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How to Create a Mind: The Secret of Human Thought Revealed, by Ray Kurzweil
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Pressestimmen
“Kurzweil's vision of our super-enhanced future is completely sane and calmly reasoned, and his book should nicely smooth the path for the earth's robot overlords, who, it turns out, will be us.”—The New York Times “Kurzweil writes boldly and with a showman’s flair, expertly guiding the lay reader into deep thickets of neuroscience.”—Kate Tuttle, Boston Globe “This book is a breath of fresh air . . . . Kurzweil makes an argument for optimism.”—Laura Spinney, New Scientist “A fascinating exercise in futurology.”—Kirkus Reviews “It is rare to find a book that offers unique and inspiring content on every page. How to Create a Mind achieves that and more. Ray has a way of tackling seemingly overwhelming challenges with an army of reason, in the end convincing the reader that it is within our reach to create nonbiological intelligence that will soar past our own. This is a visionary work that is also accessible and entertaining.”—Rafael Reif, president, MIT “Kurzweil’s new book on the mind is magnificent, timely, and solidly argued! His best so far!”—Marvin Minsky, MIT Toshiba Professor of Media Arts and Sciences; cofounder of the MIT Artificial Intelligence Lab; widely regarded as “the father of artificial intelligence” “If you ever wondered about how your mind works, read this book. Kurzweil’s insights reveal key secrets underlying human thought and our ability to recreate it. This is an eloquent and thought-provoking work.”—Dean Kamen, physicist; inventor of the first wearable insulin pump, the HomeChoice dialysis machine, and the IBOT mobility system; founder of FIRST; recipient of the National Medal of Technology “One of the eminent AI pioneers, Ray Kurzweil, has created a new book to explain the true nature of intelligence, both biological and nonbiological. The book describes the human brain as a machine that can understand hierarchical concepts ranging from the form of a chair to the nature of humor. His important insights emphasize the key role of learning both in the brain and in AI. He provides a credible road map for achieving the goal of super-human intelligence, which will be necessary to solve the grand challenges of humanity.”—Raj Reddy, founding director, Robotics Institute, Carnegie Mellon University; recipient of the Turing Award from the Association for Computing Machinery “Ray Kurzweil pioneered artificial intelligence systems that could read print in any type style, synthesize speech and music, and understand speech. These were the forerunners of the present revolution in machine learning that is creating intelligent computers that can beat humans in chess, win on Jeopardy!, and drive cars. His new book is a clear and compelling overview of the progress, especially in learning, that is enabling this revolution in the technologies of intelligence. It also offers important insights into a future in which we will begin solving what I believe is the greatest problem in science and technology today: the problem of how the brain works and of how it generates intelligence.”—Tomaso Poggio, Eugene McDermott Professor, MIT Department of Brain and Cognitive Sciences; director, MIT Center for Biological and Computational Learning; former chair, MIT McGovern Institute for Brain Research; one of the most cited neuroscientists in the world “This book is a Rosetta stone for the mystery of human thought. Even more remarkably, it is a blueprint for creating artificial consciousness that is as persuasive and emotional as our own. Kurzweil deals with the subject of consciousness better than anyone from Blackmore to Dennett. His persuasive thought experiment is of Einstein quality: It forces recognition of the truth.”—Martine Rothblatt, chairman and CEO, United Therapeutics; creator of Sirius XM Satellite Radio “Kurzweil’s book is a shining example of his prodigious ability to synthesize ideas from disparate domains and explain them to readers in simple, elegant language. Just as Chanute’s Progress in Flying Machines ushered in the era of aviation over a century ago, this book is the harbinger of the coming revolution in artificial intelligence that will fulfill Kurzweil's own prophecies about it.”—Dileep George, AI scientist; pioneer of hierarchical models of the neocortex; cofounder of Numenta and Vicarious Systems “Ray Kurzweil’s understanding of the brain and artificial intelligence will dramatically impact every aspect of our lives, every industry on Earth, and how we think about our future. If you care about any of these, read this book!”—Peter H. Diamandis, chairman and CEO, X PRIZE; executive chairman, Singularity University; author of the New York Times bestseller Abundance: The Future Is Better Than You ThinkFrom the Hardcover edition.
