Brains, Machines, and Mathematics
Author: Michael A. Arbib
Publisher: New York : McGraw-Hill
Published: 1964
Total Pages: 172
ISBN-13:
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Brains, Machines, and Mathematics
Author: Michael A. Arbib
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 215
ISBN-13: 1461247829
DOWNLOAD EBOOKThis is a book whose time has come-again. The first edition (published by McGraw-Hill in 1964) was written in 1962, and it celebrated a number of approaches to developing an automata theory that could provide insights into the processing of information in brainlike machines, making it accessible to readers with no more than a college freshman's knowledge of mathematics. The book introduced many readers to aspects of cybernetics-the study of computation and control in animal and machine. But by the mid-1960s, many workers abandoned the integrated study of brains and machines to pursue artificial intelligence (AI) as an end in itself-the programming of computers to exhibit some aspects of human intelligence, but with the emphasis on achieving some benchmark of performance rather than on capturing the mechanisms by which humans were themselves intelligent. Some workers tried to use concepts from AI to model human cognition using computer programs, but were so dominated by the metaphor "the mind is a computer" that many argued that the mind must share with the computers of the 1960s the property of being serial, of executing a series of operations one at a time. As the 1960s became the 1970s, this trend continued. Meanwhile, experi mental neuroscience saw an exploration of new data on the anatomy and physiology of neural circuitry, but little of this research placed these circuits in the context of overall behavior, and little was informed by theoretical con cepts beyond feedback mechanisms and feature detectors.
Mathematics for Machine Learning
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
Published: 2020-04-23
Total Pages: 392
ISBN-13: 1108569323
DOWNLOAD EBOOKThe fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
The Emperor's New Mind
Author: Roger Penrose
Publisher: Oxford Paperbacks
Published: 1999-03-04
Total Pages: 634
ISBN-13: 0192861980
DOWNLOAD EBOOKWinner of the Wolf Prize for his contribution to our understanding of the universe, Penrose takes on the question of whether artificial intelligence will ever approach the intricacy of the human mind. 144 illustrations.
The Handbook of Brain Theory and Neural Networks
Author: Michael A. Arbib
Publisher: MIT Press
Published: 2003
Total Pages: 1328
ISBN-13: 0262011972
DOWNLOAD EBOOKThis second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).
How We Learn
Author: Stanislas Dehaene
Publisher: Penguin
Published: 2021-02-02
Total Pages: 369
ISBN-13: 0525559906
DOWNLOAD EBOOK“There are words that are so familiar they obscure rather than illuminate the thing they mean, and ‘learning’ is such a word. It seems so ordinary, everyone does it. Actually it’s more of a black box, which Dehaene cracks open to reveal the awesome secrets within.”--The New York Times Book Review An illuminating dive into the latest science on our brain's remarkable learning abilities and the potential of the machines we program to imitate them The human brain is an extraordinary learning machine. Its ability to reprogram itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. But how do we learn? What innate biological foundations underlie our ability to acquire new information, and what principles modulate their efficiency? In How We Learn, Stanislas Dehaene finds the boundary of computer science, neurobiology, and cognitive psychology to explain how learning really works and how to make the best use of the brain’s learning algorithms in our schools and universities, as well as in everyday life and at any age.
Brains, Machines and Mathematics
Author: Michael Anthony Arbib
Publisher:
Published: 1963
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKThe Computer and the Brain
Author: John Von Neumann
Publisher: Yale University Press
Published: 2000-01-01
Total Pages: 116
ISBN-13: 9780300084733
DOWNLOAD EBOOKThis book represents the views of one of the greatest mathematicians of the twentieth century on the analogies between computing machines and the living human brain. John von Neumann concludes that the brain operates in part digitally, in part analogically, but uses a peculiar statistical language unlike that employed in the operation of man-made computers. This edition includes a new foreword by two eminent figures in the fields of philosophy, neuroscience, and consciousness.
The Digital Mind
Author: Arlindo Oliveira
Publisher: MIT Press
Published: 2018-03-09
Total Pages: 341
ISBN-13: 0262535238
DOWNLOAD EBOOKHow developments in science and technology may enable the emergence of purely digital minds—intelligent machines equal to or greater in power than the human brain. What do computers, cells, and brains have in common? Computers are electronic devices designed by humans; cells are biological entities crafted by evolution; brains are the containers and creators of our minds. But all are, in one way or another, information-processing devices. The power of the human brain is, so far, unequaled by any existing machine or known living being. Over eons of evolution, the brain has enabled us to develop tools and technology to make our lives easier. Our brains have even allowed us to develop computers that are almost as powerful as the human brain itself. In this book, Arlindo Oliveira describes how advances in science and technology could enable us to create digital minds. Exponential growth is a pattern built deep into the scheme of life, but technological change now promises to outstrip even evolutionary change. Oliveira describes technological and scientific advances that range from the discovery of laws that control the behavior of the electromagnetic fields to the development of computers. He calls natural selection the ultimate algorithm, discusses genetics and the evolution of the central nervous system, and describes the role that computer imaging has played in understanding and modeling the brain. Having considered the behavior of the unique system that creates a mind, he turns to an unavoidable question: Is the human brain the only system that can host a mind? If digital minds come into existence—and, Oliveira says, it is difficult to argue that they will not—what are the social, legal, and ethical implications? Will digital minds be our partners, or our rivals?
Beyond Zero and One
Author: Andrew Smart
Publisher: OR Books
Published: 2015-12-03
Total Pages: 270
ISBN-13: 1682190072
DOWNLOAD EBOOK“Andrew Smart deftly shows why it’s time for us to think deeply about thinking machines before they begin thinking deeply about us.” —Douglas Rushkoff, author, Escaping the Growth Trap,Present Shock, and Program or Be Programmed “Provocative and cool.” —Cory Doctorow “Forget the Turing test—will the supersmart AIs that we hear so much about these days pass the acid test? In this playful, informative, and prescient book, Andrew Smart brings psychedelics into dialogue with neuroscience in order to challenge the whiz-bang computational views of human and machine sentience that dominate the headlines. Giving robots LSD sounds like a joke, but Smart is dead serious in his critique of the hidden and sometimes dangerous biases that underlie both popular and scientific fantasies of digital minds.” —Erik Davis, host of “Expanding Mind” and author, Techgnosis: Myth, Magic, and Mysticism in the Age of Information “Philosophy, psychedelics, robots, and the future; consciousness and intelligence, what else do you desire? Here you will see why those machines that reach singularity will be smarter than us and take over the world—and shall need to be conscious…and maybe they can only be conscious if they are human enough. The thesis of the book, and the path shown us by Smart, leads to a great trip, of imagination and philosophy, of maths and neuroscience.” —Dr. Tristan Bekinschtein, Lecturer, Department of Psychology, University of Cambridge Can we build a robot that trips on acid? This is not a frivolous question, according to neuroscientist Andrew Smart. If we can’t, he argues, we haven’t really created artificial intelligence. In an exposition reminiscent of crossover works such as Gödel, Escher, Bach and Fermat’s Last Theorem, Andrew Smart weaves together Mangarevan binary numbers, the discovery of LSD, Leibniz, computer programming, and much more to connect the vast but largely forgotten world of psychedelic research with the resurgent field of AI and the attempt to build conscious robots. A book that draws on the history of mathematics, philosophy, and digital technology, Beyond Zero and One challenges fundamental assumptions underlying artificial intelligence. Is the human brain based on computation? Can information alone explain human consciousness and intelligence? Smart convincingly makes the case that true intelligence, and artificial intelligence, requires an appreciation of what is beyond the computational.
