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On Intelligence Audible – Unabridged

4.4 out of 5 stars 234 customer reviews

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Format: Hardcover
The accolades previous reviewers have lavished upon this book are all fully deserved. It is not, however, "the first time all these bits and pieces have been put into a coherent framework". The work of Stephen Grossberg explored all of these themes in the 1970s. Unfortunately Grossberg expressed his key insights in systems of differential difference equations that few could understand and fewer still could build upon or contribute to.

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).
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Format: Hardcover Verified Purchase
It is not very often that you encounter a book that alters, not simply what you think, but how you look at the world. On Intelligence is such a book. Jeff Hawkins develops a perspective on intelligence that makes sense of much of what I have discovered about learning over the past twenty years. His focus is on a unified model of how the cortex works, but in truth you do not need to have deep interest in neurobiology to see the power of the model. The book is very clear and readable, something I have learned to associate with Sandra Blakeslee's deft touch (see, for example, Phantoms In the Brain, by Ramachandran and Blakeslee). The heavy lifting occurs in the lengthy sixth chapter, "How the Cortex Works." You might want to skim this chapter or even omit it entirely on your first reading. It is well written, but requires a very thoughtful reading. The model Hawkins develops in this chapter underpins his view of intelligence, but it is not necessary to grasp the details to appreciate the power of the vision. If you have the slightest interest in the role of the brain in making us who we are, you owe it to yourself to read this book. I couldn't recommend it more highly.
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Format: Hardcover
Jeff Hawkins is the man who was the architect of the PalmPilot, the Treo, and invented Graffiti, an alphabet for inputing data to a computer with a stylus. But this book is about his other love, the deciphering of the code that makes the human brain work. There is nothing like a big, important puzzle to get the blood working, and mine was powerfully pulled along . With the human genome project's sequencing of human DNA nearly completed, understanding the brain has got to be the most important scientific undertaking one can think of. Hawkins easily persuades us that there is a burning need for a "top down" model for the brain that can play a role something analogous to the Central Dogma of molecular biology, which guides and organizes research, prioritizing the myriad of possible tasks into something like that required for the logistics of a conquering army's march through an alien land.

He also persuaded me that he has some important insights of that model that I found tantalizing, new and exciting. His central model concerns the role of the cortex in producing intelligence. He makes the case for a central dogma he calls "the memory-prediction framework." This idea says that the cortex is a machine for making predictions for temporal sensory patterns based on memories of past patterns. The prediction algorithm carried out in the cortex is the same for all of the senses of vision, touch, hearing, etc., which accounts for, among other things, the basic physiological uniformity of the cortex, and the plasticity of the brain in adapting to such problems as blindness or deafness.

He argues that since the "clock" of the brain operates at a tick-rate on the order of 5 milli-seconds, and most of the functions of the brain (e. g.
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Format: Hardcover
The early parts of the book (up to around p 60) were a great read and convinced me to buy the book. But when Hawkins finally laid out his "big ideas", I was deeply disappointed. Hawkins spends considerable space claiming that AI researchers hack up algorithms based on the "how do I do it" approach. He suggests that "real" intelligence requires memory-based hierarchical models.

What is especially frustrating to this AI (specifically vision) researcher, is that Hawkins does not seem to be aware of any AI research that has been going on in the last 15 years, during which data-driven learning approaches have become standard. I was merely suspicious of his ignorance until I checked his bibliography, in which the most recent technical AI citation was from before 1990.

Furthermore, Hawkin's theories on the brain are largely unsubstantiated. He states that his ideas were largely sparked by one dated paper that other researchers have largely ignored - probably for good reason. For instance, he claims that, since different parts of the brain have a similar physical structure, they must function similarly. This is very oversimplistic.

Nevertheless, I did find parts of the book to be entertaining and appreciated his view on the brain's role as a predictor. Although I do not think that I completely wasted my time in reading this book, my time could have been better spent reading something else. Therefore, I recommend this book to non-scientists who want to read about the brain but aren't particularly concerned about the accuracy/usefulness of what they read. Just be a very critical reader and be careful not to be smacked in the course of all the hand-waving!
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