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On Intelligence: How a New Understanding of the Brain Will Lead to the Creation of Truly Intelligent Machines Paperback – August 1, 2005
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“On Intelligence will have a big impact; everyone should read it. In the same way that Erwin Schrödinger's 1943 classic What is Life? made how molecules store genetic information then the big problem for biology, On Intelligence lays out the framework for understanding the brain.” ―James D. Watson, president, Cold Spring Harbor Laboratory, and Nobel laureate in Physiology
“Brilliant and embued with startling clarity. On Intelligence is the most important book in neuroscience, psychology, and artificial intelligence in a generation.” ―Malcolm Young, neurobiologist and provost, University of Newcastle
“Read this book. Burn all the others. It is original, inventive, and thoughtful, from one of the world's foremost thinkers. Jeff Hawkins will change the way the world thinks about intelligence and the prospect of intelligent machines.” ―John Doerr, partner, Kleiner Perkins Caufield & Byers
About the Author
Jeff Hawkins, co-author of On Intelligence, is one of the most successful and highly regarded computer architects and entrepreneurs in Silicon Valley. He founded Palm Computing and Handspring, and created the Redwood Neuroscience Institute to promote research on memory and cognition. Also a member of the scientific board of Cold Spring Harbor Laboratories, he lives in northern California.
Sandra Blakeslee has been writing about science and medicine for The New York Times for more than thirty years and is the co-author of Phantoms in the Brain by V. S. Ramachandran and of Judith Wallerstein's bestselling books on psychology and marriage. She lives in Santa Fe, New Mexico.
- Item Weight : 8.6 ounces
- Paperback : 272 pages
- ISBN-10 : 0805078533
- ISBN-13 : 978-0805078534
- Dimensions : 5.5 x 0.76 x 8.22 inches
- Publisher : St. Martin's Griffin; Reprint edition (August 1, 2005)
- Language: : English
- Best Sellers Rank: #120,317 in Books (See Top 100 in Books)
- Customer Reviews:
Top reviews from the United States
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The authors assert that, "The brain uses the same process to see as to hear. The cortex does something universal that can be applied to any type of sensory or motor system." And, "The idea that patterns from different senses are equivalent inside your brain is quite surprising, and although well understood, it still isn’t widely appreciated." Further, the way the brain processes information is consistently applied to all that sensory data. This common processing algorithm and sensory input processing helps our brains to adapt to an ever changing environment. That is why we can live and function in this modern world. A world in which change, and our need to adapt, has certainly outstripped evolutionary time scales.
The hypothesis put forward in this book rings true to me based on my understanding of complex systems and from observing the actions of my fellow human beings. This model (new to me but not necessarily new to the neuroscience world) doesn't negate my understanding from other reading how the human brain is "wired." Rather, it explains more fully how the system "hangs together" and accomplishes the incredible feats we witness every day. It also lays the foundation for a better understanding of human consciousness.
Once again the fact that we can understand our material world only in a "second hand" manner is driven home by this model. We work only with a representation of the world, and it is represented by a limited number of sensory inputs. From the standpoint of how we deal with our fellow human beings, this challenging and interesting book makes it clear that we should all be a lot less
certain that what we "know to be true" is actually a true representation of reality.
In the authors' words: "Finally, the idea that patterns are the fundamental currency of intelligence leads to some interesting philosophical questions. When I sit in a room with my friends, how do I know they are there or even if they are real? My brain receives a set of patterns that are consistent with patterns I have experienced in the past. These patterns correspond to people I know, their faces, their voices, how they usually behave, and all kinds of facts about them. I have learned to expect these patterns to occur together in predictable ways. But when you come down to it, it’s all just a model. All our knowledge of the world is a model based on patterns. Are we certain the world is real? It’s fun and odd to think about. Several science-fiction books and movies explore this theme. This is not to say that the people or objects aren’t really there. They are really there. But our certainty of the world’s existence is based on the consistency of patterns and how we interpret them. There is no such thing as direct perception. We don’t have a “people” sensor. Remember, the brain is in a dark quiet box with no knowledge of anything other than the time-flowing patterns on its input fibers. . . Your perception of the world is created from these patterns, nothing else. Existence may be objective, but the spatial-temporal patterns flowing into the axon bundles in our brains are all we have to go on."
