artificial general intelligence
description: theoretical class of AI able to perform any intelligence-based task a human can
119 results
Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the Agi Workshop 2006
by Ben Goertzel and Pei Wang · 1 Jan 2007 · 303pp · 67,891 words
The publisher is not responsible for the use which might be made of the following information. PRINTED IN THE NETHERLANDS ADVANCES IN ARTIFICIAL GENERAL INTELLIGENCE: CONCEPTS, ARCHITECTURES AND ALGORITHMS 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
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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
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extent of producing publications and preliminary results. More or less coincidentally, several books have appeared within 4 P. Wang and B. Goertzel / Introduction: Aspects of Artificial General Intelligence the last few years, presenting several AGI projects, with theoretical and technical designs with various levels of detail [2]; [16]; [3]; [17]; [5]; [6
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– but rather that attention should be paid to resolving the outstanding issues through concerted research. 8 P. Wang and B. Goertzel / Introduction: Aspects of Artificial General Intelligence 3.7. “AGI research is not fruitful” Some oppositions to AGI research come mainly from practical considerations. Given the nature of the problem, research results
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contemporary AI work, computational language learning is one thing, and learning about physical objects and 12 P. Wang and B. Goertzel / Introduction: Aspects of Artificial General Intelligence their interrelationships is something else entirely. In an integrated intelligent mind, however, language and physical reality are closely interrelated. AGI research, to be effective, must
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control (the concrete operational stage); inference-based inference control (the formal stage); and inference-based modification P. Wang and B. Goertzel / Introduction: Aspects of Artificial General Intelligence 15 of inference rules (the post-formal stage). The pragmatic implications of this view of cognitive development are discussed in the context of classic Piagetan
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Intelligence: Sequential Decisions based on Algorithmic Probability, Springer, 2005. [4] B. Goertzel. The Structure of Intelligence, Springer, 1993. [5] B. Goertzel and C. Pennachin (editors), Artificial General Intelligence, Springer, 2007. [6] B. Goertzel. The Hidden Pattern, BrownWalker, 2006. [7] J. Searle, Minds, Brains, and Programs, Behavioral and Brain Sciences 3 (1980), 417
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2002. [26] J. Schmidhuber, Goedel machines: self-referential universal problem solvers making provably optimal self-improvements. In B. Goertzel and C. Pennachin (editors), Artificial General Intelligence, 2006. 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. 17
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] 18.“...the essential, domain-independent skills necessary for acquiring a wide range of domain-specific knowledge – the ability to learn anything. Achieving this with `artificial general intelligence' (AGI) requires a highly adaptive, generalpurpose system that can autonomously acquire an extremely wide range of specific knowledge and skills and can improve its own
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October 14, 2003. [41] P. Voss. Essentials of general intelligence: The direct path to AGI. In B. Goertzel and C. Pennachin, editors, Artificial General Intelligence. Springer-Verlag, 2005. 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. 25
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mostly based on the conceptual framework presented in Stan Franklin’s workshop presentation (and represented in this volume by his article “A Foundational Architecture for Artificial General Intelligence”) with a couple additions and variations. All individuals who presented talks on AGI architectures at the workshop were invited to respond to the questionnaire,
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Algorithms B. Goertzel and P. Wang (Eds.) IOS Press, 2007 © 2007 The authors and IOS Press. All rights reserved. 36 A Foundational Architecture for Artificial General Intelligence Stan FRANKLIN Computer Science Department & Institute for Intelligent Systems, The University of Memphis Abstract. Implementing and fleshing out a number of psychological and neuroscience theories
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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
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memory includes autobiographical memory, the memory of events as described above, and semantic memory, the memory for facts. S. Franklin / A Foundational Architecture for Artificial General Intelligence 41 Figure 6. Attention and Action Selection. Attention & Action Selection In this section the gray “rest of cognition box” has disappeared, to be replaced by
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another filtering process that decides what part of the recent percepts and episodic recall to bring to conscious- 42 S. Franklin / A Foundational Architecture for Artificial General Intelligence ness. Again the criteria for this filtering include relevance, importance, urgency, and insistence. Procedural memory then uses the contents of consciousness, what comes to
