 AM Page 390 CHAPTER 27 ■ PROCESSING BINARY FILES Conway’s Game of Life In 1970, a British mathematician named John Conway created the field of cellular automata when he published the first article on the subject. Conway’s “game” isn’t so much a game played by people as it is a mathematical experiment. The game is an example of emergent behavior because there are only four simple rules that generate an amazing amount of complexity. Conway’s game is also Turing Complete, which means that (given the right initial conditions) the game is as powerful as any “real” computer.

…

See primitive types batch compilers, 405 Bayes’ Theorem, 169 binary files bitmaps and, 383–389 comparing two, 380–383 outputting, 377 parsing, 295 processing, 375– 399 reading, 383–389 bitmap header definitions, 384 blog server example, 278–288 BNF (Backus-Naur Form), 210 Boolean type (bool), 67 bottom-up design, 267 bprintf function, 76 broadcast function, 318 bscanf function, 77, 253 buffers, 80, 110 build tools, 401–409 buildmap function, 172 build_list function, 324 445 620Xidxfinal.qxd 446 9/22/06 4:19 PM Page 446 ■INDEX built-in exceptions, 125, 131 built-in functions, 48 built-in types, 24 buy function, for securities trades database, 54 ■C C code, interfacing with, 349–358 -c compiler flag, 405 .c files, 408 C functions, defining, 352–355 C preprocessor (cpp), 411 C++ Foreign Function Interfaces and, 349 polymorphic classes and, 26 templates and, 25, 160 calculators four-function, 42 guards and, 48 Calendar module, 360 CAM (Categorical Abstract Machine), 3 CAM-ML, 3 Cameleon, 14 Caml Light, 3 Caml Special Light, 4 camlbrowser, 402, 405 CamlIDL library, 359 camlidl tool, 349, 355, 357 Camlp4, 411–429 camlp4o command, 418, 425 CAMLparam macro, 352 CAMLprim, 362 caml_alloc data, 352 caml_alloc_string(length) function, 351 caml_alloc_string(n) function, 352 caml_alloc_tuple(n) function, 352 caml_copy_double(d) function, 352 caml_copy_double(initial_value) function, 352 caml_copy_string(str) string, 352 caml_failwith(argument_string) function, 352 caml_invalid_argument(argument_string) function, 352 caml_raise_end_of_file (void) exception, 352 caml_raise_not_found ( void ) exception, 352 Capability Maturity Model (CMM), 271 Categorical Abstract Machine (CAM), 3 -cc <CCNAME> flag, 406 -cclib -lLIBNAME flag, 406 -ccopt OPTION flag, 406 cellular automata, 390 CGI (Common Gateway Interface), 273–291 advantages/disadvantages of, 274 writing your own functions and, 277–284 channels, 52, 113–117 chars, 64, 377 check_suffix function, 137 choose function, 320 chop_extension function, 137 chop_suffix function, 137 Church, Alonzo, 263 class keyword, 226, 228 classes, 25, 225–229 internal, 233 vs. objects, 226 parameterized, 234 polymorphism and, 230 reasons for using, 227 virtual, 234, 241 client class, 334 client functions, 189 clients, OCaml support for, 179–191 client_app.ml file, 190 cloning objects, 241 close_in function, 114 close_out function, 114 .cma files, 20, 408 .cmi files, 20 CMM (Capability Maturity Model), 271 .cmo files, 20, 408 Cocanwiki web application, 291 code linking options for, 356 coding rules and, 130–133 obtaining line numbers/function names and, 134 ocamllex processing and, 197–201, 222 ocamlyacc processing and, 206, 222 reuse and, 225–228, 267 code completion, 14 code files, 12, 18 collapse function, 46 collections, 89–111 combine function, 96 command-line flags, 311 command-line toplevel, 13 comments documentation extracted from, 145 importance of, 154 ocamldoc for, 146 Common Gateway Interface.