What does all this mean to our daily lives? To me it simply means that there are solid reasons to make sure we always question our assumptions, work to find as much objective empirical data as possible and allow for other people to have a different view of the patterns they discern. Our individual perspective is all we have, but it isn't necessarily the only one nor is it necessarily the most accurate representation.
As a testament to it's relevancy today (I'm writing this Sept 2012, seven years after the book was published) he predicts three technological applications that may become available in the short term (5-10 years) due to breakthroughs in the kind of trainable AI this book discusses:
Computer vision and teaching a computer to tell the difference between a cat and a dog (this was successfully demonstrated in a study published in June 2012 - the paper is called "Building High-level Features Using Large Scale Unsupervised Learning" and is available online, or just search for "computer learns to recognize cats" for articles)
PDAs (as they were called back then) will understand naturally spoken instructions like "Move my daughter's basketball game on Sunday to 10 in the morning" (this kind of sentence, copied from the book verbatim, is exactly where Apple's AI application SIRI shines)
Smart/autonomous cars - in Aug 2012, Google announced that their self driving cars have logged 300 K accident free miles in live traffic on public roads, exceeding the average distance a human drives without accident.
The thing to note here is that when he wrote the book these three things had hurdles that we did not know how to solve, and at the time there was no clear linear progression of existing solutions that would guarantee they would be solved. His prediction is that we'll be able to train computers to recognize patterns by themselves which will allow us to eventually solve the problems (and this is exactly how the computer learned to recognize cat faces from youtube videos)
Furthermore, he predicts that AI will become one of the hottest fields within the next 10 years - and with the current explosion of interest in Big Data, Machine Learning, and applications like SIRI it is hard to deny that it lookslike we're right in the midst of seeing just this happen.
The grander implications of the model of this book won't be known for another 10-20 years or more, but 7 years in his general predictions about the field of AI have been very accurate.
Top reviews from other countries
It is, without a doubt, suitable for anyone who has an interest in artificial intelligence, from complete newcomers with no science background and no interest in maths or algorithms right up to established professors who feel stuck in a rut!
I have an MSc in Robotics and am undertaking my PhD in an AI related field. I have been very disillusioned with studies into AI that revolve around optimising algorithms for some specific task and entered into many arguments with academics who assert with absolute certainty that intelligence is, ultimately just a very complex algorithm.
This book argues about what intelligence is in a way that leaves the open-minded reader staggered and excited about the possibilities. Ultimately, it is all just guesswork and hypothesis but I for one shall be very disappointed if the author isn't uncomfortably close to the mark!