Über den Autor und weitere Mitwirkende
Ray Kurzweil is the author of The New York Times bestseller The Singularity Is Near and the national bestseller The Age of Spiritual Machines, among others. One of the leading inventors of our time, he was inducted into the National Inventors Hall of Fame in 2002. He is the recipient of many honors, including the National Medal of Technology, the nation’s highest honor in technology. He lives in Boston.From the Hardcover edition.
Produktinformation
Taschenbuch: 352 Seiten
Verlag: Penguin Books (27. August 2013)
Sprache: Englisch
ISBN-10: 9780143124047
ISBN-13: 978-0143124047
ASIN: 0143124048
Größe und/oder Gewicht:
2,3 x 13,7 x 21,3 cm
Durchschnittliche Kundenbewertung:
4.7 von 5 Sternen
13 Kundenrezensionen
Amazon Bestseller-Rang:
Nr. 22.781 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
Ray Kurzweil shows the human brain in a completely new way. From a complicated, ununderstandable mass of neurons, he reveals its simple structure and explains how we could replicate it in a memory of a computer. But doesn't stay only at the technical part. The book also takes its time to discuss various philosophical problems, connected with intelligence and consciousness.It was probably the best popular science book I have read.
Wow. Just wow. Ray Kurzweil explains how we actually think; that is, what he believes neocortex's algortim is told in a very nice way. I especially recommend this book to my colleagues from IT field. You'll find a lot of parallels between neocortex and the deep neural networks we have been coding.
Excellent reading especially once I got through the very technical introduction and into the detailed but easy to follow explanations.
Easy to read for such a seemingly complicated topic. Even so, for my linear brain, hard to follow. Opens up new visions. Most convincing is that his principle of hidden Markov chains in neuronal networks has proven its power in already existing solutions as speech recognition and Watson's winning at jeopardy
Kurzweil takes the reader through a tour of selected neuroscience research and concepts of reverse-engineering the brain with a focus on neocortex neural architecture for pattern recognition. As always, Kurzweil is very enthusiastic about artificial intelligence and the pace of technological progress, illustrated in his belief in the law of accelerating returns in the field of information- processing. It is very tempting to share in this enthusiasm, but key aspects of the workings of the human mind are unfortunately not addressed in the book. It might be true that information processing will advance in leaps and bounds, so that cars will find their way from A to B better and more efficiently than human drivers, that computers will be able to answer any knowledge question in the blink of an eye etc. They might even do this by using techniques derived from architectural features of the human brain. But this intelligence, that can solve these kinds of problems will always represent a fundamentally different kind of intelligence than the one our brain creates. This can be illustrated by the nature of machine speech recognition, of which Kurzweil is an expert and which also features prominently in the book. I have been using this technology for more than 10 years and I must say that the progress has peaked about seven years ago. It might be true that recognition rates are somewhere around 90% + for continuous speech recognition since that time. This is very impressive, and being handicapped I much appreciate this technology. But it is the nature of the mistakes made that has not changed and is not likely to change only by improving processing power or adding new layers of pattern recognition. Every child will aptly label the mistakes made by machine speech recognition as stupid, because they make for nonsensical sentences. Speech recognition among humans is always a process of dialogue, a search for meaning, a search for expression. The human speaker and the human listener will work along the lines of their personal agendas. Ideally (but far from necessarily), they will try to match these agendas while communicating. This is something fundamentally different from bottom-up pattern recognition. Everybody can try this out for themselves: first dictate some thoughts to your computer, then ask a friend to write the same dictation down for you. The human friend will not just write down whatever he thinks she heard, but will try to get into your head, to anticipate your meaning and match this meaning to what she hears acoustically. Also, there is no need to dictate punctuation marks, for it will be as if your friend is writing down his own thoughts. If lost, or unsure of your meaning, she will pause and ask for clarification ("I am not familiar with this Hungarian name [sic!], can you spell that?"). Your human scribe will certainly not reach 100% accuracy, just as his machine counterpart, but his sentences will never turn