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| On Intelligence | 
| Authors: Jeff Hawkins, Sandra Blakeslee
Category: Book
List Price: $25.00
Buy New: $5.00
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Avg. Customer Rating:  (97 reviews)
Sales Rank: 140050
Format: Bargain Price
Media: Hardcover
Number Of Items: 1
Pages: 272
Shipping Weight (lbs): 1
Dimensions (in): 9.2 x 6.1 x 0.6
ASIN: B000GQLCVE
Publication Date: October 3, 2004
Availability: Usually ships in 1-2 business days
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| Customer Reviews:
 Good, Eh, Good December 23, 2007
2 out of 4 found this review helpful
Awesome until the middle chapters give you a very convoluted and spectulaticve take on this theory. Nice Beginning and End chapters though...
 Groundbreaking, fascinating book December 8, 2007
After years of following and being disappointed by AI, Hawkins' book offers a breakthrough approach to understanding the brain upon which future AI research should be based. A fascinating view of ourselves that's also an enjoyable read, On Intelligence is a must-own for anyone with the remotest interest in the brain as well as hard core techies.
Very entertaining and interesting November 23, 2007
I first heard about this book while listening to Steve Gibson's "Security Now!" podcast over at [...]. Very interesting read. Particularly enjoyable was the insight into the process of learning, and how the human brain is basically a pattern-recognition and pattern-prediction machine, and that the whole concept of intelligence itself revolves around this notion of recognizing and predicting patterns. Hawkins' goal is to solve what he calls the "Intelligence Algorithm" which is universal to all intelligent life on Earth, and to ultimately program this same algorithm into computers and machines, igniting an explosion of new research and scientific study at rates we never dreamed possible. Definitely recommend!
Very interesting October 31, 2007
1 out of 1 found this review helpful
I found this book to be very interesting and though-provoking. I decided to read it after listening in on some computer science colleagues who were discussing it. There is still insufficient evidence to back up the theories that this book brings forth, but part of science is proposing hypotheses and seeing if they hold up to the evidence that we collect in the future.
An important book October 18, 2007
1 out of 1 found this review helpful
First, let me comment on the writing. There is an obvious attempt to make things as clear as possible to the layman, with almost too many illustrations of some of the points, and only as much technical language as is necessary. Some of the imagery is great. Never-the-less, getting through the long chapter on "How the Cortex Works" is a chore. At the same time, the Appendix, whose primary purpose is to lay out a research program, is clear, concise, and very informative; in other words, the appendix should have been incorporated into the chapter, and some of the chapter details left for an Appendix. It doesn't help that while hierarchy is emphasized, within the core unit of the cortex, the 6 layered "column", the flow of information is not primarily upward or downward.
A key observation is that tasks which are complex or impossible to solve by computer, such as determining if a cat is pictured in a photograph, can be accomplished by the brain in less than 100 steps (we know this from the time it takes neurons to fire). Another is that inside the brain it is dark and silent: the cortex is always simply processing spatial/temporal patterns of impulses, whether these originated: outside of the cortex, as sounds, images, etc.; feedback from the body's own activity such as moving or lifting an object; thoughts generated within the cortex. All regions of the cortex look much the same, as best we can tell - they do functionally different things, but Hawkins infers they use the same basic algorithm(s) everywhere. Another observation is that information must be stored in invariant form, so that an a face can be recognized despite the lighting, angle, and so on, which all drastically affect the actual "pixels" which are recorded on the retina.
Hawkins sees the cortex as an auto-associative memory, which stores patterns in an invariant, hierarchical form, and can recall a complete pattern from part of the pattern, and even if the inputs are somewhat distorted (which is why we never notice blind spots in the retina). The cortex is constantly using this capability to predict what pattern it will see next, and to compare it to actual patterns: if the prediction is incorrect, then this information is moved up the hierarchy and learning may occur as new and often more general kinds of classifications (invariant representations) are made dynamically.
Patterns can correspond to concepts as well as the output of the physical senses. In fact, my appreciation of Hawkins' book was greatly enhanced by having previously read Jerome Feldman's " From Molecule to Metaphor", which seems to take a very different approach to the brain in explaining how the child masters language (and is very different as to the actual mechanics, suggesting the use of what Hawkins calls backward propagation neural networks rather than auto-associative networks, the latter making more sense to me). What Feldman makes clear is how we bootstrap learning using analogy (comparable to invariant patterns), so that abstract concepts can be seen as originally built from analogy to models of physical movement and grasping and then get increasingly abstract. Interestingly, just as Feldman starts with concepts of motor control as the basis of language, Hawkins points out a predicted pattern can also correspond to a series of instructions for muscular movement. Hawkins defines creativity as "prediction by analogy" (p.183).
One interesting prediction that Hawkins makes is that neurons will be found to be smarter than mere aggregators which fire only if the sum of positive minus negative inputs exceed some threshold; instead, he thinks at least some neurons also have the capability to fire if certain inputs fire together without respect to an aggregate threshold. He also speculates on why sounds seem different than images, acknowledging that this may have to do with the non-cortical areas of the brain, just as these areas are so important to emotions.
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