artificial general intelligence

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Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the Agi Workshop 2006 by Ben Goertzel, Pei Wang


AI winter, artificial general intelligence, bioinformatics, brain emulation, combinatorial explosion, complexity theory, computer vision, conceptual framework, correlation coefficient, epigenetics, friendly AI, information retrieval, Isaac Newton, John Conway, Loebner Prize, Menlo Park, natural language processing, Occam's razor, p-value, pattern recognition, performance metric, Ray Kurzweil, Rodney Brooks, semantic web, statistical model, strong AI, theory of mind, traveling salesman, Turing machine, Turing test, Von Neumann architecture, Y2K

Adams, Eric Baum, Pei Wang, Steve Grand, Ben Goertzel and Phil Goetz 283 Author Index 295 Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms B. Goertzel and P. Wang (Eds.) IOS Press, 2007 © 2007 The authors and IOS Press. All rights reserved. 1 Introduction: Aspects of Artificial General Intelligence Pei WANG and Ben GOERTZEL Introduction This book contains materials that come out of the Artificial General Intelligence Research Institute (AGIRI) Workshop, held in May 20-21, 2006 at Washington DC. The theme of the workshop is “Transitioning from Narrow AI to Artificial General Intelligence.” In this introductory chapter, we will clarify the notion of “Artificial General Intelligence”, briefly survey the past and present situation of the field, analyze and refute some common objections and doubts regarding this area of research, and discuss what we believe needs to be addressed by the field as a whole in the near future.

The next major step in this direction was the May 2006 AGIRI Workshop, of which this volume is essentially a proceedings. The term AGI, artificial general intelligence, was introduced as a modern successor to the earlier strong AI. Artificial General Intelligence What is artificial general intelligence? The AGIRI website lists several features, describing machines • • • • with human-level, and even superhuman, intelligence. that generalize their knowledge across different domains. that reflect on themselves. and that create fundamental innovations and insights. Even strong AI wouldn’t push for this much, and this general, an intelligence. Can there be such an artificial general intelligence? I think there can be, but that it can’t be done with a brain in a vat, with humans providing input and utilizing computational output.

New York: Basic Books, 1958. [4] Goertzel, Ben and Cassio Pennachin (2006). The Novamente Design for Artificial General Intelligence. In Artificial General Intelligence, Springer-Verlag. [5] Goertzel, Ben (2006). Patterns, Hypergraphs and General Intelligence. Proceedings of International Joint Conference on Neural Networks, IJCNN 2006, Vancouver CA, to appear. [6] Goertzel, Ben, C. Pennachin, A. Senna, T. Maia, G. Lamacie. (2003) “Novamente: an integrative architecture for Artificial General Intelligence.” Proceedings of IJCAI 2003 Workshop on Cognitive Modeling of Agents. Acapulco, Mexico, 2003. [7] Goertzel, Ben, C. Pennachin, A. Senna, M. Looks. (2004) “The Novamente Artificial General Intelligence Architecture.” Proceedings of AAAI Symposium on Achieving Intelligence Through Integrated Systems And Research.

The Economic Singularity: Artificial intelligence and the death of capitalism by Calum Chace


3D printing, additive manufacturing, agricultural Revolution, AI winter, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, banking crisis, Baxter: Rethink Robotics, Berlin Wall, Bernie Sanders, bitcoin, blockchain, call centre, Chris Urmson, congestion charging, credit crunch, David Ricardo: comparative advantage, Elon Musk,, Erik Brynjolfsson, Flynn Effect, full employment, future of work, gender pay gap, gig economy, Google Glasses, Google X / Alphabet X, income inequality, industrial robot, Internet of things, invention of the telephone, invisible hand, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, lump of labour, Lyft, Mark Zuckerberg, Martin Wolf, McJob, means of production, Milgram experiment, Narrative Science, natural language processing, new economy, Occupy movement, Oculus Rift, PageRank, pattern recognition, post scarcity, post-industrial society, precariat, prediction markets, QWERTY keyboard, railway mania, RAND corporation, Ray Kurzweil, RFID, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, software is eating the world, speech recognition, Stephen Hawking, Steve Jobs, TaskRabbit, technological singularity, Thomas Malthus, transaction costs, Tyler Cowen: Great Stagnation, Uber for X, universal basic income, Vernor Vinge, working-age population, Y Combinator, young professional

There is no reason to suppose that humans have attained anywhere near the maximum possible level of intelligence, and it seems highly probable that we will eventually create machines that are more intelligent than us in all respects – assuming we don't blow ourselves up first. We don't yet know whether those machines will be conscious, let alone whether they will be more conscious than us – if that is even a meaningful question. Artificial General Intelligence (AGI) and Superintelligence As we noted in chapter 1, the term for a machine which equals or exceeds human intelligence in all respects is artificial general intelligence, or AGI. The day when the first such machine is built will be a momentous one, as the arrival of superintelligence will not be far beyond it. The likelihood of an intelligence explosion is commonly referred to as the technological singularity. This could be an astonishingly positive development for humankind, or a disastrously negative one.

[lxviii] At the beginning of this chapter we noted that intelligence is not a single, unitary skill or process. The fact that Watson is an amalgam – some would say a kludge – of numerous different techniques does not in itself mark it out as different and perpetually inferior to human intelligence. It is nowhere near an artificial general intelligence which is human-level or beyond in all respects. It is not conscious. It does not even know that it won the Jeopardy match. But it may prove to be an early step in the direction of artificial general intelligence. In January 2016, an AI system called AlphaGo developed by Google's DeepMind beat Fan Hui, the European champion of Go, a board game. This was hailed as a major step forward: the game of chess has more possible moves (3580) than there are atoms in the visible universe, but Go has even more – 250150.

Chapter 6.6 adopted Kevin Kelly’s term Protopia for a successful transition, and suggested that the blockchain might turn out to be the mechanism to administer society’s collectively owned assets, notably its artificial intelligence. 7.2 – The two singularities In my previous book, “Surviving AI”, I wrote at length about the challenge and the opportunity presented by the technological singularity, the moment when (and if) we create an artificial general intelligence which continues to improve its cognitive performance and becomes a superintelligence. Ensuring that we survive that event is, I believe, the single most important task facing the next generation or two of humans – along with making sure we don’t blow ourselves up with nuclear weapons, or unleash a pathogen which kills everyone. If we secure the good outcome to the technological singularity, the future of humanity is glorious almost beyond imagination. As DeepMind co-founder Demis Hassabis likes to say, humanity’s plan for the future should consist of two steps: first, solve artificial general intelligence, and second, use that to solve everything else. “Everything else” includes poverty, illness, war and even death itself.

pages: 574 words: 164,509

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom


agricultural Revolution, AI winter, Albert Einstein, algorithmic trading, anthropic principle, anti-communist, artificial general intelligence, autonomous vehicles, barriers to entry, bioinformatics, brain emulation, cloud computing, combinatorial explosion, computer vision, cosmological constant, dark matter, DARPA: Urban Challenge, data acquisition, delayed gratification, demographic transition, Douglas Hofstadter, Drosophila, Elon Musk,, epigenetics, fear of failure, Flash crash, Flynn Effect, friendly AI, Gödel, Escher, Bach, income inequality, industrial robot, informal economy, information retrieval, interchangeable parts, iterative process, job automation, John von Neumann, knowledge worker, Menlo Park, meta analysis, meta-analysis, mutually assured destruction, Nash equilibrium, Netflix Prize, new economy, Norbert Wiener, NP-complete, nuclear winter, optical character recognition, pattern recognition, performance metric, phenotype, prediction markets, price stability, principal–agent problem, race to the bottom, random walk, Ray Kurzweil, recommendation engine, reversible computing, social graph, speech recognition, Stanislav Petrov, statistical model, stem cell, Stephen Hawking, strong AI, superintelligent machines, supervolcano, technological singularity, technoutopianism, The Coming Technological Singularity, The Nature of the Firm, Thomas Kuhn: the structure of scientific revolutions, transaction costs, Turing machine, Vernor Vinge, Watson beat the top human players on Jeopardy!, World Values Survey

The definition of HLMI used by Nilsson is “AI able to perform around 80% of jobs as well or better than humans perform” (Kruel 2012). 81. The table shows the results of four different polls as well as the combined results. The first two were polls taken at academic conferences: PT-AI, participants of the conference Philosophy and Theory of AI in Thessaloniki 2011 (respondents were asked in November 2012), with a response rate of 43 out of 88; and AGI, participants of the conferences Artificial General Intelligence and Impacts and Risks of Artificial General Intelligence, both in Oxford, December 2012 (response rate: 72/111). The EETN poll sampled the members of the Greek Association for Artificial Intelligence, a professional organization of published researchers in the field, in April 2013 (response rate: 26/250). The TOP100 poll elicited the opinions among the 100 top authors in artificial intelligence as measured by a citation index, in May 2013 (response rate: 29/100). 82.