out to be nonsensical. Also, you will not have to go through the tedious process of selecting and correcting the mistakes one by one, and correcting the mistakes made during correction etc. The corrections will be a fluent part of your conversation/dictation.This of course addresses the field of top-down processing, which is briefly mentioned by Kurzweil as "a very important point" in the beginning of the book, but sadly nowhere further elaborated. "We are continually making predictions", says Kurzweil, but so far no machine does this at the level of complexity or intrinsic motivation seen in human minds. Certainly my speech recognition software is not making any predictions as to what I'm going to say next in terms of meaning. Again, this is different than using texts I have written before as templates for pattern recognition (it is even counter-productive to use letters to my daughter or to my insurance company to help in understanding my comments on a book on neuroscience). What is asked for is to share in my thoughts and purposes and making predictions based on this attempt. Kurzweil writes that the Siri-speechrecognition for example "works impressively for a first-generation product, and it is clear that this category of product is only going to get better." This does not seem to be so clear for me, as long as we do not address the problem of top-down processing. I am not saying that this is an unsolvable problem, not even a problem of unreachable processing power or forever mysterious processing architecture. It is a question of what drives the processing in the first place, of the mind or the machine actively searching for a definition of the problem to be solved. The selfdriving car might be much better than us at getting from A to B, but if we don't tell it to, it will not move. Just as the horse or oxen that we used to use for these purposes in the olden days. And they were also kind of smart. All these intelligences, biological or artificial are so far only extensions of our own selfishly motivated intelligence. We humans are thrown into a vastly complex and dangerous world and we are constantly driven to make sense of it, to find or create tools, to gain companions in our quests that extend far beyond mere survival. Our brains are vastly complex meaning-creating biological machines, they are not only problem-solving but problem-creating machines, constantly inventing new tasks and fields for learning. Everyone of us is uniquely driven by constantly evolving multilayered and conflicting needs that we project onto our surroundings. The fallen branch becomes a stick to reach an apple or a weapon to destroy an opponent, because our needs coupled with our processing power make it so. The information processing of the human mind is always also affective information processing (and the nascent field of affective neuroscience is still groping about very much in the dark). Unless we put this kind of need into a machine, we will not create true artificial intelligence, we will not create a mind, but just more and more "clever" tools. If Kurzweil knows how to create this kind of individualistic and unpredictable, self-evolving need-machine, he does not tell us in his book. But then again, do we really want to create such a mind artificially? Together with his needs we would also create his frustrations (an intrinsic part of the need-driven problem-solving process) and ultimately a rich bouquet of suffering. And we certainly wouldn't want it to become conscious (this still mysterious "emergent property") of its suffering and our part in it. We humans know all about suffering, and how it can only be made bearable by a passion for life's adventures - or by changing the very architecture of our brain through year-long meditation techniques. Do we really want to artificially create a passionate mind? The reverse-engineering of a Buddhist monks mind wouldn't solve any problems. Because it knows no more problems. It would just smile at us and pat us on our shoulder.
Ray is not afraid, to point out every detail about why it is gonna be us, to be The next step in evolution. Technology is not taking over, we will just embrace it more, when it comes to meet us in smarter ways.Highly recommended read!Ps: did you know, Ray is now hired by google, as head of their AI lab...
Ray Kurzweil one moré time shining with his thought provoking reflections. A must read for all of those interested in AI vs human evolution
Ray Kurzweil fasst hier aktuelle Erkenntnisse der Neurologie und Computerwissenschaffen mit seinen Erfahrungen und Selbstbeobachtungen so zusammen, dass auch interessierte Laien einen guten Einblick darüber er gewinnen können wie unser Neocortex funktioniert und wie der Weg für maschinelles Lernen und Denken sich weiter entwickeln kann. Ein faszinierendes Buch und fast so etwas wie ein Vermäcbtnis eines der großen Denker und Genies unserer Zeit.
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