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On Intelligence Hardcover – 15 Sep 2004


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Product details

  • Hardcover: 272 pages
  • Publisher: Times Books (15 Sep 2004)
  • Language: English
  • ISBN-10: 0805074562
  • ISBN-13: 978-0805074567
  • Product Dimensions: 16.2 x 2.5 x 24.3 cm
  • Average Customer Review: 4.9 out of 5 stars  See all reviews (25 customer reviews)
  • Amazon Bestsellers Rank: 323,571 in Books (See Top 100 in Books)

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Amazon Review

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

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66 of 67 people found the following review helpful By Coert Visser on 10 Dec 2004
Format: Hardcover
We often routinely talk about intelligence and we attempt to measure it for for a variety of purposes. But do we know what it is? Jeff Hawkins is one of the first people to present a specific and comprehesensive theory of intelligence with a leading role for the human neocortex. Hawkins starts by stating that Human intelliigence is fundamentally different from what a computer does.
But isn't artifical intelligence (AI) a good metaphor for human intelligence? No, says Hawkins. In AI a computer is taught to solve problems beloning to a specific domain based on a large set of data and rules. In comparison to human intelligence AI systems are very limited. They are only good for the one thing they were designed for. Teaching an AI based system to perform a task like catching a ball is hard because it would require vast amounts of data and complicated algorithms to capture the complex features of the environment. A human would have little difficulty in solving such everyday problems much easier and quicker.
Ok, but aren't neural networks then a good approximation of human intelligence? Although they are indeed an improvement to AI and have made possible some very practical tools they are still very different to human intelligence. Not only are human brains structurally much more complicated, there are clear functional differences too. For instance, in a neural network information flows only one direction while in the human brain there is a constant flow of information in two directions.
Well, isn't the brain then like a parallel computer in which billions of cells are concurrently computing? Is parallel computing what makes human so fast in solving complex problems like catching a ball? No, says the author.
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11 of 11 people found the following review helpful By Printul Noptilor on 26 Dec 2009
Format: Paperback
This book explores the question "what is intelligence?", introducing rather surprising results of brain research in a way that should be understandable to a person of average intelligence.

Mr. Hawkins explains that intelligence is not what people usually think it is. For most of us (including me prior to reading this book), the word "intelligence" associates with "artificial intelligence" and that associates with computers that beat humans at chess, and begs the question: will computers smarter than us take over the Earth one day?
Of course, I have always noticed, as probably all serious chess players have, that computers play chess in a totally different way. In a nutshell, they tend to excel at short-term tactics while being ridiculously inept at endgame in which one needs a good grasp of long-term strategy. Humans often make the kinds of mistakes chess software would almost never make, and chess software often makes mistakes a human player would hardly ever make. I have, though, never been able to figure out what it is that makes the "artificial intelligence" so different from "human intelligence".
That's where this book steps in. It's not about chess, of course - I just brought that example to help you understand what the problem's all about. This book is about scientific research that convincingly refutes the popular belief that computer CPU's are "electronic brains", or that a human brain is just a very, very compact, very, very efficient computer.

I shall now try to explain briefly how this book describes the essential difference between brains and computers.
In an electronic circuitry, you have a certain module (or a network of modules) that turns a certain kind of input into a certain kind of output.
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9 of 9 people found the following review helpful By Dennis Littrell TOP 1000 REVIEWER on 15 Sep 2009
Format: Paperback
"Prediction is not just one of the things your brain does. It is the primary function of the neocortex, and the foundation of intelligence." (p. 89)

Perhaps the crux of Hawkins's insight into how our brains work and how that is different from how computers work can be gleaned from considering how to catch a ball in flight.

It used to be thought that such tasks were solved by the brain through calculation. The brain would calculate the flight of the ball, adjusting the muscles of the body appropriately so as to arrive at a spot where the ball would be and grab it. Artificial intelligence people working on robots used this method and found out that it was enormously complex, so much so that the robots remained clumsy (and not about to play centerfield for the New York Yankees).

What Hawkins is saying is that the brain does NOT calculate the flight of the ball but instead recalls from memory similar flights of balls while at the same time recalling again from memory the muscular workings of the body as it went after and caught or did not catch similar balls in flight. After a bit of practice (storing memories) a person can get very good at catching balls.

In other words the brain predicts where the ball is going to be not through a laborious and lengthy calculation but through memories of similar events. This is a startling insight. Hawkins shows how everything we do is based on our brain's ability to predict events based on previous experience. Here's how it works:

First there is a "sequence of patterns" of past events stored in the brain.

Second, the brain has an "auto-associative mechanism" that allows it to "recall complete patterns when given only partial or distorted inputs." (p.
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