(The different lines in the plot correspond to different data sets, which yield slightly different estimates.6) Great expectations Machines matching humans in general intelligence—that is, possessing common sense and an effective ability to learn, reason, and plan to meet complex information-processing challenges across a wide range of natural and abstract domains—have been expected since the invention of computers in the 1940s. At that time, the advent of such machines was often placed some twenty years into the future.7 Since then, the expected arrival date has been receding at a rate of one year per year; so that today, futurists who concern themselves with the possibility of artificial general intelligence still often believe that intelligent machines are a couple of decades away.8 Two decades is a sweet spot for prognosticators of radical change: near enough to be attention-grabbing and relevant, yet far enough to make it possible to suppose that a string of breakthroughs, currently only vaguely imaginable, might by then have occurred. Contrast this with shorter timescales: most technologies that will have a big impact on the world in five or ten years from now are already in limited use, while technologies that will reshape the world in less than fifteen years probably exist as laboratory prototypes.

A more relevant distinction for our purposes is that between systems that have a narrow range of cognitive capability (whether they be called “AI” or not) and systems that have more generally applicable problem-solving capacities. Essentially all the systems currently in use are of the former type: narrow. However, many of them contain components that might also play a role in future artificial general intelligence or be of service in its development—components such as classifiers, search algorithms, planners, solvers, and representational frameworks. One high-stakes and extremely competitive environment in which AI systems operate today is the global financial market. Automated stock-trading systems are widely used by major investing houses. While some of these are simply ways of automating the execution of particular buy or sell orders issued by a human fund manager, others pursue complicated trading strategies that adapt to changing market conditions.

pages: 144 words: 43,356

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


3D printing, Ada Lovelace, AI winter, Airbnb, artificial general intelligence, augmented reality, barriers to entry, bitcoin, blockchain, brain emulation, Buckminster Fuller, cloud computing, computer age, computer vision, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, dematerialisation, discovery of the americas, disintermediation, don't be evil, Elon Musk,, epigenetics, Erik Brynjolfsson, everywhere but in the productivity statistics, Flash crash, friendly AI, Google Glasses, industrial robot, Internet of things, invention of agriculture, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, life extension, low skilled workers, Mahatma Gandhi, means of production, mutually assured destruction, Nicholas Carr, pattern recognition, Peter Thiel, Ray Kurzweil, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, Skype, South Sea Bubble, speech recognition, Stanislav Petrov, Stephen Hawking, Steve Jobs, strong AI, technological singularity, theory of mind, Turing machine, Turing test, universal basic income, Vernor Vinge, wage slave, Wall-E

Whether intelligence resides in the machine or in the software is analogous to the question of whether it resides in the neurons in your brain or in the electrochemical signals that they transmit and receive. Fortunately we don’t need to answer that question here. ANI and AGI We do need to discriminate between two very different types of artificial intelligence: artificial narrow intelligence (ANI) and artificial general intelligence (AGI (4)), which are also known as weak AI and strong AI, and as ordinary AI and full AI. The easiest way to do this is to say that artificial general intelligence, or AGI, is an AI which can carry out any cognitive function that a human can. We have long had computers which can add up much better than any human, and computers which can play chess better than the best human chess grandmaster. However, no computer can yet beat humans at every intellectual endeavour.

History doesn’t repeat itself, and even though it sometimes rhymes, the rhyme is often irregular and impossible to forecast, although it seems natural in hindsight. As we saw in the introduction to this book, nobody suggested thirty years ago that we would have powerful AIs in our pockets in the form of telephones, even though now that it has happened it seems a natural and logical development. PART TWO: AGI Artificial General Intelligence CHAPTER 4 CAN WE BUILD AN AGI? 4.1 – Is it possible in principle? The three biggest questions about artificial general intelligence (AGI) are: Can we build one? If so, when? Will it be safe? The first of these questions is the closest to having an answer, and that answer is “probably, as long as we don’t go extinct first”. The reason for this is that we already have proof that it is possible for a general intelligence to be developed using very common materials.

TABLE OF CONTENTS TITLE PAGE INTRODUCTION: SURVIVING AI PART ONE: ANI (ARTIFICIAL NARROW INTELLIGENCE) CHAPTER 1 CHAPTER 2 CHAPTER 3 PART TWO: AGI (ARTIFICIAL GENERAL INTELLIGENCE) CHAPTER 4 CHAPTER 5 PART THREE: ASI (ARTIFICIAL SUPERINTELLIGENCE) CHAPTER 6 CHAPTER 7 PART FOUR: FAI (FRIENDLY ARTIFICIAL INTELLIGENCE) CHAPTER 8 CHAPTER 9 ACKNOWLEDGEMENTS ENDNOTES COMMENTS ON SURVIVING AI A sober and easy-to-read review of the risks and opportunities that humanity will face from AI. Jaan Tallinn, co-founder Skype, co-founder Centre for the Study of Existential Risk (CSER), co-founder Future of Life Institute (FLI) Understanding AI – its promise and its dangers – is emerging as one of the great challenges of coming decades and this is an invaluable guide to anyone who’s interested, confused, excited or scared.

pages: 294 words: 81,292

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


3D printing, AI winter, Amazon Web Services, artificial general intelligence, Automated Insights, Bernie Madoff, Bill Joy: nanobots, brain emulation, cellular automata, cloud computing, cognitive bias, computer vision, cuban missile crisis, Daniel Kahneman / Amos Tversky, Danny Hillis, data acquisition, don't be evil, Extropian, finite state, Flash crash, friendly AI, friendly fire, Google Glasses, Google X / Alphabet X, Isaac Newton, Jaron Lanier, 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, traveling salesman, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, zero day

He acknowledges hazards but devotes his energy to advocating for the likelihood of a long snag-free journey down the digital birth canal. My informal survey of about two hundred computer scientists at a recent AGI conference confirmed what I’d expected. The annual AGI Conferences, organized by Goertzel, are three-day meet-ups for people actively working on artificial general intelligence, or like me who are just deeply interested. They present papers, demo software, and compete for bragging rights. I attended one generously hosted by Google at their headquarters in Mountain View, California, often called the Googleplex. I asked the attendees when artificial general intelligence would be achieved, and gave them just four choices—by 2030, by 2050, by 2100, or not at all? The breakdown was this: 42 percent anticipated AGI would be achieved by 2030; 25 percent by 2050; 20 percent by 2100; 10 percent by 2100, and 2 percent never.

Andrew Rubin, Google’s Senior Vice President of Mobile: Fried, Ina, “Android Chief Says Your Phone Should Not Be Your Assistant,” All Things D, October 19, 2011, (accessed November 13, 2011). It may be that we need a scientific breakthrough: Goertzel, Ben, “Editor’s Blog Report on the Fourth Conference on Artificial General Intelligence,” H+ Magazine, September 1, 2011, (accessed November 22, 2011). LIDA scores like a human: Biever, Celeste, “Bot shows signs of consciousness,” New Scientist, April 1, 2011, (accessed June 1, 2011). committing the Holocaust: Goertzel, Ben, “The Machine Intelligence Research Institute’s Scary Idea (and Why I Don’t Buy It),” The Multiverse According to Ben (blog), October 29, 2010, http://multiverseaccordingtoben. (accessed June 1, 2011).