**
Blockchain: Blueprint for a New Economy
** by
Melanie Swan

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

One possible path is bringing existing non-AI and non-blockchain rule-based systems onto the blockchain to further automate and empower their operations. This could include systems like chaining together simple if-this-then-that (or IFTTT) behavior and the open source Huginn platform for building agents that monitor situations and act on your behalf. A second possible path is implementing programmatic ideas from AI research fields such as Wolfram’s cellular automata, Conway’s Game of Life, Dorigo’s Ant Colony Optimization and Swarm Intelligence, Andy Clark’s embodied cognitive robots, and other general agent-based systems. Chapter 3. Blockchain 3.0: Justice Applications Beyond Currency, Economics, and Markets Blockchain Technology Is a New and Highly Effective Model for Organizing Activity Not only is there the possibility that blockchain technology could reinvent every category of monetary markets, payments, financial services, and economics, but it might also offer similar reconfiguration possibilities to all industries, and even more broadly, to nearly all areas of human endeavor.

**
Masterminds of Programming: Conversations With the Creators of Major Programming Languages
** by
Federico Biancuzzi,
Shane Warden

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Benevolent Dictator For Life (BDFL), business intelligence, business process, cellular automata, cloud computing, commoditize, complexity theory, conceptual framework, continuous integration, data acquisition, domain-specific language, Douglas Hofstadter, Fellow of the Royal Society, finite state, Firefox, follow your passion, Frank Gehry, general-purpose programming language, Guido van Rossum, HyperCard, information retrieval, iterative process, John von Neumann, Larry Wall, linear programming, loose coupling, Mars Rover, millennium bug, NP-complete, Paul Graham, performance metric, Perl 6, QWERTY keyboard, RAND corporation, randomized controlled trial, Renaissance Technologies, Ruby on Rails, Sapir-Whorf hypothesis, Silicon Valley, slashdot, software as a service, software patent, sorting algorithm, Steve Jobs, traveling salesman, Turing complete, type inference, Valgrind, Von Neumann architecture, web application

So here was a promising idea, but it just didn’t quite work in the long run. I pulled some of those ideas into UML, but data flow architecture doesn’t seem to replace von Neumann architecture in most cases. So I had my shot and didn’t quite make it. There are also cellular automata. I think over half of my fellow grad students tried to build on them a highly parallel computer. That has to be the right approach, because that’s how the universe is constructed. (Or maybe not. Modern physics is stranger than fiction. The latest speculations suggest that space and time arise out of something more primitive.) But cellular automata seem suited to only certain geometric problems, very important problems to be sure, but not general-case problems. People haven’t figured out how to program them for the general case. Maybe there is no general case. The critical issue seems to be the interface between control flow and data structure.

**
Mathematics for Finance: An Introduction to Financial Engineering
** by
Marek Capinski,
Tomasz Zastawniak

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Black-Scholes formula, Brownian motion, capital asset pricing model, cellular automata, delta neutral, discounted cash flows, discrete time, diversified portfolio, fixed income, interest rate derivative, interest rate swap, locking in a profit, London Interbank Offered Rate, margin call, martingale, quantitative trading / quantitative ﬁnance, random walk, short selling, stochastic process, time value of money, transaction costs, value at risk, Wiener process, zero-coupon bond

Springer-Verlag: Mathematica in Education and Research Vol 4 Issue 3 1995 article by Roman E Maeder, Beatrice Amrhein and Oliver Gloor ‘Illustrated Mathematics: Visualization of Mathematical Objects’ page 9 ﬁg 11, originally published as a CD ROM ‘Illustrated Mathematics’ by TELOS: ISBN 0-387-14222-3, German edition by Birkhauser: ISBN 3-7643-5100-4. Mathematica in Education and Research Vol 4 Issue 3 1995 article by Richard J Gaylord and Kazume Nishidate ‘Trafﬁc Engineering with Cellular Automata’ page 35 ﬁg 2. Mathematica in Education and Research Vol 5 Issue 2 1996 article by Michael Trott ‘The Implicitization of a Trefoil Knot’ page 14. Mathematica in Education and Research Vol 5 Issue 2 1996 article by Lee de Cola ‘Coins, Trees, Bars and Bells: Simulation of the Binomial Process’ page 19 ﬁg 3. Mathematica in Education and Research Vol 5 Issue 2 1996 article by Richard Gaylord and Kazume Nishidate ‘Contagious Spreading’ page 33 ﬁg 1.