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is to dive right in and attempt to build a Perceptual Learning Encode Procedural Learning Figure 7. Learning. S. Franklin / A Foundational Architecture for Artificial General Intelligence 43 full-blown AGI directly. This strategy, while surely ambitious, may well succeed. A second possible strategy might be to construct a sequence of increasingly
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perceptual memory. Their instantiations as sequences of actions contribute to perceptual learning, including conceptualization, leading to further understanding. S. Franklin / A Foundational Architecture for Artificial General Intelligence 45 Figure 9. Sloman’s Architecture. The long-term working memory of Ericsson and Kinstch [42] is incorporated into LIDA’s workspace (see below), in
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a continuously iterating cognitive cycle. Higher-level cognitive processes are composed of sequences of several or many of 46 S. Franklin / A Foundational Architecture for Artificial General Intelligence these cognitive cycles. Such higher-level cognitive processes might include deliberation, volition, problem solving, and metacognition. Let’s take a quick, guided tour through
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TEM encodings decay in humans within hours or a day. DM encodings Figure 10. The LIDA Cognitive Cycle. S. Franklin / A Foundational Architecture for Artificial General Intelligence 47 only occur through offline consolidation from TEM. Though they can decay away, when sufficiently reinforced DM encodings can last a lifetime. Both episodic memories
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Cambridge: Cambridge University Press. [19] Baars, B. J. 1997. In the Theater of Consciousness. Oxford: Oxford University Press. S. Franklin / A Foundational Architecture for Artificial General Intelligence 53 [20] Baars, B. J. 2002. The conscious access hypothesis: origins and recent evidence. Trends in Cognitive Science 6:47–52. [21] Franklin, S. 2003
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Columbia, Canada. Vancouver, British Columbia, Canada. [51] Edelman, G. M. 1987. Neural Darwinism. New York: Basic Books. 54 S. Franklin / A Foundational Architecture for Artificial General Intelligence [52] Lehmann, D., H. Ozaki, and I. Pal. 1987. EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. Electroencephalogr. Clin. Neurophysiol. 67
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sides of the same coin. In Proceedings of the Sixth International Workshop on Epigenetic Robotics, vol. 128. Paris, France: Lund University Cognitive Studies. 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. 55 A
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, Eric. (2004) What is Thought? MIT Press, Cambridge, MA. [3] Hutter, M. (2006) Universal Algorithmic Intelligence: A Mathematical Top->Down Approach,pp 228291 in Artificial General Intelligence (Cognitive Technologies) (Hardcover) by Ben Goertzel and Cassio Pennachin (eds), Springer 74 E. Baum / A Working Hypothesis for General Intelligence [4] Schmidhuber, J.(2004) Optimal
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Norton, 1963. [12] L. Birnbaum, Rigor mortis: a response to Nilsson's “Logic and artificial intelligence”, Artificial Intelligence 47 (1991), 57-77. 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. 94 Adaptive Algorithmic
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C. Schultz, “Integrating Cognition, Perception, and Action through Mental Simulation in Robots,” Robotics and Autonomous Systems, vol. 49, pp. 13–23, 2004. 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. 111 Cognitive Map
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of Computer Science and Science Applications International Corporation (SAIC), Integrated Intelligence Solutions Operation and Novamente LLC Abstract. A program evolution component is proposed for integrative artificial general intelligence. The system’s deployment is intended to be comparable, on Marr’s level of computational theory, to evolutionary mechanisms in human thought. The challenges
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celoxica.com [5] Peter N. Martin, Genetic Programming in Hardware, PhD thesis, University of Essex, 2003, http://homepage.ntlworld.com/petemartin/HardwareGeneticProgramming.pdf 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. 159 Complex
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of Experimental Child Psychology, 1994, 58, 184-199. [5] B. Goertzel, C. Pennachin, A. Senna, T. Maia, G. Lamacie. “Novamente: an integrative architecture for Artificial General Intelligence.” Proceedings of IJCAI 2003 Workshop on Cognitive Modeling of Agents. Acapulco, Mexico, 2004. [6] M. Looks, B. Goertzel and C. Pennachin. “Novamente: an integrative architecture
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for Artificial General Intelligence.” Proceedings of AAAI 2004 Symposium on Achieving Human-Level AI via Integrated Systems and Research, Washington DC, 2004. [7] B. Goertzel and Cassio Pennachin. “The
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[59] T. Gilovich, D. Griffin & D. Kahneman, (Eds.). Heuristics and biases: The psychology of intuitive judgment. Cambridge, UK: Cambridge University Press, 2002 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. 195 Indefinite Probabilities
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College, Alamosa, Colorado and Novamente LLC b Novamente LLC Abstract. The creation of robust mechanisms for uncertain inference is central to the development of Artificial General Intelligence systems. While probability theory provides a principled foundation for uncertain inference, the mathematics of probability theory has not yet been developed to the point where
