After a solid intro from Hawkins, Stefan Rudnicki takes over the narrating reins. The effect is an audio program with a compelling ability to anticipate the question taking form in your own brain as you listen, then answer it with clarity and sincerity. That's a feat worthy of admiration.
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.
©2004 Jeff Hawkins and Sandra Blakeslee; (P)2005 Audible, Inc.
"[Hawkins's] argument is complex but comprehensible, and his curiosity will intrigue anyone interested in the lessons neurobiology may hold for AI." (Booklist)
"[Hawkins] 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." (Publishers Weekly)
1. A sudden manifestation of the essence or meaning of something.
2. A comprehension or perception of reality by means of a sudden intuitive realization: ?I experienced an epiphany, a spiritual flash that would change the way I viewed myself? (Frank Maier).
Jeff Hawkins proposes a theory for how the mind works that rings true. I found this book to be a profound mind-expanding experience, allowing my mind to finally understand how my mind works. I am a 45-year old Software Engineer strongly tempted to take up Hawkin's call to young scientists to join the new revolution that will take place as we learn how to apply this model of mind to computers.
This book will probably be of most interest to people who are interested in both computers and psychology, but I think many people who are not interested in computers will still find this book fascinating. Anyone who is interested in the miracle of consciousness and sentience should read this book.
Another reviewer complained that the "ghost narrator" is a poor reader. This narrator is Stephan Rudnicki, a professional voice actor with a deep, resonant voice. He is one of the reader's on the Ender's Game series. There is something about his voice that is a bit unsettling, but I would never call it simpering. Overall, I think he was an excellent choice for narrator for this book.
Note: there are some figures/diagrams in the printed book that can be downloaded from audible.com. The link is on the main page for this book.
This is, all and all, a pretty solid book, particularly if you already have some interest in the field. It explains both current state of modern neuroscience as well as the author's theory of the basis for intelligence. If you are interested in this topic it's probably worth the download. You will have to put up with a few minor irritations, such as (1) the author's ego occasionally bleeds through with little snotty asides. He's fairly arrogant and quickly dismissive of alternative views, (2) his theory seems internally consistent but is ultimately a little reductionist. The brain almost certainly does work, at some level, just as he describes it. But when he pushes the model into describing the creative process, the basis of consciousness and some other areas, it feels a little thin. It's an engineer's view of the essence of these aspects of human behavior, overly wedded to a simplistic structure, ignoring nuances which are clearly important. (3) There is one chapter in the book which doesn't translate into a book tape very well, because it's fairly technical and relies on diagrams. But even if you don't entirely drink his Kool-Aid, this is still an interesting, thought-provoking way to spend a few hours.
I focus on fiction, sci-fi, fantasy, science, history, politics and read a lot. I try to review everything I read.
An excellent book well worth the listen. Not very technical, and a lot is left out. The most frustrating is the almost total lack of discussion of feedback, neuron death, and connectivity changes. I never found this tedious, indeed I would love two more volumes. Even if the authors theories are utterly wrong, anyone interested in intelligence or AI would benefit from reading this book. The author is a bit of a salesperson, a bit conceited, but may very well be correct, and is, in any case, quite interesting.
My husband and I have altered our language. "That didn't make it to the fourth level," we say to each other when there's an automatic reaction to an event. Or "Maybe you need to engage the sixth level..." when facing a problem. And: "Intelligence is the ability to predict..." when my husband's keys are still in his pocket as he approaches the door of the car...
This book was sometimes redundant-- but repetition leads to retention and I needed it sometimes.
I have a Ph.D. in applied behavior analysis because learning theory has always intrigued me. This was the closest I've ever come to feeling like someone has united the nature-nurture issue. I often think of the question he asks: What would a brain do with an eternity of learning?
What would happen if each generation did not have to re-learn the same things?
There were some areas I felt were incompletely developed. I want to know how emotions interact with the learning process. I want to know to enhance the generalizations which lead to creative thinking. How do we Brain Train in a general fashion?? And how do we untrain the brain?
A book that leaves me with the desire to know more is definitely a book I'd recommend to friends.
I don't normally talk to friends about what I'm reading. But for the past two weeks I've been obsessively telling friends - even my 78-year-old mother - about this book. Maybe it's just me, but I find hearing On Intelligence has changed the way I think about computing and human intelligence. I suddenly feel I understand a range of phenomena which have intrigued or baffled me for years.
