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On Intelligence Paperback – July 14, 2005
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Jeff Hawkins, the high-tech success story behind PalmPilots and the Redwood Neuroscience Institute, does a lot of thinking about thinking. In On Intelligence Hawkins juxtaposes his two loves--computers and brains--to examine the real future of artificial intelligence. In doing so, he unites two fields of study that have been moving uneasily toward one another for at least two decades. Most people think that computers are getting smarter, and that maybe someday, they'll be as smart as we humans are. But Hawkins explains why the way we build computers today won't take us down that path. He shows, using nicely accessible examples, that our brains are memory-driven systems that use our five senses and our perception of time, space, and consciousness in a way that's totally unlike the relatively simple structures of even the most complex computer chip. Readers who gobbled up Ray Kurzweil's (The Age of Spiritual Machines and Steven Johnson's Mind Wide Open will find more intriguing food for thought here. Hawkins does a good job of outlining current brain research for a general audience, and his enthusiasm for brains is surprisingly contagious. --Therese Littleton --This text refers to an out of print or unavailable edition of this title.
From Publishers Weekly
Hawkins designed the technical innovations that make handheld computers like the Palm Pilot ubiquitous. But he also has a lifelong passion for the mysteries of the brain, and he's convinced that artificial intelligence theorists are misguided in focusing on the limits of computational power rather than on the nature of human thought. He "pops the hood" of the neocortex and carefully articulates a theory of consciousness and intelligence that offers radical options for future researchers. "[T]he ability to make predictions about the future... is the crux of intelligence," he argues. The predictions are based on accumulated memories, and Hawkins suggests that humanoid robotics, the attempt to build robots with humanlike bodies, will create machines that are more expensive and impractical than machines reproducing genuinely human-level processes such as complex-pattern analysis, which can be applied to speech recognition, weather analysis and smart cars. Hawkins presents his ideas, with help from New York Times science writer Blakeslee, in chatty, easy-to-grasp language that still respects the brain's technical complexity. He fully anticipates—even welcomes—the controversy he may provoke within the scientific community and admits that he might be wrong, even as he offers a checklist of potential discoveries that could prove him right. His engaging speculations are sure to win fans of authors like Steven Johnson and Daniel Dennett.
Copyright © Reed Business Information, a division of Reed Elsevier Inc. All rights reserved. --This text refers to an out of print or unavailable edition of this title.
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Top Customer Reviews
To his credit, Hawkins does cite Grossberg approvingly at several junctures in his argument, but he fails to take into account several of Grossberg's greatest insights into neocortical processing: his theory of how serial processing can be accomplised in a parallel anatomy and his theory of "rebounds". The latter is especially important since it explains how new memories are prevented from overwriting old memories. For example, when I learn a second language, it doesn't overwrite my first.
These criticisms, however, are in no way meant to detract in the slightest from Hawkins' superb book. It is an eminently readable account of neocortical computing, and correct in all its broad brush strokes. If you are as beguiled by "On Intelligence" as the other reviewers in this thread, my purpose is only to alert you to the even deeper wonders that are to be found in Grossberg's work. As I have said, his work is difficult, but his 1980 and 1982 Psychological Review articles will provide good entry-points. Those of you with an interest in brain and language will find an even better second course in neocortical computing in Loritz' "How the Brain Evolved Language" (Oxford University Press, 1999).
As a testament to it's relevancy today (I'm writing this Sept 2012, seven years after the book was published) he predicts three technological applications that may become available in the short term (5-10 years) due to breakthroughs in the kind of trainable AI this book discusses:
Computer vision and teaching a computer to tell the difference between a cat and a dog (this was successfully demonstrated in a study published in June 2012 - the paper is called "Building High-level Features Using Large Scale Unsupervised Learning" and is available online, or just search for "computer learns to recognize cats" for articles)
PDAs (as they were called back then) will understand naturally spoken instructions like "Move my daughter's basketball game on Sunday to 10 in the morning" (this kind of sentence, copied from the book verbatim, is exactly where Apple's AI application SIRI shines)
Smart/autonomous cars - in Aug 2012, Google announced that their self driving cars have logged 300 K accident free miles in live traffic on public roads, exceeding the average distance a human drives without accident.
The thing to note here is that when he wrote the book these three things had hurdles that we did not know how to solve, and at the time there was no clear linear progression of existing solutions that would guarantee they would be solved. His prediction is that we'll be able to train computers to recognize patterns by themselves which will allow us to eventually solve the problems (and this is exactly how the computer learned to recognize cat faces from youtube videos)
Furthermore, he predicts that AI will become one of the hottest fields within the next 10 years - and with the current explosion of interest in Big Data, Machine Learning, and applications like SIRI it is hard to deny that it lookslike we're right in the midst of seeing just this happen.
The grander implications of the model of this book won't be known for another 10-20 years or more, but 7 years in his general predictions about the field of AI have been very accurate.
Most Recent Customer Reviews
I purchased this book as used but in a very good condition.