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heuristic ones), we argue that this mode of quantifying uncertainty may be adequate to serve as an ingredient of powerful artificial general intelligence. Introduction As part of our ongoing work on the Novamente artificial general intelligence (AGI) system, we have developed a logical inference system called Probabilistic Logic Networks (PLN), designed to handle the
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9, 2004, Pages 837–857. [15] Ben Goertzel, Matthew Iklé, “Revision of Indefinite Probabilities via Entropy Minimization”, in preparation, expected publication 2007. 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. 217 Virtual Easter
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Social Learning, Cognitive Process Integration, and the Dynamic Emergence of the Self Ben GOERTZEL Novamente LLC Abstract. The Novamente Cognition Engine (NCE) architecture for Artificial General Intelligence is briefly reviewed, with a focus on exploring how the various cognitive processes involved in the architecture are intended to cooperate in carrying out moderately
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The Growth of Logical Thinking from Childhood to Adolescence. 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
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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
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29] Yudkowsky, Eliezer (2007). Artificial Intelligence and Global Risk, in Global Catastrophic Risks, Ed. by Nick Bostrom and Milan Cirkovic, Oxford University Press. 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. 253 Probabilistic Logic
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these aspects, which draws on probability theory and algorithmic information theory, among other areas. Unlike most contemporary AI projects, it is specifically oriented towards artificial general intelligence (AGI), rather than being restricted by design to one narrow domain or range of cognitive functions. The NAIE integrates aspects of prior AI projects and
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the first International Conference on Simulation of Adaptive Behavior, Meyer J.A. and Wilson S. (eds.). MIT Press. Franklin, S. (2006). A Foundational Architecture for Artificial General Intelligence, this volume. Ikle’, M., Goertzel, B. and Goertzel, I. (2006). Quantifying Weight of Evidence in Uncertain Inference via Hybridizing Confidence Intervals and Imprecise Probabilities,
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Goertzel, B. and Goertzel, I. (2006). Quantifying Weight of Evidence in Uncertain Inference via Hybridizing Confidence Intervals and Imprecise Probabilities, this volume 276 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. How Do
The Age of Extraction: How Tech Platforms Conquered the Economy and Threaten Our Future Prosperity
by Tim Wu · 4 Nov 2025 · 246pp · 65,143 words
prosperity to a degree that seems unimaginable today.”[7] In an interview with author Nate Silver, Altman said, “If you have something like an AGI [artificial general intelligence], I think poverty really does just end.”[8] I take Altman as well-meaning and there is an admirable optimism in this declaration. But it
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, 107, 130, 131–32, 138, 139, 159, 166–68 line of business restrictions on platforms, 170–71 neutrality rules, 38–40, 162–64 ARPANET, 43 artificial general intelligence, 6 artificial intelligence (AI), 6, 72 as challenge to platform monopoly, 95–99 chatbots, 20, 79, 88, 90, 94–95, 98–99, 101 Connectionist, 91
Against the Machine: On the Unmaking of Humanity
by Paul Kingsnorth · 23 Sep 2025 · 388pp · 110,920 words
, take an essay published in the usually staid Time magazine,[2] in which AI researcher Eliezer Yudkowsky, regarded as a leader in the field of artificial general intelligence, responded to the tech gurus’ call for a moratorium in AI development. Yudkowsky didn’t join that call, because, in his words, ‘I think the
Gilded Rage: Elon Musk and the Radicalization of Silicon Valley
by Jacob Silverman · 9 Oct 2025 · 312pp · 103,645 words
regulate it?” Schmidt remarked about AI.4 He said that humanity’s only hope for stymieing climate change was a breakneck pursuit of AGI, or artificial general intelligence, a greater-than-human intelligence that will be able, somehow, to solve the problem for us. Schmidt represented a Silicon Valley variant of an increasingly
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of innovation and profit. It had a sense of religiosity, but God had been dethroned by AI—or at least by the promise of creating Artificial General Intelligence, also known as AGI, a greater-than-human intelligence that many seemed to think was only months or years away from emerging. AGI would change
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the tech industry, everything that had been developed in the AI field was just a preamble to the sole pursuit that mattered: the creation of artificial general intelligence, or AGI. The so-called “last invention,” AGI would be a revolutionary leap forward in computing that would produce a greater-than-human intelligence. AGI
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, Ahmad here, here, here Ackman, Bill here, here Activision here Adams, Eric here, here Adams, Scott here Adelson, Miriam here, here Agarwal, Sachin here AGI (artificial general intelligence) here, here, here Al Ahmed, Ali here, here, here, here, here AI (artificial intelligence) here, here, here, here, here and the 2024 election here Project
Nexus
by Ramez Naam · 16 Dec 2012 · 502pp · 124,794 words