Aboujaoude, Elias accidents AI and, see risks of artificial intelligence nuclear power plant Adaptive AI affinity analysis agent-based financial modeling “Age of Robots, The” (Moravec) Age of Spiritual Machines, The: When Computers Exceed Human Intelligence (Kurzweil) AGI, see artificial general intelligence AI, see artificial intelligence AI-Box Experiment airplane disasters Alexander, Hugh Alexander, Keith Allen, Paul Allen, Robbie Allen, Woody AM (Automatic Mathematician) Amazon Anissimov, Michael anthropomorphism apoptotic systems Apple iPad iPhone Siri Arecibo message Aristotle artificial general intelligence (AGI; human-level AI): body needed for definition of emerging from financial markets first-mover advantage in jump to ASI from; see also intelligence explosion by mind-uploading by reverse engineering human brain time and funds required to develop Turing test for artificial intelligence (AI): black box tools in definition of drives in, see drives as dual use technology emotional qualities in as entertainment examples of explosive, see intelligence explosion friendly, see Friendly AI funding for jump to AGI from Joy on risks of, see risks of artificial intelligence Singularity and, see Singularity tight coupling in utility function of virtual environments for artificial neural networks (ANNs) artificial superintelligence (ASI) anthropomorphizing gradualist view of dealing with jump from AGI to; see also intelligence explosion morality of nanotechnology and runaway Artilect War, The (de Garis) ASI, see artificial superintelligence Asilomar Guidelines ASIMO Asimov, Isaac: Three Laws of Robotics of Zeroth Law of Association for the Advancement of Artificial Intelligence (AAAI) asteroids Atkins, Brian and Sabine Automated Insights availability bias Banks, David L.

pages: 48 words: 12,437

Smarter Than Us: The Rise of Machine Intelligence by Stuart Armstrong


artificial general intelligence, brain emulation, effective altruism, Flash crash, friendly AI, shareholder value, Turing test

See, for instance, Bill Hibbard, “Super-Intelligent Machines,” ACM SIGGRAPH Computer Graphics 35, no. 1 (2001): 13–15,; Ben Goertzel and Joel Pitt, “Nine Ways to Bias Open-Source AGI Toward Friendliness,” Journal of Evolution and Technology 22, no. 1 (2012): 116–131, 4. Ben Goertzel, “CogPrime: An Integrative Architecture for Embodied Artificial General Intelligence,” OpenCog Foundation, October 2, 2012, accessed December 31, 2012, Chapter 10 A Summary There are no convincing reasons to assume computers will remain unable to accomplish anything that humans can. Once computers achieve something at a human level, they typically achieve it at a much higher level soon thereafter. An AI need only be superhuman in one of a few select domains for it to become incredibly powerful (or empower its controllers).

See MIRI’s work on the fragility of values and FHI’s work on the problem of containing oracles: Luke Muehlhauser and Louie Helm, “The Singularity and Machine Ethics,” in Singularity Hypotheses: A Scientific and Philosophical Assessment, ed. Amnon Eden et al., The Frontiers Collection (Berlin: Springer, 2012); Stuart Armstrong, Anders Sandberg, and Nick Bostrom, “Thinking Inside the Box: Controlling and Using an Oracle AI,” Minds and Machines 22, no. 4 (2012): 299–324, doi:10.1007/s11023-012-9282-2. 2. Stephen M. Omohundro, “The Basic AI Drives,” in Artificial General Intelligence 2008: Proceedings of the First AGI Conference, Frontiers in Artificial Intelligence and Applications 171 (Amsterdam: IOS, 2008), 483–492. 3. Roman V. Yampolskiy, “Leakproofing the Singularity: Artificial Intelligence Confinement Problem,” Journal of Consciousness Studies 2012, nos. 1–2 (2012): 194–214, 4.

Journal of Consciousness Studies 17, nos. 9–10 (2010): 7–65. Eden, Amnon, Johnny Søraker, James H. Moor, and Eric Steinhart, eds. Singularity Hypotheses: A Scientific and Philosophical Assessment. The Frontiers Collection. Berlin: Springer, 2012. Goertzel, Ben. “CogPrime: An Integrative Architecture for Embodied Artificial General Intelligence.” OpenCog Foundation. October 2, 2012. Accessed December 31, 2012. Goertzel, Ben, and Joel Pitt. “Nine Ways to Bias Open-Source AGI Toward Friendliness.” Journal of Evolution and Technology 22, no. 1 (2012): 116–131. Hanson, Robin. “Economics of the Singularity.” IEEE Spectrum 45, no. 6 (2008): 45–50. doi:10.1109/MSPEC.2008.4531461. ———.

pages: 798 words: 240,182

The Transhumanist Reader by Max More, Natasha Vita-More


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, Drosophila,, 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, 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

Copyright © 2007 Andy Clark. 12 Artificial General Intelligence and the Future of Humanity Ben Goertzel What will be the next huge leap in humanity’s progress? We cannot know for sure, but I am ­reasonably confident that it will involve the radical extension of technology into the domain of thought. Ray Kurzweil (2000, 2005) has eloquently summarized the arguments in favor of this ­position. We have created tools to carry out much of the practical work previously done by human bodies. Next we will create tools to carry out the work currently done by human minds. We will create powerful robots and artificially intelligent software programs – not merely “narrow AI” programs carrying out specific tasks, but AGIs, artificial general intelligences capable of coping with unpredictable situations in intelligent and creative ways.

Freitas, Raymond Kurzweil, Marvin Minsky, Max More, Christine Peterson, Michael D. Shapiro, Lee Silver, Gregory Stock, Natasha Vita-More, Roy Walford, and Michael West. See Statement for Extropy Institute Vital Progress Summit February 18, 2004. Index accelerating change adaptability aesthetics ageless AGI, see artificial general intelligence aging alchemy alterity anti-aging Aristotle Armstrong, Rachel artifact artificial general intelligence artificial intelligence artificial life Ascott, Roy atheism atom atomic augmentation authoritarian autonomous self (agent) autonomy avatar Bacon, Francis Bailey, Ronald Bainbridge, William Beloff, Laura Berger, Ted Benford, Gregory Beyond Therapy: Biotechnology and the Pursuit of Happiness bias bioart bioconservative biocultural capital bioethics biofeedback biopolitics biotechnology Blackford, Russell Blue Brain body alternative body biological body biopolitic computer interaction and body cyborg body modification morphological freedom posthuman body prosthetic body regenerated simulated transformative transhuman body wearable, see Hybronaut Bostrom, Nick brain–computer interface brain–machine interface (BMI) brain preservation Brin, David Broderick, Damien Caplan, Arthur Chalmers, David Chislenko, Alexander “Sasha,” Church, George Clark, Andy Clarke, Arthur C.

Nanorobotics Nanorobotics Revolution by the 2020s Conclusions 7 Life Expansion Media Living Matter Degeneration/Regeneration Transmutation Dialectics of Desirability and Viability Cybernetics Human-machine Interfaces and the Prosthetic Body Life Expansion 8 The Hybronaut Affair Techno-Organic Environment The Umwelt Bubble Network and the Hybronaut The Appendix-tail Conclusion 9 Transavatars Avatars and Simulation Avatar Censuses Secondary and Posthumous Avatars Conclusion 10 Alternative Biologies Biology as Technology The Rise of Machines Complexity The Science of Complexity Synthetic Biology – Complex Embodied Technology Top-Down Synthetic Biology Bottom-Up Synthetic Biology Protocells Artificial Biology From Proposition to Reality Future Venice Artificial Biology and Human Enhancement Part III Human Enhancement: The Cognitive Sphere 11 Re-Inventing Ourselves I. Introduction: Where the Rubber Meets the Road II. What’s in an Interface? III. New Systemic Wholes IV. Incorporation Versus Use V. Extended Cognition VI. Profound Embodiment VII. Enhancement or Subjugation? VIII. Conclusions 12 Artificial General Intelligence and the Future of Humanity The Top Priority for Mankind AGI and the Transformation of Individual and Collective Experience AGI and the Global Brain What is a Mind that We Might Build One? Why So Little Work on AGI? Why the “AGI Sputnik” Will Change Things Dramatically and Launch a New Phase of the Intelligence Explosion The Risks and Rewards of Advanced AGI 13 Intelligent Information Filters and Enhanced Reality Preface Text Translation and Its Consequences Enhanced Multimedia Structure of Enhanced Reality Historical Observations Truth vs.

