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On Intelligence, by Jeff Hawkins, Sandra Blakeslee
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From the inventor of the PalmPilot comes a new and compelling theory of intelligence, brain function, and the future of intelligent machines
Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself.
Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines.
The brain is not a computer, but a memory system that stores experiences in a way that reflects the true structure of the world, remembering sequences of events and their nested relationships and making predictions based on those memories. It is this memory-prediction system that forms the basis of intelligence, perception, creativity, and even consciousness.
In an engaging style that will captivate audiences from the merely curious to the professional scientist, Hawkins shows how a clear understanding of how the brain works will make it possible for us to build intelligent machines, in silicon, that will exceed our human ability in surprising ways.
Written with acclaimed science writer Sandra Blakeslee, On Intelligence promises to completely transfigure the possibilities of the technology age. It is a landmark book in its scope and clarity.
- Sales Rank: #49095 in Books
- Brand: Hawkins, Jeff/ Blakeslee, Sandra
- Published on: 2005-08-01
- Released on: 2005-07-14
- Original language: English
- Number of items: 1
- Dimensions: 8.28" h x .77" w x 5.45" l, .54 pounds
- Binding: Paperback
- 272 pages
- Used Book in Good Condition
Amazon.com 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
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.
From Scientific American
"This book and my life are animated by two passions," writes Hawkins in On Intelligence. Those passions are mobile computing and brains. This curious combination becomes less puzzling when one realizes that Hawkins is a founder not only of two leading mobile computing companies—Palm Computing and Handspring—but also of the Redwood Neuroscience Institute in Menlo Park, Calif., which explores memory and cognition. Hawkins contends that the human brain and intelligence have little in common with today’s computing systems. Therefore, he offers his perspective on artificial intelligence, neural networks, cognition, consciousness and creativity, with the goal of explaining the mind. The book is elegantly written with Blakeslee, a veteran science writer for the New York Times. At its core, the book puts forth Hawkins’s "memory-prediction framework of intelligence"—a model of cognition positing that the main function of the human neocortex, and the basis of intelligence, is to make predictions. The brain constantly compares new sensory information with stored memories and experiences and combines the information to anticipate the future. In essence, as we wander around, we build a reserve of information from which we construct an internal model of the world. But we constantly update that model. When we see a friend wearing a new hat, the brain automatically predicts what that person ought to look like and contrasts that prediction with the new sensory rendering, updating its model. Brain prediction "is so pervasive," Hawkins says, "that what we ‘perceive’... does not come solely from our senses." The continuous interplay of sensory input, memory, prediction and feedback—which occurs instantly through parallel processing in the neocortex—ultimately gives rise to consciousness and intelligence. "Correct predictions," Hawkins contends, "result in understanding." Hawkins argues that creativity and imagination emerge from prediction as well. Imagination utilizes a neural mechanism to transform predictions into a form of sensory input—which is why our fantasies have such a strong "feel." Moving on, Hawkins says that true machine intelligence will arise only if it is rooted in the same principles as brain-based intelligence. By the book’s end, Hawkins proffers a "comprehensive theory of how the brain works," of "what intelligence is," and of "how your brain creates it." He acknowledges that many aspects of his theory have been developed by other scientists and that his role is to weave a comprehensive explanation. As such, this book provides some provocative thoughts on how the brain and the mind may actually function.
Richard Lipkin
Most helpful customer reviews
87 of 94 people found the following review helpful.
A Great Intro to Even Greater Insights
By Jane E. Carroll
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).
194 of 218 people found the following review helpful.
Simply Indispensable
By Bruce Gregory
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.
56 of 61 people found the following review helpful.
Central Dogma for the Brain
By Donald B. Siano
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. recognizing that a picture of a cat shows a cat) are carried out in less than 100 ticks. From the time that light enters the eye, to the time it takes to signify recognition takes less than a second. A computer would take billions of instruction steps, and even the fastest parallel computer available would not do it in less than millions of steps. So the brain doesn't really "compute" the answer, it retrieves it from memory, which requires far fewer steps than the computation. Sounds good to me.
His explication of the memory-prediction framework is clear and accessible even to the uninitiated like me, though I found some of it in the middle pretty heavy going. But this is something like reading Watson and Crick's paper on the structure of DNA. The part about turning the diffraction diagram and other insights into a workable model was a little above my head, but I could still see the importance of the answer, and how it addressed the problem of replication and how it gave clues as to how to "read the genes." I can only grasp part of what Hawkins has done, and I can see that there is still a long way to go. But I can still jump up and down about it!
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