**
Bad Data Handbook
** by
Q. Ethan McCallum

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Amazon Mechanical Turk, asset allocation, barriers to entry, Benoit Mandelbrot, business intelligence, cellular automata, chief data officer, Chuck Templeton: OpenTable, cloud computing, cognitive dissonance, combinatorial explosion, commoditize, conceptual framework, database schema, en.wikipedia.org, Firefox, Flash crash, Gini coefficient, illegal immigration, iterative process, labor-force participation, loose coupling, natural language processing, Netflix Prize, quantitative trading / quantitative ﬁnance, recommendation engine, selection bias, sentiment analysis, statistical model, supply-chain management, survivorship bias, text mining, too big to fail, web application

The Delicate Sound of a Combinatorial Explosion… We’ve introduced the problem and sketched out a rudimentary solution in just a few pages, but imagine how a real system like this might evolve over an extended period of months or even years with a team of people involved. It’s easy to see how the complexity could be overlooked or taken for granted as the nature of the problem we set out to solve. A system can start out simple, but very quickly become complex. This fact has been deeply explored in the study of complex systems and cellular automata. To see this idea in action, consider a classic technique for defining a complex graphical object by starting with two simple objects: “One begins with two shapes, an initiator and a generator…each stage of the construction begins with a broken line and consists in replacing each straight interval with a copy of the generator, reduced and displaced so as to have the same end points as those of the interval being replaced.”

**
All Your Base Are Belong to Us: How Fifty Years of Video Games Conquered Pop Culture
** by
Harold Goldberg

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Alexey Pajitnov wrote Tetris, Apple II, cellular automata, Columbine, Conway's Game of Life, game design, In Cold Blood by Truman Capote, Mars Rover, Mikhail Gorbachev, Ralph Waldo Emerson, Ray Oldenburg, Saturday Night Live, Silicon Valley, Steve Jobs, Steve Wozniak, The Great Good Place, Thorstein Veblen, urban planning

As well, when Maxis was still a public company, Braun had shown Wright a 1985 Activision game for the Apple II called Little Computer People. Little Computer People was occasionally hilarious and featured a slow-moving cartoonlike character called Darren who would write you letters saying, “I have many hobbies that occupy my time.” To prove it, he watched TV, exercised, and searched for someone to live in his computer with him. Finally, Wright was impressed with John Horton Conway’s theories of cellular automata, which were espoused in The Game of Life. In his 1970s simulation game, Conway showed that you could emulate the complex patterns of the birth and death of organisms living together in society—and everything in between. All these combined to influence Wright as he dreamed up a project whose working title was Home Tactics, the Experimental Domestic Simulator. Wright later tweaked the name to the slightly more appealing Dollhouse.

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

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3D printing, AI winter, Amazon Web Services, artificial general intelligence, Asilomar, Automated Insights, Bayesian statistics, Bernie Madoff, Bill Joy: nanobots, brain emulation, cellular automata, Chuck Templeton: OpenTable, cloud computing, cognitive bias, commoditize, computer vision, cuban missile crisis, Daniel Kahneman / Amos Tversky, Danny Hillis, data acquisition, don't be evil, drone strike, Extropian, finite state, Flash crash, friendly AI, friendly fire, Google Glasses, Google X / Alphabet X, Isaac Newton, Jaron Lanier, John Markoff, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, Loebner Prize, lone genius, mutually assured destruction, natural language processing, Nicholas Carr, optical character recognition, PageRank, pattern recognition, Peter Thiel, prisoner's dilemma, Ray Kurzweil, Rodney Brooks, 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 Wozniak, strong AI, Stuxnet, 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

Humans should not stand in the way: Kristof, Nicholas D., “Robokitty,” New York Times Magazine, August 1, 1999. In fact, de Garis: De Garis, Hugo, Brain Builder Group, Evolutionary Systems Department, ATR Human Information Processing Research Laboratories, “CAM-BRAIN The Evolutionary Engineering of a Billion Neuron Artificial Brain by 2001 which Grows/Evolves at Electronic Speeds inside a Cellular Automata Machine (CAM),” last modified 1995, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.8902 (accessed June 22, 2011). a system will consider stealing: Omohundro, “Foresight Vision Talk: Self-Improving AI and Designing 2030.” They are going to want: Omohundro, “The Nature of Self-Improving Artificial Intelligence.” There is a first-mover advantage: Ibid. That’s because M13 will: Steele, Bill, Cornell News, “It’s the 25th anniversary of Earth’s first (and only) attempt to phone E.T.,” last modified November 12, 1999, http://web.archive.org/web/20080802005337/http://www.news.cornell.edu/releases/Nov99/Arecibo.message.ws.html (accessed July 2, 2011).

