Creating Brain Like Intelligence

TheInternationalSymposiumCreatingBrain-LikeIntelligencewasheldinFeb- ary 2007 in Germany. The symposium brought together notable scientists from di?erent backgrounds and with di?erent expertise related to the emerging ?eld of brain-like intelligence. Our understanding of the principles behind brain-like intelligence is still limited. After all, we have had to acknowledge that after tremendous advances in areas like neural networks, computational and arti?cial intelligence (a ?eld that had just celebrated its 50 year anniversary) and fuzzy systems, we are still not able to mimic even the lower-level sensory capabilities of humans or animals. We asked what the biggest obstacles are and how we could gain ground toward a scienti?c understanding of the autonomy, ?exibility, and robustness of intelligent biological systems as they strive to survive. New principles are usually found at the interfaces between existing disciplines, and traditional boundaries between disciplines have to be broken down to see how complex systems become simple and how the puzzle can be assembled. During the symposium we could identify some recurring themes that p- vaded many of the talks and discussions. The triad of structure, dynamics and environment,theroleoftheenvironmentasanactivepartnerinshapingsystems, adaptivity on all scales (learning, development, evolution) and the amalga- tion of an internal and external world in brain-like intelligence rate high among them. Each of us is rooted in a certain community which we have to serve with the results of our research. Looking beyond our ?elds and working at the interfaces between established areas of research requires e?ort and an active process.

Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

A bestselling author, neuroscientist, and computer engineer unveils a theory of intelligence that will revolutionize our understanding of the brain and the future of AI. For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses maplike structures to build a model of the world—not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought. A Thousand Brains heralds a revolution in the understanding of intelligence. It is a big-think book, in every sense of the word. One of the Financial Times' Best Books of 2021 One of Bill Gates' Five Favorite Books of 2021

TheInternationalSymposiumCreatingBrain-LikeIntelligencewasheldinFeb- ary 2007 in Germany. The symposium brought together notable scientists from di?erent backgrounds and with di?erent expertise related to the emerging ?eld of brain-like intelligence. Our understanding of the principles behind brain-like intelligence is still limited. After all, we have had to acknowledge that after tremendous advances in areas like neural networks, computational and arti?cial intelligence (a ?eld that had just celebrated its 50 year anniversary) and fuzzy systems, we are still not able to mimic even the lower-level sensory capabilities of humans or animals. We asked what the biggest obstacles are and how we could gain ground toward a scienti?c understanding of the autonomy, ?exibility, and robustness of intelligent biological systems as they strive to survive. New principles are usually found at the interfaces between existing disciplines, and traditional boundaries between disciplines have to be broken down to see how complex systems become simple and how the puzzle can be assembled. During the symposium we could identify some recurring themes that p- vaded many of the talks and discussions. The triad of structure, dynamics and environment,theroleoftheenvironmentasanactivepartnerinshapingsystems, adaptivity on all scales (learning, development, evolution) and the amalga- tion of an internal and external world in brain-like intelligence rate high among them. Each of us is rooted in a certain community which we have to serve with the results of our research. Looking beyond our ?elds and working at the interfaces between established areas of research requires e?ort and an active process.

A fascinating tour behind the scenes at laboratories around the world as top researchers race to create revolutionary "thinking machines" that may one day lead to a new form of intelligence. Join David Freedman as he takes you on a fascinating tour behind the scenes at laboratories around the world as top researchers race to create revolutionary "thinking machines" that may one day lead to a new form of intelligence. The subject of fantasy and skepticism for centuries—from William James's mechanical bride to 2001's Hal to Star Wars' R2D2—artificial intelligence has been limited to number-crunching computers that are "smart" only in highly specific domains like chess—until now. Brainmakers is an eye-opening, mind-expanding, and mind-blowing journey through laboratories engaged in cutting-edge research into neuroscience and robotics. Inside, you'll discover: MIT's Attila, a 3.6-pound, six-legged robot that learns as it interacts with its surroundings. Japan's efforts to grow brain cells on chips and construct a "wiring diagram" of the human brain. UCLA's "robot farm," where robots will be "bred" for intelligence. In exciting yet accessible detail, Freedman shows how this research has moved into a new realm that transcends computer science, combining neuroscience, microbiology, evolutionary biology, and zoology. Modeled after natural rather than artificial intelligence, thinking machines may soon develop powers that rival—or exceed—those of the human brain.

Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks

From the inventor of the PalmPilot comes a new and compelling theory of intelligence, brain function, and the future of intelligent machines Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself. Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines. The brain is not a computer, but a memory system that stores experiences in a way that reflects the true structure of the world, remembering sequences of events and their nested relationships and making predictions based on those memories. It is this memory-prediction system that forms the basis of intelligence, perception, creativity, and even consciousness. In an engaging style that will captivate audiences from the merely curious to the professional scientist, Hawkins shows how a clear understanding of how the brain works will make it possible for us to build intelligent machines, in silicon, that will exceed our human ability in surprising ways. Written with acclaimed science writer Sandra Blakeslee, On Intelligence promises to completely transfigure the possibilities of the technology age. It is a landmark book in its scope and clarity.

This book describes historical and current research into artificial intelligence. It focuses on the limitations imposed by hardware and software, and approaches inspired by the nature of human brains.