pages: 484 words: 104,873

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


3D printing, additive manufacturing, Affordable Care Act / Obamacare, AI winter, algorithmic trading, Amazon Mechanical Turk, artificial general intelligence, autonomous vehicles, banking crisis, Baxter: Rethink Robotics, Bernie Madoff, Bill Joy: nanobots, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chris Urmson, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, computer age, debt deflation, deskilling, diversified portfolio, Erik Brynjolfsson, factory automation, financial innovation, Flash crash, Fractional reserve banking, Freestyle chess, full employment, Goldman Sachs: Vampire Squid, High speed trading, income inequality, indoor plumbing, industrial robot, informal economy, iterative process, Jaron Lanier, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Khan Academy, knowledge worker, labor-force participation, labour mobility, liquidity trap, low skilled workers, low-wage service sector, Lyft, manufacturing employment, McJob, moral hazard, Narrative Science, Network effects, new economy, Nicholas Carr, Norbert Wiener, obamacare, optical character recognition, passive income, performance metric, Peter Thiel, Plutocrats, plutocrats, post scarcity, precision agriculture, price mechanism, Ray Kurzweil, rent control, rent-seeking, reshoring, RFID, Richard Feynman, Richard Feynman, Rodney Brooks, secular stagnation, self-driving car, Silicon Valley, Silicon Valley startup, single-payer health, software is eating the world, sovereign wealth fund, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Steven Pinker, strong AI, Stuxnet, technological singularity, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Coming Technological Singularity, Thomas L Friedman, too big to fail, Tyler Cowen: Great Stagnation, union organizing, Vernor Vinge, very high income, Watson beat the top human players on Jeopardy!, women in the workforce

See artificial intelligence (AI) “AI winters,” 231 Alaska, annual dividend, 268 algorithms acceleration in development of, 71 automated trading, 56, 113–115 increasing efficiency of, 64 machine learning, 89, 93, 100–101, 107–115, 130–131 threat to jobs, xv, 85–86 alien invasion parable, 194–196, 240 “All Can Be Lost: The Risk of Putting Our Knowledge in the Hands of Machines” (Carr), 254 all-payer ceiling, 168–169 all-payer rates, 167–169, 16–17, 76, 89 artificial intelligence and, 231 cloud computing and, 104–105, 107 delivery model, 190, 190n “Mechanical Turk” service, 125n AMD (Advanced Micro Devices), 70n American Airlines, 179 American Hospital Association, 168 American Motors, 76 Andreesen, Marc, 107 Android, 6, 21, 79, 121 Apple, Inc., 17, 20, 51, 92, 106–107, 279 Apple Watch, 160 apps, difficulty in monetizing, 79 Arai, Noriko, 127–128 Aramco, 68 Ariely, Dan, 47n Arrow, Kenneth, 162, 169 art, machines creating, 111–113 Artificial General Intelligence (AGI), 231–233 dark side of, 238–241 the Singularity and, 233–238 artificial intelligence (AI), xiv arms race and, 232, 239–240 in medicine, 147–153 narrow, 229–230 offshoring and, 118–119 warnings concerning dangers of, 229 See also Artificial General Intelligence (AGI); automation; information technology Artificial Intelligence Laboratory (Stanford University), 6 artificial neural networks, 90–92. See also deep learning The Atlantic (magazine), 71, 237, 254, 273 AT&T, 135, 159, 166 Audi, 184 Australian agriculture, x–xi, 24–25 Australian Centre for Field Robotics (ACFR), 24–25 AutoDesk, 234 automated invention machines, 110 automated trading algorithms, 56, 113–115 automation alien invasion parable, 194–196, 240 anti-automation view, 253–257 cars and (see autonomous cars) effect on Chinese manufacturing, 3, 10–11, 225–226 effect on prices, 215–216 health care jobs and, 172–173 information technology and, 52 job-market polarization and, 50–51 low-wage jobs and, 26–27 offshoring as precursor to, 115, 118–119 predictions of effect of, 30–34 reshoring and, 10 retail sector and, 16–20 risk of, 256 service sector and, 12–20 solutions to rise of, 273–278 (see also basic income guarantee) as threat to workers with varying education and skill levels, xiv–xv, 59 of total US employment, 223 Triple Revolution report, 30–31 white-collar, 85–86, 105–106, 126–128 See also robotics; robots automotive industry, 3, 76, 193–194 autonomous cars, xiii, 94, 176, 181–191 as shared resource, 186–190 Autor, David, 50 Average Is Over (Cowen), 123, 126n aviation, 66–67, 179, 256 AVT, Inc., 18 Ayres, Ian, 125 Babbage, Charles, 79 Baker, Stephen, 96n, 102n Barra, Hugo, 121 Barrat, James, 231, 238–239 basic income guarantee, 31n, 257–261 approaches to, 261–262 downsides and risks of, 268–271 economic argument for, 264–267 economic risk taking and, 267–268 incentives and, 261–264 paying for, 271–273 Baxter (robot), 5–6, 7, 10 BD Focal Point GS Imaging System, 153 Beaudry, Paul, 127 Beijing Genomics Institute, 236n Bell Labs, 159 Berg, Andrew G., 214–215 Bernanke, Ben, 37 big data, xv, 25n, 86–96 collection of, 86–87 correlation vs. cause and, 88–89, 102 deep learning and, 92–93 health care and, 159–160 knowledge-based jobs and, 93–96 machine learning and, 89–92 The Big Switch (Carr), 72 Bilger, Burkhard, 186 “BinCam,” 125n “Bitter Pill” (Brill), 160 Blinder, Alan, 117–118, 119 Blockbuster, 16, 19 Bloomberg, 113–114 Bluestone, Barry, 220 Borders, 16 Boston Consulting Group, 9 Boston Globe (newspaper), 149 Boston Red Sox, 83 Boston University, 141 Bowley, Arthur, 38 Bowley’s Law, 38–39, 41 box-moving robot, 1–2, 5–6 brain, reverse engineering of human, 237 breast cancer screening, 152 Brill, Steven, 160, 163 Brin, Sergey, 186, 188, 189, 236 Brint, Steven, 251 Brooks, Rodney, 5 Brown, Jerry, 134 Brynjolfsson, Erik, 60, 122, 254 Bureau of Labor Statistics, 13, 16, 38n, 158, 222–223, 281 Bush, George W., 116 business interest lobbying, economic policy and, 57–58 “Busy child scenario,” (Barrat) 238–239 Calico, 236 California Institute of Technology, 133 Canada, 41, 58, 167n, 251 “Can Nanotechnology Create Utopia?”

The extraordinary power of today’s computers combined with advances in specific areas of AI research, as well as in our understanding of the human brain, are generating a great deal of optimism. James Barrat, the author of a recent book on the implications of advanced AI, conducted an informal survey of about two hundred researchers in human-level, rather than merely narrow, artificial intelligence. Within the field, this is referred to as Artificial General Intelligence (AGI). Barrat asked the computer scientists to select from four different predictions for when AGI would be achieved. The results: 42 percent believed a thinking machine would arrive by 2030, 25 percent said by 2050, and 20 percent thought it would happen by 2100. Only 2 percent believed it would never happen. Remarkably, a number of respondents wrote comments on their surveys suggesting that Barrat should have included an even earlier option—perhaps 2020.2 Some experts in the field worry that another expectations bubble might be building.

AI is becoming indispensable to militaries, intelligence agencies, and the surveillance apparatus in authoritarian states.* Indeed, an all-out AI arms race might well be looming in the near future. The real question, I think, is not whether the field as a whole is in any real danger of another AI winter but, rather, whether progress remains limited to narrow AI or ultimately expands to Artificial General Intelligence as well. If AI researchers do eventually manage to make the leap to AGI, there is little reason to believe that the result will be a machine that simply matches human-level intelligence. Once AGI is achieved, Moore’s Law alone would likely soon produce a computer that exceeded human intellectual capability. A thinking machine would, of course, continue to enjoy all the advantages that computers currently have, including the ability to calculate and access information at speeds that would be incomprehensible for us.