**
The Most Human Human: What Talking With Computers Teaches Us About What It Means to Be Alive
** by
Brian Christian

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4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Bertrand Russell: In Praise of Idleness, carbon footprint, cellular automata, Claude Shannon: information theory, cognitive dissonance, commoditize, complexity theory, crowdsourcing, David Heinemeier Hansson, Donald Trump, Douglas Hofstadter, George Akerlof, Gödel, Escher, Bach, high net worth, Isaac Newton, Jacques de Vaucanson, Jaron Lanier, job automation, l'esprit de l'escalier, Loebner Prize, Menlo Park, Ray Kurzweil, RFID, Richard Feynman, Richard Feynman, Ronald Reagan, Skype, statistical model, Stephen Hawking, Steve Jobs, Steven Pinker, theory of mind, Thomas Bayes, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero-sum game

You get this from the human-computer dialogues: And this from the human-human dialogues: Now if that difference isn’t night and day, I don’t know what is. Over. 1. Some equations (the Newtonian parabolas that projectiles follow, for instance) are such that you can just plug in any old future value for time and get a description of the future state of events. Other calculations (e.g., some cellular automata) contain no such shortcuts. Such processes are called “computationally irreducible.” Future time values cannot simply be “plugged in”; rather, you have to run the simulation all the way from point A to point Z, including all intermediate steps. Stephen Wolfram, in A New Kind of Science, attempts to reconcile free will and determinism by conjecturing that the workings of the human brain are “irreducible” in this way: that is, there are no Newtonian-style “laws” that allow us shortcuts to knowing in advance what people will do.

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

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

Bates, J. (2012) ‘“This is what modern deregulation looks like”: co-optation and contestation in the shaping of the UK’s Open Government Data Initiative’, The Journal of Community Informatics, 8(2), http://www.ci-journal.net/index.php/ciej/article/view/845/916 (last accessed 6 February 2013). Bates, J. (2013) ‘Opening up public data’, SPERI Comment, 21 May. http://speri.dept.shef.ac.uk/2013/05/21/opening-public-data/(last accessed 18 September 2013). Batty, M. (2007) Cities and Complexity: Understanding Cities with Cellular Automata, Agent Based Models, and Fractals. MIT Press, Cambridge, MA. Batty, M., Axhausen, K.W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., Ouzounis, G. and Portugali, Y. (2012) ‘Smart cities of the future’, European Physical Journal Special Topics, 214: 481–518. Baym, N.K. (2013) ‘Data not seen: the uses and shortcomings of social media metrics’, First Monday, 18(10), http://firstmonday.org/ojs/index.php/fm/article/view/4873/3752 (last accessed 3 January 2014).

**
Anathem
** by
Neal Stephenson

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anthropic principle, cellular automata, Danny Hillis, double helix, interchangeable parts, nuclear winter, pattern recognition, phenotype, selection bias, Stewart Brand, trade route

“I suppose ants can flank,” I said, though I sensed that it was a trick question and that Lio was flanking me with words at this very moment. “Why not?” “By accident, of course they can! You look down on it from above and say, ‘Oh, that looked like flanking.’ But if there’s no commander to see the field and direct their movements, can they really perform coordinated maneuvers?” “That’s a little like Saunt Taunga’s Question,” I pointed out (“Can a sufficiently large field of cellular automata think?”). “Well, can they?” “I’ve seen ants work together to carry off part of my lunch, so I know they can coordinate their actions.” “But if I’m one of a hundred ants all pushing on the same raisin, I can feel the raisin moving, can’t I—so the raisin itself is a way that they communicate with one another. But, if I’m a lone ant on a battlefield—” “Thistlehead, it’s Provener.” “Okay,” he said, and turned his back on me and started walking.

…

The Orithenans had used a system of computational chanting that, it was plain to see, was rooted in traditions that their founders had brought over from Edhar. To that point, it was clearly recognizable to any Edharian. It was a way of carrying out computations on patterns of information by permuting a given string of notes into new melodies. The permutation was done on the fly by following certain rules, defined using the formalism of cellular automata. After the Second Sack reforms, newly computerless avout had invented this kind of music. In some concents it had withered away, in others mutated into something else, but at Edhar it had always been practiced seriously. We’d all learned it as a sort of children’s musical game. But at Orithena they had been doing new things with it, using it to solve problems. Or rather to solve a problem, the nature of which I didn’t understand yet.