I can't do justice to Hawkins's thesis, but I'll take a stab. He claims to have figured out how the cortex - the part of the brain that was "new" to mammals, and whose size seems to be the greatest difference between humans and other primates - works. In other words, he asserts a general theory of what makes humans intelligent, and more generally, of what we're doing when we think.
Based on several lines of evidence, he rejects the idea that the cortex is primarily sifting through input data, looking for general patterns, with each stage summarizing and passing information up to more abstract levels. Instead, Hawkins asserts that the cortex is mainly MODELING the world we sense, and spends the great bulk of its effort actually passing predictive data DOWN to lower levels, including sensory areas.
These predictions are broken into an unbeliveably detailed representation of the world, modeling at the level of individual sensory neuron, what we will see, hear, touch, in the next second or two. Wherever this prediction is more-or-less right, it is treated as "confirmed" and the world we experience is mainly THAT PREDICTION, not a summation of this instant's actual nerve receptors' sensations. Where the prediction is NOT confirmed, an "exception" is generated, which either causes minor adjustments in the predicted scenario, or draws our conscious attention to the unexpected event.
If that doesn't make sense, listen to the book. There's a lot more to it.
This book has changed the way I see the world. I think it's a really big deal.
This is one of the worst books I have heard.
Yes, there were some interesting ideas.
But there were so many errors and faulty assumptions, that it made it hard to accept even his simplistic and obvious claims (and he made many of these).
I resented his assertions that everyone but him, all scientists and AI (Artificial Intelligence) researchers in particular, just don't get it. I assume that some of this attitude comes from the fact that MIT rejected him. But many of his claims regarding what certain fields think about the brain are just wrong.
For example, he mentions several times that AI researchers believe that a computer is just like the human brain. While some may talk metaphoricaly of the mind as computer, I have never heard the claim that the human brain works just like the hardware of a computer.
(disclosure: My PhD is in AI)
Old & fat, but strong; American, Chinese, & Indian (sort of); Ph.D. in C.S.; strategy, economics & stability theory; trees & machining.
I'm not qualified to judge how well this book stands up to peer-review within the biological sciences. I'd guess that it not fully accepted by high-end biological researchers, but I'd also guess that this has more to do with the interdisciplinary nature of the work than with any fundamental disagreement about the big concepts. However, I am qualified to say that as a continuation of the cognitive science tradition within computer science this book is simply masterful.
The overall thesis of the book is that the human brain is architecturally not a computer, but rather a smart memory. Of course, this is an architectural distinction rather than a functional distinction. But the distinction yields important clues about how to build smart machines.
The book goes on to propose that memories are recalled using a mixture of forward error correction and search that is biased on invariants. The algorithmic details of this recall mechanism are not fully understood, but can be imitated, at least clumsily with various electronic circuits. The book further suggests that learning is the combination of laying down memories and finding useful patterns in these memories.
Computer Programmer and Worship Leader. Have enjoyed reading since my mom got me hooked on Nancy Drew and Agatha Christie prior to my teen years. My brother got me hooked on audio books after I started having a longer commute to work. Love a variety of genres.
This is really a fascinating book when it comes to the author's theory of how the brain works. I was greatly surprised by his assertion that very few unified theories exist regarding how the brain produces or mainfests "intelligence". It will be interesting to see if the theories offered in this book will stand the test of time, but the observations made regarding pattern recognition seem very true to experience.
There are times that it is hard to visualize the concepts regarding the various "levels" of the cerebral cortex, but the downloadable drawings help a bit.
My biggest criticism of the book is not scientific, but the author's logical inconsistencies when dealing with metaphysics. The author makes it clear that he believes our "minds" and "selves" are nothing more that the functioning of the brain (ie. no "soul" or anything beyond the physical). He makes it clear that he believes that our beliefs about morality are shaped by the "patterns" we grow up with - and that these "biases" can be very counterproductive. He also states that romantic "love" is really nothing more that a complex chemical process that starts in the brain and moves throughout the body.
If the author had stopped there, I would do no more than respectively disagree. However, mere pages later the author states that it is important that we teach our children the "right" values and morals and that we espouse healthy loving relationships in our families. This author is far too smart to be unaware that if what he says is true in the prevous pages, both of these admonitions have no real meaning and are actually at odds with what he just stated.