yielded up a plethora of fascinating talks: Neural Substrates of Symbolic Reasoning, Intelligence and Prospects for Increasing It, Emotive-Loop Programming: A New Path to Artificial General Intelligence. How could they even hold these talks? In the US the topics of half of them would be classified as Emerging Technological Threats. No wonder
Smarter Than Us: The Rise of Machine Intelligence
by Stuart Armstrong · 1 Feb 2014 · 48pp · 12,437 words
Evolution and Technology 22, no. 1 (2012): 116–131, http://jetpress.org/v22/goertzel-pitt.htm. 4. Ben Goertzel, “CogPrime: An Integrative Architecture for Embodied Artificial General Intelligence,” OpenCog Foundation, October 2, 2012, accessed December 31, 2012, http://wiki.opencog.org/w/CogPrime_Overview. Chapter 10 A Summary There are no convincing reasons
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,” 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
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, 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. http://wiki.opencog.org/w/CogPrime_Overview. Goertzel, Ben, and Joel Pitt. “Nine Ways to Bias
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(blog), April 8, 2007. http://amartester.blogspot.co.uk/2007/04/bugs-per-lines-of-code.html. Omohundro, Stephen M. “The Basic AI Drives.” In Artificial General Intelligence 2008: Proceedings of the First AGI Conference, 483–492. Frontiers in Artificial Intelligence and Applications 171. Amsterdam: IOS, 2008. Parameswaran, Ashwin. “People Make Poor Monitors
Scary Smart: The Future of Artificial Intelligence and How You Can Save Our World
by Mo Gawdat · 29 Sep 2021 · 259pp · 84,261 words
unlikely. I think you AGreeP. If You Can’t Beat Them . . . Some of those who recognize that we will not be able to control an artificial general intelligence that is smarter than us, suggest that we plug them directly into our bodies instead. A sort of ‘if you can’t beat them, join
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Turing predicted that ‘once the machine thinking method had started, it would not take long to outstrip our feeble powers.’ As AI transitions to AGI, artificial general intelligence, and beyond the confines of the programmable tasks the machine was invented to carry out, the concerns heighten. Irving Good, who was a consultant on
The Driver in the Driverless Car: How Our Technology Choices Will Create the Future
by Vivek Wadhwa and Alex Salkever · 2 Apr 2017 · 181pp · 52,147 words
arrive at something resembling original works or to solve unstructured problems without benefit of specific rules or guidance. Such broader reasoning ability is known as artificial general intelligence (A.G.I.), or hard A.I. One step beyond this is artificial superintelligence, the stuff out of science fiction that is still so far
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clean the bathroom. And I expect that she will be as witty and lovable as she was on TV. No, she won’t have the artificial general intelligence that will make her seem human, but she will be able to have fun conversations with us. In fact, a very limited version of Rosie
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, 23, 72n, 181, 186–187, 189 AIC Chile, 181 Airliner, supersonic, 7 Anderson, Chris, 115 Anger in society, 3–4 Argus retinal prosthesis, 167–168 Artificial general intelligence (A.G.I.), 40 Artificial intelligence (A.I.), 7, 12, 13. See also specific topics benefits of, 43 fostering autonomy vs. dependence, 44–46 hard
AI Superpowers: China, Silicon Valley, and the New World Order
by Kai-Fu Lee · 14 Sep 2018 · 307pp · 88,180 words
comes to AI. It has fed a belief that we’re on the verge of achieving what some consider the Holy Grail of AI research, artificial general intelligence (AGI)—thinking machines with the ability to perform any intellectual task that a human can—and much more. Some predict that with the dawn of
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, love, empathy, and appreciation for beauty. These are the key hurdles that separate what AI does today—spotting correlations in data and making predictions—and artificial general intelligence. Any one of these new abilities may require multiple huge breakthroughs; AGI implies solving all of them. The mistake of many AGI forecasts is to
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still many decades, if not centuries, away from the real thing. There is also a real possibility that AGI is something humans will never achieve. Artificial general intelligence would be a major turning point in the relationship between humans and machines—what many predict would be the most significant single event in the
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, 18, 25 Chinese government and, 18 data and, 17, 20, 55, 80 deep learning and, 13–14, 143 going light vs. going heavy, 71 AGI (artificial general intelligence), 140–44 AI. See artificial intelligence (AI) AI engineers, 14 Airbnb, 39, 49, 73 AI revolution deep learning and, 5, 25, 92, 94, 143 economic
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Apple, 33, 75, 117, 126, 143, 177, 184 Apple Pay, 75, 76 app-within-an-app model, 59 ARM (British firm), 96 Armstrong, Neil, 3 artificial general intelligence (AGI), 140–44 artificial intelligence (AI) introduction to, ix–xi See also China; deep learning; economy and AI; four waves of AI; global AI story
MegaThreats: Ten Dangerous Trends That Imperil Our Future, and How to Survive Them
by Nouriel Roubini · 17 Oct 2022 · 328pp · 96,678 words
even creative jobs. So for workers, including those in the creative industries, there is nowhere to hide. All this is vaulting us even closer to artificial general intelligence, or AGI, where super intelligent machines leave humans in the dust. Author Ray Kurzweil and other visionaries predict a pivotal moment that will disrupt everything
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