The broad essence of his argument is based on the observation of Vernon Montcastle that the mammalian cortex has a uniform global and microscopic structure. The cortex is the crinkly sheet that we see when looking at the brain from above and the sides, and that is wrapped around the more evolutionarily primitive inner components. A possible corollary of this observation is that `cortex is cortex', and that it is all implementing the same highly generalised processing algorithm. This is a rather counter-intuitive proposition as it would seem reasonable that the brain is doing a diversity of things and is therefore using a diversity of mechanisms to accomplish them. A vertical section through any part of the cortex reveals it to be comprised of six layers, each with a distinct composition of types and densities of neurones, and synaptic interconnections. Closer examination shows that these neurones are organised into a semi-astronomical number of transversely arranged microcolumns, with many interconnecting vertical synapses between the constituent neurones working to make each microcolumn into a tiny processing unit. Microcolumns operate together to make the functional areas that neuroscientists have been mapping in ever greater detail over the last century or so. These areas or regions are interconnected in a complex, but highly organised way, to establish a hierarchy in which areas connected to sensory inputs are at the bottom, and areas of increasingly abstract association are towards the top. The puzzling fact that there are more backward connections flowing down this hierarchy of areas, than there are forward/upward connections, has been known for a long while, but has arguably been largely ignored. This connectivity can be understood however in the light of Hawkin's proposed 'memory-prediction framework'. According to this model the brain's operation, and the essence of intelligence, consists of higher cortical areas constantly seeking to predict what patterns will be encountered next in the lower areas to which they are connected. These predictions are based on comparisons between memory, that is the cumulative analysis of previous patterns, as extracted by blind and simple algorithms, and the patterns of current input. Hawkin's thus argues that each area of the brain is constantly trying to anticipate its future inputs from its lower areas. Where such prediction fails we have the experience of surprise or novelty, and attention on behalf of areas further up the hierarchy is required in order to subsume that input under existing patterns, or to derive new patterns. Such new patterns will cause changes to flow up and down the hierarchy, this process being learning. He even argues that movement, as a result of activations in the motor cortex, is implemented in the same terms. Thus we actually move by anticipating the sensory inputs from our bodies, including the vestibular (balance), proprioceptive (disposition of the body in space), etc. that will arise as a result of issuing motor signals, and that it is these predictions themselves that drive the motor areas. He goes on to propose a reasonably detailed description of how this pattern-predicting model might be implemented down at the level of microcolumns and the synaptic connections between the neurones in the six layers.
For such an easy to read little book this is quite an extraordinary hypothesis that, at a stroke, makes a great deal of sense out of a mountain of baffling detail. If Hawkin's has achieved nothing else it is to demonstrate ways of thinking and writing about neural architecture that are more transparent and intuitive than has arguably been accomplished thus far. I am going to have to spend a while thinking about his theory, and considering whether his model really does capture everything that the cortex, and the generalised intelligence that gives us knowledge, skills, reasoning, language and so on, does for us. I have returned now to the Cotterill book and already I am finding myself thinking about what I am reading in a rather new and different way. Time will tell whether Hawkin's theory will turn out to be a master key that will bring some overarching sense to the mass of messy detail that my current knowledge of the brain presents me with. Time will also tell how his predictions about intelligent machines and the social revolution they could engender will transpire. That such machines are possible, and will be built I have no doubt. How long it will take is rather trickier. However, when they finally arrive it may be that we come to look back on this little book, which is as much a pamphlet or manifesto, as a milestone in intellectual history.
Jeff Hawkins and Sandra Blakeslee appear to be doing for Computer Science and Intelligent machines what Edward Witten had done for String Theory. Remember the madness that String Physicists went through till M theory was pronounced in the University of South California sometime 1995!
If we allow JS to stand for the initials of the two authors, one may conclude Intelligent Machines can be defined as follows:
JS= IM(neocortex). In other words, intelligent machine are function of our ability to understand and then imitate how the Neocortex works.
The two others succeeded to simplify a complex subject that made us the dominant animals on planet earth, though we are yet prove our mastery of the space beyond our atmosphere. They truly shed a light on why the AI world and neural network proponents are still struggling to deliver what many of us thought was achievable by the end of the 20st century.
Even if you do not understand differential equations or even basic algebra, this book will give you an insight of how your brain works in a language that is so simple and absorbing. Even if you are not coding or do not have nerdy or some kind crazy tendency, you will still appreciate understanding how the grey stuff between your ears makes you what you are and worth. You may truly even start training your brain to master other fields that you have not thought about before. The authors' attention may have not been to help you retrained your brain, but this would be a by-product of reading this.