**
The Age of Spiritual Machines: When Computers Exceed Human Intelligence
** by
Ray Kurzweil

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Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Buckminster Fuller, call centre, cellular automata, combinatorial explosion, complexity theory, computer age, computer vision, cosmological constant, cosmological principle, Danny Hillis, double helix, Douglas Hofstadter, Everything should be made as simple as possible, first square of the chessboard / second half of the chessboard, fudge factor, George Gilder, Gödel, Escher, Bach, I think there is a world market for maybe five computers, information retrieval, invention of movable type, Isaac Newton, iterative process, Jacquard loom, Jacquard loom, John Markoff, John von Neumann, Lao Tzu, Law of Accelerating Returns, mandelbrot fractal, Marshall McLuhan, Menlo Park, natural language processing, Norbert Wiener, optical character recognition, ought to be enough for anybody, pattern recognition, phenotype, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Richard Feynman, Robert Metcalfe, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, speech recognition, Steven Pinker, Stewart Brand, stochastic process, technological singularity, Ted Kaczynski, telepresence, the medium is the message, There's no reason for any individual to have a computer in his home - Ken Olsen, traveling salesman, Turing machine, Turing test, Whole Earth Review, Y2K

A Bibliography of Computer Music: A Reference for Composers. Iowa City: University of Iowa Press, 1981. Toepperwein, L. L., et al. Robotics Applications for Industry: A Practical Guide. Park Ridge: Noyes Data Corporation, 1983. Toffler, Alvin. Powershift. New York: Bantam Books, 1990. ————. The Third Wave: The Classic Study of Tomorrow. New York: Bantam Books, 1980. Toffoli, Tommaso and Norman Margolis. Cellular Automata Machines: A New Environment for Modeling. Cambridge, MA: MIT Press, 1987. Torrance, Stephen B., ed. The Mind and the Machine: Philosophical Aspects of Artificial Intelligence. Chichester, UK: Ellis Horwood, 1986. Traub, Joseph F., ed. Cohabiting with Computers. Los Altos, CA: William Kaufmann, 1985. Truesdell, L. E. The Development of Punch Card Tabulation in the Bureau of the Census, 1890-1940.

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

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A Declaration of the Independence of Cyberspace, AI winter, airport security, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, basic income, Baxter: Rethink Robotics, Bill Duvall, bioinformatics, Brewster Kahle, Burning Man, call centre, cellular automata, Chris Urmson, Claude Shannon: information theory, Clayton Christensen, clean water, cloud computing, collective bargaining, computer age, computer vision, crowdsourcing, Danny Hillis, DARPA: Urban Challenge, data acquisition, Dean Kamen, deskilling, don't be evil, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dynabook, Edward Snowden, Elon Musk, Erik Brynjolfsson, factory automation, From Mathematics to the Technologies of Life and Death, future of work, Galaxy Zoo, Google Glasses, Google X / Alphabet X, Grace Hopper, Gunnar Myrdal, Gödel, Escher, Bach, Hacker Ethic, haute couture, hive mind, hypertext link, indoor plumbing, industrial robot, information retrieval, Internet Archive, Internet of things, invention of the wheel, Jacques de Vaucanson, Jaron Lanier, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, Kodak vs Instagram, labor-force participation, loose coupling, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, medical residency, Menlo Park, Mother of all demos, natural language processing, new economy, Norbert Wiener, PageRank, pattern recognition, pre–internet, RAND corporation, Ray Kurzweil, Richard Stallman, Robert Gordon, Rodney Brooks, Sand Hill Road, Second Machine Age, self-driving car, semantic web, 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, strong AI, superintelligent machines, technological singularity, Ted Nelson, telemarketer, telepresence, telepresence robot, Tenerife airport disaster, The Coming Technological Singularity, the medium is the message, Thorstein Veblen, Turing test, Vannevar Bush, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, William Shockley: the traitorous eight, zero-sum game

Alan Turing, for example, had written about the possibility the previous year, to receptive audiences on both sides of the Atlantic. McCarthy was thinking about intelligence as a mathematical abstraction rather than something realizable—along the lines of Turing—through building an actual machine. It was an “automaton” notion of creating human intelligence, but not of the kind of software cellular automata that von Neumann would later pursue. McCarthy focused instead on an abstract notion of intelligence that was capable of interacting with the environment. When he told von Neumann about it, the scientist exclaimed, “Write it up!” McCarthy thought about the idea a lot but never published anything. Years later he would express regret at his inaction. Although his thesis at Princeton would focus on differential equations, he also developed an interest in logic, and a major contribution to the field of artificial intelligence would later come from his application of mathematical logic to common sense reasoning.