Pandora's Brain by Calum Chace


3D printing, AI winter, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, brain emulation, Extropian, friendly AI, hive mind, Ray Kurzweil, self-driving car, Silicon Valley, Singularitarianism, Skype, speech recognition, stealth mode startup, Stephen Hawking, strong AI, technological singularity, theory of mind, Turing test, Wall-E

‘What I am going to tell you may sound melodramatic, but please hear me out because I mean every word of it.’ He paused, and looked at Matt and Leo in turn. ‘We are engaged in a race, gentlemen. A race for the survival of our species. Humanity is sleepwalking towards an apocalypse.’ Matt and Leo were listening attentively, but Ivan held up his hand anyway, as if to forestall interruptions. ‘The great majority of our fellow human beings have no clue that the first artificial general intelligence – human-level AI, a conscious machine – will almost certainly be created in the first half of this century. Of the few who do realise where the technology is heading, most are Californian dreamers who think nothing can go wrong: they love technology and they love computers, and they cannot conceive that an intelligent computer will not be their friend.’ ‘I’ve read some of their stuff,’ Matt agreed.

I probably don’t know everything that the military is up to with regard to machine intelligence, but I think I know about their most advanced projects. Their resources are formidable. We’re supervised by the Strategic Technology Office, and I have a high level of clearance. The organisation I run was no mean outfit before I teamed up with Norman and his pals, so I like to think that if the US Army does turn out to be the first institution to build an artificial general intelligence, there will be a well-informed and well-connected civilian organisation standing shoulder-to-shoulder with them and making sure they don’t go off in all sorts of unhealthy directions. ‘Norman and his colleagues have been incredibly helpful. Not only with money, but with contacts, technologies, advice, and of course intelligence. Which brings us to our friend Ivan, and to you, Matt.’

‘But on the other hand, going public too late could be much worse,’ Matt said. ‘If the idea is effectively sprung on people just before it becomes a reality, the panic you are worried about could be enormously damaging.’ Leo was nodding as Matt spoke. ‘If we withhold some of the story and then it gets out, people will be suspicious about what else is being hidden. If it leaks out that the US Army is close to creating the first artificial general intelligence, and has been less than truthful about it, a lot of people will get very concerned. But to be honest I’m more concerned about the more immediate problems. For instance, is it realistic to insist that Matt never speaks to anyone outside this room about his experience – not now and not for the rest of his life? And what about Ivan’s people on the boat and elsewhere? How many of them know more than you’re proposing to disclose?’

pages: 219 words: 63,495

50 Future Ideas You Really Need to Know by Richard Watson


23andMe, 3D printing, access to a mobile phone, Albert Einstein, artificial general intelligence, augmented reality, autonomous vehicles, BRICs, Buckminster Fuller, call centre, clean water, cloud computing, collaborative consumption, computer age, computer vision, crowdsourcing, dark matter, dematerialisation, digital Maoism, Elon Musk, energy security, failed state, future of work, Geoffrey West, Santa Fe Institute, germ theory of disease, happiness index / gross national happiness, hive mind, hydrogen economy, Internet of things, Jaron Lanier, life extension, Marshall McLuhan, megacity, natural language processing, Network effects, new economy, oil shale / tar sands, pattern recognition, peak oil, personalized medicine, phenotype, precision agriculture, profit maximization, RAND corporation, Ray Kurzweil, RFID, Richard Florida, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Skype, smart cities, smart meter, smart transportation, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, supervolcano, telepresence, The Wisdom of Crowds, Thomas Malthus, Turing test, urban decay, Vernor Vinge, Watson beat the top human players on Jeopardy!, web application, women in the workforce, working-age population, young professional

timeline 1662 Dodo becomes extinct 1966 Last Arabian ostrich 1989 Golden toads extinct 1998 Poll of 400 scientists reveals that 70 percent believe mass extinction is happening 2000 Last Pyrenean Ibex dies (it’s cloned back in 2009 but later dies) 2005 Extinct Laotian Rock Rat rediscovered 2006 Freshwater dolphin declared dead 2035 50 percent of European amphibians extinct 46 The Singularity Moore’s Law (named after Gordon Moore) says that computers double their processing ability every 18 months or so. But imagine if this rate of exponential growth was itself exponential. That’s one potential consequence of what future tech-heads call the “Singularity,” where computers will be able to create AGIs (artificial general intelligences) more intelligent than human beings. Proponents of the Singularity, most notably the inventor and futurist Ray Kurzweil, say that if computers continue to advance at their current rate, the singularity is a mere 20–30 years away—perhaps sooner if useful quantum computers are developed. Intel is already reinventing the humble transistor by harnessing photons and quantum properties to increase processing power, and Kurzweil has set up the so-called Singularity University, backed by Google and NASA, to educate the next generation in making the Singularity possible.

Moreover, an intellect would not need to be humanlike to be reckoned with. In many ways it could be worse to deal with if it were not, because it’s entirely possible that such an intellect could not be reasoned with using human logic or emotion. the condensed idea Machines much smarter than people timeline 2011 Voice declines significantly as a human-to-human communication medium 2040 AGI (artificial general intelligence) exists 2045 The distinction between virtual and real life becomes almost meaningless 2050 Full virtual-reality immersion 2060 The first human brain enters a machine body 2070 Computer viruses become the main threat to human existence 2080 Scientists acknowledge that immortality exists for those that want it 2095 Human-robot hybrids (brains in boxes) take off to explore distant galaxies 47 Me or we?

Gus Bally, Arcade Inc. 1994 “I will believe in the 500-channel world only when I see it.” Sumner Redstone, chairman, Viacom and CBS 2002 “There is no doubt that Saddam Hussein has weapons of mass destruction.” Dick Cheney Glossary 3D printer A way to produce 3D objects from digital instructions and layered materials dispersed or sprayed on via a printer. Affective computing Machines and systems that recognize or simulate human effects or emotions. AGI Artificial general intelligence, a term usually used to describe strong AI (the opposite of narrow or weak AI). It is machine intelligence that is equivalent to, or exceeds, human intelligence and it’s usually regarded as the long-term goal of AI research and development. Ambient intelligence Electronic or artificial environments that recognize the presence of other machines or people and respond to their needs. Artificial photosynthesis The artificial replication of natural photosynthesis to create or store solar fuels.

pages: 377 words: 97,144

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


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

This “crowdsourcing,” which occurs when a problem is thrown open to anyone, helps a company by allowing them to draw on the talents of strangers, while only paying the strangers if they help the firm. This kind of crowdsourcing works only if, as with a video recommendation system, there is an easy and objective way of measuring progress toward the crowdsourced goal. 13.Potential Improvement All the Way Up to Superhuman Artificial General Intelligence—A recommendation AI could slowly morph into a content creator. At first, the AI might make small changes to content, such as improving sound quality, zooming in on the interesting bits of the video, or running in slow motion the part of a certain cat video in which a kitten falls into a bowl of milk. Later, the AI might make more significant alterations by, for example, developing a mathematical model of what people consider cute in kittens, and then changing kittens’ appearances to make them cuter.

THE SINGULARITY INSTITUTE Michael Vassar, a director and former president of the Singularity Institute for Artificial Intelligence, has told me that he would like an endowment of about $50 million to fund a serious program to create a seed AI that will undergo an intelligence explosion and create a friendly artificial intelligence, although he said that a $10 million endowment would be enough to mount a serious effort. Even with the money, Vassar admitted, the Institute would succeed only if it attracted extremely competent programmers because the programming team would be working under the disadvantage of trying to make an AI that’s mathematically certain to yield a friendly ultra-intelligence, whereas other organizations trying to build artificial general intelligence might not let concerns about friendliness slow them down. The Institute’s annual budget is currently around $500,000 per year. Even if Eliezer and the Singularity Institute have no realistic chance of creating a friendly AI, they still easily justify their institute’s existence. As Michael Anissimov, media director for the Institute, once told me in a personal conversation, at the very least the Institute has reduced the chance of humanity’s destruction by repeatedly telling artificial-intelligence programmers about the threat of unfriendly AI.