For those of us, who are striving to understand, decode and them emulate how our brains are so good in doing certain things, I think this book would help us to sit back and rethink about how we architect the software we develop, even if this is a small software that operates within the bully dark valleys - a.k.a black pools - that frightened John Lewis to write a book that painted an overweight chines nocturnal, writing a software in one night, with no unit, integration and acceptance testing that works well in the morning and beats the rest!
The strange thing about this book is that as you keep reading it, you will simply and subtly learn how you behave, see this world, value your relationships and respect others would always depend on the quality of information fed into your Cortex from the day you were born to day. Hence, if we had one liberal school that every child in this world attends, perhaps, we would have lived in a fairer world, where we do not see abuse, unfairness and killings and so forth! While the authors do not mention, you would get to understand, during the end of the II World War, why PM Winston Churchill and his European counterparts believed in the art of Sphere of influence, while their North American counterparts abhorred this strange foreign policy.
If you ever happened to watch the "Gifted hand', after you read this book, you would appreciate how an illiterate mother succeeded to get her son, Ben Carson, to become a renown neurosurgeon. Remember, when she asked her sons to go the library and read and read. And the did this and the young Ben becomes the best in his class. It was all about feeding his brain with information that made him more informative than his class mates. His Neocortex got the memory it needed to predict what his teachers expected from him. Every thing you look would make sense for you, once you have gone through this book. You would even further predict the what would have happened to young Ben, if his mother did not go to work for the professor with house of full of books!
The authors also appear to have an unchallengeable knowledge of how a computers and programming languages work. They do understand how the SSDs has transformed the way we do use data, while they never mention the letters SSDs in their book and explain how we could make a memories that the applications we design can tap on demand without latency. They talk about the beauty of allowing machines to learn and then passing that knowledge from one machine to another, just like the way we use fast USB drivers to copy data from one place to another.
They even go deep on explaining why it would be plausible that we do not build one humongous software that mimics the entire Cortex, but modules that can specialise on different functionalities. And, if the need arises, all of this can be brought together one day. Here it looks like they did not only tell you how the magic stuff works, but also how we can utilise the art of SOA so as to bring together different sensors, brain like software and even machines that can react to or commanded by this software.
The authors view on the separation between the software and the mechanical parts is another design architect that can allow, for example, our intelligent devices to even share the same intelligent software hosted somewhere, where the art of SOA could be brought into play.
Although the authors were hesitant to precisely predict when this Intelligent thing should happen, though they mentioned in 10 ten years this may start happening, I think unknowingly we are already in the era of Intelligent Software - here I am avoiding the word machines - as I do not want the fainthearted among us to think we are sleep walking into the SKYNET situation. Just think about the software that gives you a quick and accurate answer about the historical exchange rates by just calling simple Restful Web API, hosted somewhere in the world. The application does not retrieve any data from any HD. But it use a collection of objects that lives or resides in Memory. Although this is a tiny example, it is a microcosm of what is to come. Think about the current claims on Big Data and how this would aide the creation of Cortex memory that would one day do more than then crunching numbers. Think about the art of correlation instead of that of causation - the era of big data.
I would urge every software architect, who had an interest in designing better applications, to read this book. This would help you think about the behaviour of your software from when the machine is turned on till it is switched off. This May also lead you to think about how much you could have achieved if you have used servers that never get switched off and argument it with Restful Web APIs as conduit for getting requests and returning what the client software wants; where this client software could be hosted on any lightweight devices.
I would recommend to ever ordinary (non-nerdy/crazy) individual of us to read this book, as it would help you understand how the art of prediction works.
However, I hope this book would not provide an excuse for those, who murder and abuse - from statesmen/women to ordinary individuals -to use this as an excuse by claiming that the horrendous acts they did was due to the corrupt memory they had in their Cortex!
The main value of this book is that Jeff describes a functional theory of the cortex, rather than just anatomy or operating principles. He explains why the cortex does what it does and makes it analogous to common experiences we all have.
Although it was written in 2005, even after a mass release of new neurological studies, this book remains a trusted source of theory.