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

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3D printing, Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is the new oil, double helix, Douglas Hofstadter, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, global village, Google Glasses, Gödel, Escher, Bach, information retrieval, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, lone genius, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, Richard Feynman, Second Machine Age, self-driving car, Silicon Valley, speech recognition, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, zero-sum game

AND, OR and NOT can all be implemented using NOR gates, so NOR can do everything, and in fact it’s all some microprocessors use. So why can’t it be the Master Algorithm? It’s certainly unbeatable for simplicity. Unfortunately, a NOR gate is not the Master Algorithm any more than a Lego brick is the universal toy. It can certainly be a universal building block for toys, but a pile of Legos doesn’t spontaneously assemble itself into a toy. The same applies to other simple computation schemes, like Petri nets or cellular automata. Moving on to more sophisticated alternatives, what about the queries that any good database engine can answer, or the simple algorithms in a statistical package? Aren’t those enough? These are bigger Lego bricks, but they’re still only bricks. A database engine never discovers anything new; it just tells you what it knows. Even if all the humans in a database are mortal, it doesn’t occur to it to generalize mortality to other humans.

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Darwin Among the Machines
** by
George Dyson

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

., in four volumes (London: Charles Knight, 1845), 9. 39.John von Neumann, in Arthur Burks, ed., Theory of Self-Reproducing Automata (Urbana: University of Illinois Press, 1966), 47. 40.John Myhill, “The Abstract Theory of Self-Reproduction,” in Mihajlo D. Mesarovic, ed., Views on General Systems Theory, Proceedings of the Second Systems Symposium at Case Institute of Technology, 1964; reprinted in Arthur Burks, ed., Essays on Cellular Automata (Urbana: University of Illinois Press, 1970), 218. 41.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. 42.Robert Chambers, Vestiges of the Natural History of Creation (London: John Churchill, 1844), 222–223. 43.Nils Barricelli, in Paul S. Moorhead and Martin M.

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The Transhumanist Reader
** by
Max More,
Natasha Vita-More

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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, 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, game design, germ theory of disease, 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, meta-analysis, moral hazard, Network effects, Norbert Wiener, P = NP, pattern recognition, phenotype, positional goods, prediction markets, presumed consent, Ray Kurzweil, reversible computing, RFID, Richard Feynman, Ronald Reagan, silicon-based life, Singularitarianism, stem cell, stochastic process, superintelligent machines, supply-chain management, supply-chain management software, 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, Whole Earth Review, women in the workforce, zero-sum game

Yes, as Dawkins says they are creatures naturally evolved in their physical universe and they cannot violate their physics (Dawkins 2006), but they can violate ours if they want. Make this simple experiment: Run a Game of Life program, choose an initial pattern, and let it evolve for a while. Now, stop the program, flip a cell, and resume the program. You have just performed a miracle: something that goes against the physical laws (the simple cellular automata evolution rules of Life) of the lower-level reality that you are simulating. Of course the Game of Life is too simple to contain conscious observers, but hypothetical observers within the game would observe an event that cannot be understood in terms of the physical laws of their universe. A miracle. Berkeley and Moravec are not only saying similar things, they are saying the same thing using different wording.

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

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

(1996) Prices, Cycles and Growth, Cambridge, MA: MIT Press. Oakley, A. (1983) The Making of Marx’s Critical Theory, London: Routledge and Kegan Paul. Obama, B. (2009) ‘Obama’s remarks on the economy,’ New York Times, 14 April. O’Brien, Y.-Y. J. C. (2007) ‘Reserve requirement systems in OECD countries,’ SSRN eLibrary. Oda, S. H., K. Miura, K. Ueda and Y. Baba (2000) ‘The application of cellular automata and agent models to network externalities in consumers’ theory: a generalization of life game,’ in W. A. Barnett, C. Chiarella, S. Keen, R. Marks and H. Schnabl (eds), Commerce, Complexity and Evolution, New York: Cambridge University Press. O’Hara, M. (1995) Market Microstructure Theory, Cambridge: Blackwell. Ormerod, P. (1997) The Death of Economics, 2nd edn, New York: John Wiley & Sons.