Robots have the potential to be another huge source of demand for computing hardware. And, of course, robots would necessarily have at least limited artificial intelligence. I doubt much time would elapse between the creation of Rosie, the robot maid on the 1960s TV show The Jetsons, and a Singularity. Similarly, I believe we would have a Singularity thrust upon us very quickly after someone creates an AI like HAL from the movie 2001: A Space Odyssey. Any artificial general intelligence such as HAL could almost certainly become much smarter and more capable just by running on faster or more numerous computers. Consequently (and perhaps tragically), I strongly suspect that: HAL + Continued Exponential Growth in Computing Power = Not-Too-Distant Singularity Brain implants that can raise the general intelligence of a healthy person would be a strong sign that mankind is near a Singularity.

pages: 589 words: 147,053

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


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

Obviously, the first 30 years of such forecasts were quite wrong. However, researchers who don’t go out of their way to publish predictions, but are instead asked for forecasts in a survey, tend to give durations roughly 10 years longer than researchers who do make public predictions (Armstrong and Sotala 2012; Grace 2014). Shorter durations are given by researchers in the small AI subfield of “artificial general intelligence,” which is more ambitious in trying to write software that is good at a great many tasks at once. A recent survey of the 100 most cited living AI researchers got 29 responses, who gave a median forecast of 37 years until there is a 50% chance of human level AI (Müller and Bostrom 2014). Incidentally, none of those 29 thought that brain emulation “might contribute the most” to human level AI.

The size, location, and specializations of clans, firms, and cities are also distorted in the direction of making such things easier to defend, and better able to launch successful attacks. For example, if it is hard to protect cities against nuclear attacks, cities will be smaller and spread further apart. However, to the extent that there are em enclaves well protected against attack, those probably look more like the scenario described in this book. In a second variation, we might create artificial general intelligence that is similar to ems, except that it is made via a shallower analysis of higher-level human brain processes, instead of via directly emulating lower-level brain processes as in a classic em. Such variations on ems probably are not greatly redesigned at the highest levels of organization, and thus are relatively human in behavior and style. The main ways these differ from ems is that they probably do not remember being human, they might not run as easily on parallel computer hardware, and they might require a lot less computer hardware.

“Democracy and the Variability of Economic Performance.” Economics and Politics 14(3): 225–257. Alston, Julian, Matthew Andersen, Jennifer James, and Philip Pardey. 2011. “The Economic Returns to U.S. Public Agricultural Research.” American Journal of Agricultural Economics 93(5): 1257–1277. Alstott, Jeff. 2013. “Will We Hit a Wall? Forecasting Bottlenecks to Whole Brain Emulation Development.” Journal of Artificial General Intelligence 4(3): 153–163. Alvanchi, Amin, SangHyun Lee, and Simaan AbouRizk. 2012. “Dynamics of Working Hours in Construction.” Journal of Construction Engineering and Management 138(1): 66–77. Alwin, Duane, and Jon Krosnick. 1991. “Aging, Cohorts, and the Stability of Sociopolitical Orientations Over the Life Span.” American Journal of Sociology 97(1): 169–195. Anderson, David. 1999. “The Aggregate Burden of Crime.”

pages: 481 words: 125,946

What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence by John Brockman


3D printing, agricultural Revolution, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, bitcoin, blockchain, clean water, cognitive dissonance, Colonization of Mars, complexity theory, computer age, computer vision, constrained optimization, corporate personhood, cosmological principle, cryptocurrency, cuban missile crisis, Danny Hillis, dark matter, discrete time, Elon Musk, Emanuel Derman, endowment effect, epigenetics, Ernest Rutherford, experimental economics, Flash crash, friendly AI, Google Glasses, hive mind, income inequality, information trail, Internet of things, invention of writing, iterative process, Jaron Lanier, job automation, John von Neumann, Kevin Kelly, knowledge worker, loose coupling, microbiome, Moneyball by Michael Lewis explains big data, natural language processing, Network effects, Norbert Wiener, pattern recognition, Peter Singer: altruism, phenotype, planetary scale, Ray Kurzweil, recommendation engine, Republic of Letters, RFID, Richard Thaler, Rory Sutherland, Search for Extraterrestrial Intelligence, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, superintelligent machines, supervolcano, the scientific method, The Wisdom of Crowds, theory of mind, Thorstein Veblen, too big to fail, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K

One doesn’t need to be a superintelligent AI to realize that running unprepared toward the biggest event in human history would be just plain stupid. “TURING+” QUESTIONS TOMASO POGGIO Eugene McDermott Professor, Department of Brain and Cognitive Sciences, and director, Center for Brains, Minds, and Machines, MIT Recent months have seen an increasingly public debate forming around the risks of artificial intelligence—in particular, AGI (artificial general intelligence). AI has been called by some (including the physicist Stephen Hawking) the top existential risk to humankind, and such recent films as Her and Transcendence have reinforced the message. Thoughtful comments by experts in the field—Rod Brooks and Oren Etzioni among them—have done little to settle the debate. I argue here that research on how we think and on how to make machines that think is good for society.

My suspicion is that replicating the effectiveness of this evolved intelligence in an artificial agent will require amounts of computation not that much lower than evolution has required, which would far outstrip our abilities for many decades, even given exponential growth in computational efficiency per Moore’s Law—and that’s even if we understood how to correctly employ that computation. I assign a probability of about 1 percent for artificial general intelligence (AGI) arising in the next ten years, and about 10 percent over the next thirty years. (This essentially reflects a probability that my analysis is wrong, times a probability more representative of AI experts, who—albeit with lots of variation—tend to assign somewhat higher numbers.) On the other hand, I assign a rather high probability that, if AGI is created (and especially if it arises relatively quickly), it will be—in a word—insane.

ZIYAD MARAR Global publishing director, SAGE; author, Intimacy: Understanding the Subtle Power of Human Connection There’s something old-fashioned about visions of the future. The majority of predictions, like three-day weeks, personal jet packs, and the paperless office, tell us more about the times in which they were proposed than about contemporary experience. When people point to the future, we’d do well to run an eye back up the arm to see who’s doing the pointing. The possibility of artificial general intelligence has long invited such crystal-ball gazing, whether utopian or dystopian in tone. Yet speculations on this theme have reached such a pitch and intensity in the last few months alone (enough to trigger an Edge Question, no less) that this may reveal something about ourselves and our culture today. We’ve known for some time that machines can outthink humans in a narrow sense. The question is whether they do so in any way that could or should ever resemble the baggier mode of human thought.

pages: 238 words: 77,730

Final Jeopardy: Man vs. Machine and the Quest to Know Everything by Stephen Baker


23andMe, AI winter, Albert Einstein, artificial general intelligence, business process, call centre, clean water, computer age, Frank Gehry, information retrieval, Iridium satellite, Isaac Newton, job automation, pattern recognition, Ray Kurzweil, Silicon Valley, Silicon Valley startup, statistical model, theory of mind, thinkpad, Turing test, Vernor Vinge, Wall-E, Watson beat the top human players on Jeopardy!

In August 2010, hundreds of computer scientists, cognitive psychologists, futurists, and curious technophiles descended on San Francisco’s Hyatt hotel, on the Embarcadero, for the two-day Singularity Summit. For most of these people, programming machines to catalogue knowledge and answer questions, whether manually or by machine, was a bit pedestrian. They weren’t looking for advances in technology that already existed. Instead, they were focused on a bolder challenge, the development of deep and broad machine intelligence known as Artificial General Intelligence. This, they believed, would lead to the next step of human evolution. The heart of the Singularity argument, as explained by the technologists Vernor Vinge and Ray Kurzweil, the leading evangelists of the concept, lies in the power of exponential growth. As Samuel Butler noted, machines evolve far faster than humans. But information technology, which Butler only glimpsed, races ahead at an even faster rate.