Overall - fascinating stuff to think about, but realize that the author has a naturalistic bias that he applies consistently when dealing with science, but inconsistenly when addressing the logical conclusions of his scientific beliefs.
BTW - The author's preface was great - he would have made a GREAT reader for the book!!
Gen-Xer, software engineer, and lifelong avid reader. Soft spots for sci-fi, fantasy, and history, but I'll read anything good.
If, like me, you're a software developer with an interest in true artificial intelligence, this is a very stimulating book. Hawkins applies his own engineer's mind to an effort to discern and describe the human brain's underlying "cortical algorithm", the means by which intelligence "works". As Hawkins sees it, the neuroscience community has been too focused on the minutae of how neurons function, without giving adequate consideration to the brain's overall learning and decision-making architecture, while the computer science community has been too absorbed in traditional symbolic and procedural computation methods, ignoring insights that might be gleaned from studying the most powerful problem-solving system in nature. Of course, it's untrue that neuroscientists and comp-sci academics aren't interested in each other's disciplines, but the crossover is still a long way from mainstream. For coders working in industry (like me), Hawkin's thoughts may be revelatory.
The author focuses most of his attention on the cortex, the most recently evolved part of the human brain, and the one responsible for many functions of higher intelligence. His speculation is that this system uses the same generalized learning/prediction algorithm throughout, with little difference in how input from vision, hearing, touch, and other senses are processed. All this data is just sequences of patterns that the cortex filters through its multilayered hierarchy, each layer discerning trends in the input from lower layers, and forming models of the world.
This may sound like the traditional AI concept of "neural networks", but Hawkins breaks from that model with his view that the cortex uses massive amounts of feedback from higher, more time-invariant layers (which view the world more abstractly) to lower, more time-variant layers (which deal with more concrete experience), activating many context switches. He sees the cortex as a blank slate upon birth, which follows relatively simple programming to accumulate and categorizes knowledge. As our minds form, we find ourselves experiencing the world less through our sensory input, and more through our pre-formed models. Only when there is conflict between those models and our input sequences, is our conscious attention drawn to our senses.
In terms of biological neuroscience, this is all probably overly simplistic and not completely accurate (Hawkins doesn't give a lot of attention to the older, more instinctive parts of the brain), but if he's even partly right, his ideas have huge implications for artificial intelligence. If much our human intelligence really does boil down to a generalized memory-prediction algorithm -- one that may be complex, but not beyond our understanding -- the effects on the future will be astounding. Even if Hawkins wasn't able to prove his claims, they're fascinating to contemplate, and the next few decades will certainly shed a lot of light on their truth.
If this book speaks to you, consider also reading Marvin Minsky's A Society of Minds, which contains a lot of complementary ideas.
No doubt Jeff Hawkins is a brilliant cortex, given that each one of us and the world we live in is nothing more than the experience of an active cortex. But he is not a wise human, which, in my mind, is the greatest achievement of homo sapiens, not the ability to recreate intellience in a machine.
It is telling that he admits to never studying the nature of consciousness, but in one pithy statement of "fact", reduces it to one thing - the neo-cortex experience. When the cortex ceases to function, so does consciousness. It's not that he holds this "belief" that is troublesome, but rather the arrogance with which he holds his cortex-created model of the world to be "the truth."
This book is an excellent example of the scientist telling us how the trunk of an elephant works and the value of putting that information to work for us humans, but the consistent conclusion that the elephant IS the trunk is tiresome, offensive, and indicative of an immature soul.
Not being schooled in AI or neuroscience, I have no judgement on his theory - other than it is too reductionistic in general - and as one who has a passion for understanding as much as I can about being human, the discussion of how the brain works and what a model of this might be was enjoyable.
As for the narrator, I found the voice professional and easy to listen to. What struck me having heard Jeff's voice, however, was how different the tone and character was between them. Jeff's voice - in my Blink judgement - exudes enthusiastic immaturity; the actor's voice is calm, maturity. For the record, my invariant representation of wisdom (i.e., mature intelligence) is based on 30 yrs of studying religion, sprituality, and human development. IMHO, my cortex is well-trained in this area.
In sum, I welcome the endeavor to create truly intelligent machines, but I suspect Jeff & others will learn a lot more about the complexity of the human experience along the way.
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