pages: 1,737 words: 491,616

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Rationality: From AI to Zombies
** by
Eliezer Yudkowsky

Albert Einstein, Alfred Russel Wallace, anthropic principle, anti-pattern, anti-work, Arthur Eddington, artificial general intelligence, availability heuristic, Bayesian statistics, Berlin Wall, Build a better mousetrap, Cass Sunstein, cellular automata, cognitive bias, cognitive dissonance, correlation does not imply causation, cosmological constant, creative destruction, Daniel Kahneman / Amos Tversky, dematerialisation, discovery of DNA, Douglas Hofstadter, Drosophila, effective altruism, experimental subject, Extropian, friendly AI, fundamental attribution error, Gödel, Escher, Bach, hindsight bias, index card, index fund, Isaac Newton, John Conway, John von Neumann, Long Term Capital Management, Louis Pasteur, mental accounting, meta analysis, meta-analysis, money market fund, Nash equilibrium, Necker cube, NP-complete, P = NP, pattern recognition, Paul Graham, Peter Thiel, Pierre-Simon Laplace, placebo effect, planetary scale, prediction markets, random walk, Ray Kurzweil, reversible computing, Richard Feynman, Richard Feynman, risk tolerance, Rubik’s Cube, Saturday Night Live, Schrödinger's Cat, scientific mainstream, sensible shoes, Silicon Valley, Silicon Valley startup, Singularitarianism, Solar eclipse in 1919, speech recognition, statistical model, Steven Pinker, strong AI, technological singularity, The Bell Curve by Richard Herrnstein and Charles Murray, the map is not the territory, the scientific method, Turing complete, Turing machine, ultimatum game, X Prize, Y Combinator, zero-sum game

The statisticians and cryptographers and physicists and computer scientists go to work. There is structure here; it needs only to be unraveled. The masters of causality search for conditional independence, screening-off and Markov neighborhoods, among bits and groups of bits. The so-called “color” appears to play a role in neighborhoods and screening, so it’s not just the equivalent of surface reflectivity. People search for simple equations, simple cellular automata, simple decision trees, that can predict or compress the message. Physicists invent entire new theories of physics that might describe universes projected onto the grid—for it seems quite plausible that a message such as this is being sent from beyond the Matrix. After receiving 32 × 512 × 256 = 4,194,304 bits, around one and a half months, the stars stop flickering. Theoretical work continues.

…

What if you build your own simulated universe? The classic example of a simulated universe is Conway’s Game of Life. I do urge you to investigate Life if you’ve never played it—it’s important for comprehending the notion of “physical law.” Conway’s Life has been proven Turing-complete, so it would be possible to build a sentient being in the Life universe, although it might be rather fragile and awkward. Other cellular automata would make it simpler. Could you, by creating a simulated universe, escape the reach of God? Could you simulate a Game of Life containing sentient entities, and torture the beings therein? But if God is watching everywhere, then trying to build an unfair Life just results in the God stepping in to modify your computer’s transistors. If the physics you set up in your computer program calls for a sentient Life-entity to be endlessly tortured for no particular reason, the God will intervene.

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The system of the world
** by
Neal Stephenson

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bank run, British Empire, cellular automata, Edmond Halley, Fellow of the Royal Society, high net worth, Isaac Newton, James Watt: steam engine, joint-stock company, large denomination, place-making, the market place, trade route, transatlantic slave trade

Many others have, knowingly or not, contributed to a milieu in which it was possible for me to consider writing something like this without seeming completely mad. And here I am tempted to list the names of a lot of mathematicians and physicists. But out of a concern for their privacy and a desire not to seem like I’m clinging to their ankles, I’ll draw a veil over those conversations. Suffice it to say that the Royal Society crowd written about in these books has many descendants and heirs today, who are capable of talking learnedly about monads, cellular automata, the calculus dispute, absolute time and space, &c. at the drop of a hat, and that it’s been my privilege to know a few of them. They seem pleasantly surprised to learn that someone actually wants to write a novel about such topics, and I in turn have been pleasantly surprised to find that they are actually willing to spend time talking to me, and out of this, quite a few good conversations have arisen over the years.