A diminutive thirty-four-year-old British neuroscientist, Hassabis told the crowd that technology wasn’t the only thing growing exponentially. Research papers on the brain were also doubling every year. Some fifty thousand academic papers on neuroscience had been published in 2008 alone. “If you looked at neuroscience in 2005, or before that, you’re way out of date now,” he said. But which areas of brain research would lead to the development of Artificial General Intelligence? Hassabis had followed an unusual path toward AI research. At thirteen, he was the highest ranked chess player of his age on earth. But computers were already making inroads in chess. So why dedicate his brain, which he had every reason to believe was exceptional, to a field that machines would soon conquer? (From the perspective of futurists, chess was an early sighting of the Singularity.)

pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman


23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, mobile money, more computing power than Apollo, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, offshore financial centre, optical character recognition, pattern recognition, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, WikiLeaks, Y Combinator, zero day

“Don Watson” might even engage in murder for hire by geo-locating human targets and hacking into objects connected to the Internet of Things surrounding victims, such as cars, elevators, and robots, in order to cause accidents resulting in the death of its prey. While such activities would be at the extreme level of what a narrow AI might accomplish, they would be easy for the next generation of computing: artificial general intelligence. Man’s Last Invention: Artificial General Intelligence By the time Skynet became self-aware, it had spread into millions of computer servers all across the planet. Ordinary computers in office buildings, dorm rooms, everywhere. It was software, in cyberspace. There was no system core. It could not be shut down. JOHN CONNOR, TERMINATOR 3: RISE OF THE MACHINES Ray Kurzweil has popularized the idea of the technological singularity: that moment in time in which nonhuman intelligence exceeds human intelligence for the first time in history—a shift so profound that it’s often been referred to as our “final invention.”

It’s Written All Over Your Face On Your Best Behavior Augmenting Reality The Rise of Homo virtualis CHAPTER 15: RISE OF THE MACHINES: WHEN CYBER CRIME GOES 3-D We, Robot The Military-Industrial (Robotic) Complex A Robot in Every Home and Office Humans Need Not Apply Robot Rights, Law, Ethics, and Privacy Danger, Will Robinson Hacking Robots Game of Drones Robots Behaving Badly Attack of the Drones The Future of Robotics and Autonomous Machines Printing Crime: When Gutenberg Meets Gotti CHAPTER 16: NEXT-GENERATION SECURITY THREATS: WHY CYBER WAS ONLY THE BEGINNING Nearly Intelligent Talk to My Agent Black-Box Algorithms and the Fallacy of Math Neutrality Al-gorithm Capone and His AI Crime Bots When Watson Turns to a Life of Crime Man’s Last Invention: Artificial General Intelligence The AI-pocalypse How to Build a Brain Tapping Into Genius: Brain-Computer Interface Mind Reading, Brain Warrants, and Neuro-hackers Biology Is Information Technology Bio-computers and DNA Hard Drives Jurassic Park for Reals Invasion of the Bio-snatchers: Genetic Privacy, Bioethics, and DNA Stalkers Bio-cartels and New Opiates for the Masses Hacking the Software of Life: Bio-crime and Bioterrorism The Final Frontier: Space, Nano, and Quantum PART THREE SURVIVING PROGRESS CHAPTER 17: SURVIVING PROGRESS Killer Apps: Bad Software and Its Consequences Software Damages Reducing Data Pollution and Reclaiming Privacy Kill the Password Encryption by Default Taking a Byte out of Cyber Crime: Education Is Essential The Human Factor: The Forgotten Weak Link Bringing Human-Centered Design to Security Mother (Nature) Knows Best: Building an Immune System for the Internet Policing the Twenty-First Century Practicing Safe Techs: The Need for Good Cyber Hygiene The Cyber CDC: The World Health Organization for a Connected Planet CHAPTER 18: THE WAY FORWARD Ghosts in the Machine Building Resilience: Automating Defenses and Scaling for Good Reinventing Government: Jump-Starting Innovation Meaningful Public-Private Partnership We the People Gaming the System Eye on the Prize: Incentive Competitions for Global Security Getting Serious: A Manhattan Project for Cyber Final Thoughts Appendix: Everything’s Connected, Everyone’s Vulnerable: Here’s What You Can Do About It Acknowledgments Notes PROLOGUE The Irrational Optimist: How I Got This Way My entrée into the world of high-tech crime began innocuously in 1995 while working as a twenty-eight-year-old investigator and sergeant at the LAPD’s famed Parker Center police headquarters.

• Heavier-than-air flying machines are impossible (Lord Kelvin, British mathematician, physicist, and president of the Royal Society, 1895). • This “telephone” has too many shortcomings to be seriously considered as a means of communication. The device is inherently of no value to us (internal memo at Western Union, 1878). Somehow, the impossible always seems to become the possible. In the world of artificial intelligence, that next phase of development is called artificial general intelligence (AGI), or strong AI. In contrast to narrow AI, which cleverly performs a specific limited task, such as machine translation or auto navigation, strong AI refers to “thinking machines” that might perform any intellectual task that a human being could. Characteristics of a strong AI would include the ability to reason, make judgments, plan, learn, communicate, and unify these skills toward achieving common goals across a variety of domains, and commercial interest is growing.

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


A Declaration of the Independence of Cyberspace, AI winter, airport security, Apple II, artificial general intelligence, augmented reality, autonomous vehicles, 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 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, 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 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, 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

When pressed, the computer scientists, roboticists, and technologists offer conflicting views. Some want to replace humans with machines; some are resigned to the inevitability—“I for one, welcome our insect overlords” (later “robot overlords”) was a meme that was popularized by The Simpsons—and some of them just as passionately want to build machines to extend the reach of humans. The question of whether true artificial intelligence—the concept known as “Strong AI” or Artificial General Intelligence—will emerge, and whether machines can do more than mimic humans, has also been debated for decades. Today there is a growing chorus of scientists and technologists raising new alarms about the possibility of the emergence of self-aware machines and their consequences. Discussions about the state of AI technology today veer into the realm of science fiction or perhaps religion. However, the reality of machine autonomy is no longer merely a philosophical or hypothetical question.

., 191–192 aging, of humans, 93–94, 236–237, 245, 327–332 “Alchemy and Artificial Intelligence” (Dreyfus), 177 Allen, Paul, 267, 268, 337 Alone Together (Turkle), 173, 221–222 Amazon, 97–98, 206, 247 Ambler (robot), 33, 202 Anderson, Chris, 88 Andreessen, Marc, 69 Apocalypse AI (Geraci), 85, 116–117 Apple. see also Siri (Apple) early history of, 7, 8, 214, 279–281, 307 iPhone, 23, 93, 239, 275, 281 iPod, 194, 275, 281 Jobs and, 13, 35, 112, 131, 194, 214, 241, 281–282, 320–323 Knowledge Navigator, 188, 300, 304, 305–310, 317, 318 labor force of, 83–84 Rubin and, 240 Sculley and, 35, 280, 300, 305, 306, 307, 317 Architecture Machine, The (Negroponte), 191 Architecture Machine Group, 306–307, 308–309 Arkin, Ronald, 333–335 Armer, Paul, 74 Aronson, Louise, 328 Artificial General Intelligence, 26 artificial intelligence (AI). see artificial intelligence (AI) history; autonomous vehicles; intelligence augmentation (IA) versus AI; labor force; robotics advancement; Siri (Apple) artificial intelligence (AI) history, 95–158. see also intelligence augmentation (IA) versus AI AI commercialization, 156–158 AI terminology, xii, 105–109 AI Winter, 16, 130–131, 140 Breiner and, 125–135 deep learning neural networks, 150–156, 151 early neural networks, 141–150 expert systems, 134–141, 285 McCarthy and, 109–115 Moravec and, 115–125 Silicon Valley inception, 95–99, 100, 256 SRI inception, 99–105 Strong artificial intelligence, 12, 26, 272 “Artificial Intelligence” (Lighthill), 130 “Artificial Intelligence of Hubert L.

pages: 381 words: 78,467

100 Plus: How the Coming Age of Longevity Will Change Everything, From Careers and Relationships to Family And by Sonia Arrison


23andMe, 8-hour work day, Albert Einstein, Anne Wojcicki, artificial general intelligence, attribution theory, Bill Joy: nanobots, bioinformatics, Clayton Christensen, dark matter, East Village,, epigenetics, Frank Gehry, Googley, income per capita, indoor plumbing, Jeff Bezos, Johann Wolfgang von Goethe, Law of Accelerating Returns, life extension, personalized medicine, Peter Thiel, placebo effect, post scarcity, Ray Kurzweil, rolodex, Silicon Valley, Simon Kuznets, Singularitarianism, smart grid, speech recognition, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Levy, Thomas Malthus, upwardly mobile, World Values Survey, X Prize

This means it is both modifiable and reparable, but the biggest problem Goertzel sees is that we have too much data and not enough human bandwidth to analyze everything. “The human brain simply was not evolved for the integrative analysis of a massive number of complexly-interrelated, highdimensional biological datasets,” he writes.15 “In the short term, the most feasible path to working around this problem is to supplement human biological scientists with increasingly advanced AI software, gradually moving toward the goal of an AGI (Artificial General Intelligence) bioscientist.”16 Just as Google is a form of artificial intelligence that allows for fast searching of the Internet, a software program that could “read” biological studies and help to sort the data for human scientists would make the task of finding repair mechanisms for the human body that much easier. Another proponent of this idea is maven Ray Kurzweil. In 1999 President Bill Clinton awarded Ray Kurzweil the National Medal of Technology, the highest honor for technological achievement bestowed by the president of the United States on America’s leading innovators.

pages: 551 words: 174,280

The Beginning of Infinity: Explanations That Transform the World by David Deutsch


agricultural Revolution, Albert Michelson, anthropic principle, artificial general intelligence, Bonfire of the Vanities, conceptual framework, cosmological principle, dark matter, David Attenborough, discovery of DNA, Douglas Hofstadter, Eratosthenes, Ernest Rutherford, first-past-the-post, Georg Cantor, Gödel, Escher, Bach, illegal immigration, invention of movable type, Isaac Newton, Islamic Golden Age, Jacquard loom, Jacquard loom, John Conway, John von Neumann, Joseph-Marie Jacquard, Loebner Prize, Louis Pasteur, pattern recognition, Richard Feynman, Richard Feynman, Search for Extraterrestrial Intelligence, Stephen Hawking, supervolcano, technological singularity, The Coming Technological Singularity, the scientific method, Thomas Malthus, Thorstein Veblen, Turing test, Vernor Vinge, Whole Earth Review, William of Occam

But my guess is that when we do understand them, artificially implementing evolution and intelligence and its constellation of associated attributes will then be no great effort. TERMINOLOGY Quale (plural qualia) The subjective aspect of a sensation. Behaviourism Instrumentalism applied to psychology. The doctrine that science can (or should) only measure and predict people’s behaviour in response to stimuli. SUMMARY The field of artificial (general) intelligence has made no progress because there is an unsolved philosophical problem at its heart: we do not understand how creativity works. Once that has been solved, programming it will not be difficult. Even artificial evolution may not have been achieved yet, despite appearances. There the problem is that we do not understand the nature of the universality of the DNA replication system. 8 A Window on Infinity Mathematicians realized centuries ago that it is possible to work consistently and usefully with infinity.

Anything that is copied, for whatever reason, he calls a replicator. What I call a replicator he calls an ‘active replicator’. *These are not the ‘parallel universes’ of the quantum multiverse, which I shall describe in Chapter 11. Those universes all obey the same laws of physics and are in constant slight interaction with each other. They are also much less speculative. * Hence what I am calling ‘AI’ is sometimes called ‘AGI’: Artificial General Intelligence. *First, they announce to the existing guests, ‘For each natural number N, will the guest in room number N please move immediately to room number N (N +1)/2.’ Then they announce, ‘For all natural numbers N and M, will the Nth passenger from the Mth train please go to room number [(N + M)2 + N – M/2.’ *In the story as told by Plato in his Apology, Chaerophon asks the Oracle whether there is anyone wiser than Socrates, and is told no.

pages: 347 words: 97,721

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby


AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, Google Glasses, Hans Lippershey, haute cuisine, income inequality, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Khan Academy, knowledge worker, labor-force participation, loss aversion, Mark Zuckerberg, Narrative Science, natural language processing, Norbert Wiener, nuclear winter, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative finance, Ray Kurzweil, Richard Feynman, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, transaction costs, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar

Vendors like IBM, Cognitive Scale, SAS, and Tibco are adding new cognitive functions and integrating them into solutions. Deloitte is working with companies like IBM and Cognitive Scale to create not just a single application, but a broad “Intelligent Automation Platform.” Even when progress is made on these types of integration, the result will still fall short of the all-knowing “artificial general intelligence” or “strong AI” that we discussed in Chapter 2. That may well be coming, but not anytime soon. Still, these short-term combinations of tools and methods may well make automation solutions much more useful. Broadening Application of the Same Tools —In addition to employing broader types of technology, organizations that are stepping forward are using their existing technology to address different industries and business functions.

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


additive manufacturing, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, augmented reality, autonomous vehicles, Benoit Mandelbrot, Bill Joy: nanobots, bioinformatics, brain emulation, Brewster Kahle, Brownian motion, business intelligence,, 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,, 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, 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, Rodney Brooks, Search for Extraterrestrial Intelligence, 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, transaction costs, Turing machine, Turing test, Vernor Vinge, Y2K, Yogi Berra

Yudkowsky formed the Singularity Institute for Artificial Intelligence (SIAI) to develop "Friendly AI," intended to "create cognitive content, design features, and cognitive architectures that result in benevolence" before near-human or better-than-human Als become possible. SIAI has developed The SIAI Guidelines on Friendly AI: "Friendly AI," Ben Goertzel and his Artificial General Intelligence Research Institute have also examined issues related to developing friendly AI; his current focus is on developing the Novamente AI Engine, a set of learning algorithms and architectures. Peter Voss, founder of Adaptive A.I., Inc., has also collaborated on friendly-AI issues: 46. Integrated Fuel Cell Technologies, Disclosure: The author is an early investor in and adviser to IFCT. 47.

pages: 669 words: 210,153

Tools of Titans: The Tactics, Routines, and Habits of Billionaires, Icons, and World-Class Performers by Timothy Ferriss


Airbnb, artificial general intelligence, asset allocation, Atul Gawande, augmented reality, back-to-the-land, Bernie Madoff, Bertrand Russell: In Praise of Idleness, Black Swan, blue-collar work, Buckminster Fuller, business process, Cal Newport, call centre, Checklist Manifesto, cognitive bias, cognitive dissonance, Colonization of Mars, Columbine, correlation does not imply causation, David Brooks, David Graeber, diversification, diversified portfolio, Donald Trump, effective altruism, Elon Musk, fault tolerance, fear of failure, Firefox, follow your passion, future of work, Google X / Alphabet X, Howard Zinn, Hugh Fearnley-Whittingstall, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Kickstarter, Lao Tzu, life extension, Mahatma Gandhi, Mark Zuckerberg, Mason jar, Menlo Park, Mikhail Gorbachev, Nicholas Carr, optical character recognition, PageRank, passive income, pattern recognition, Paul Graham, Peter H. Diamandis: Planetary Resources, Peter Singer: altruism, Peter Thiel, phenotype, post scarcity, premature optimization, QWERTY keyboard, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, rent-seeking, Richard Feynman, Richard Feynman, risk tolerance, Ronald Reagan, sharing economy, side project, Silicon Valley, skunkworks, Skype, Snapchat, social graph, software as a service, software is eating the world, stem cell, Stephen Hawking, Steve Jobs, Stewart Brand, superintelligent machines, Tesla Model S, The Wisdom of Crowds, Thomas L Friedman, Wall-E, Washington Consensus, Whole Earth Catalog, Y Combinator

Libin, Phil: “So just imagine it’s me with a big glass of whiskey. And the caption will say, ‘Evernote helps you remember. Suntory helps you forget.’” MacAskill, Will: “It would be outside the Gates Foundation, or maybe outside Bill Gates’s house . . . where ultimately, he’s going to donate $100 billion. And it would say, ‘Bill, you have spoken about the risks and potential upside in the long run from development of artificial general intelligence, yet you’re not doing anything about it yet. You haven’t gotten involved.’” MacKenzie, Brian: “‘Ego is how we want the world to see us. Confidence is how we see ourselves.’” McCarthy, Nicholas: “‘Anything is possible.’ I wholeheartedly believe that. Why wouldn’t I think that? Because for a guy who’s from a non-classical background, from a non-money background, from a very small village in England—no one’s really done a great deal where I’m from—and with one arm as well, and the age that I started, to then enter this arena of highbrow classical music and honing your craft to the highest level . . .