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199 of 209 people found the following review helpful
4.0 out of 5 stars Fascinating, Disappointing but Ultimately Enlightening
How to Create a Mind: The Secret of Human Thought Revealed by Ray Kurzweil

"How to Create a Mind" is a very interesting book that presents the pattern recognition theory of mind (PRTM), which describes the basic algorithm of the neocortex (the region of the brain responsible for perception, memory, and critical thinking). It is the author's contention that the...
Published on November 16, 2012 by Book Shark

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22 of 24 people found the following review helpful
2.0 out of 5 stars Old news in a new package
Ray Kurzweil writes as an authority on AI (artificial intelligence). As a practitioner in that field myself, I am not impressed by his expertise. He knows one or two subfields of AI well and is a talented inventor, but his vision of the future of AI simply doesn't hold water.

An informed layman who has never read an AI textbook (or history, such as Nils...
Published 18 months ago by David W. Nicholas


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199 of 209 people found the following review helpful
4.0 out of 5 stars Fascinating, Disappointing but Ultimately Enlightening, November 16, 2012
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How to Create a Mind: The Secret of Human Thought Revealed by Ray Kurzweil

"How to Create a Mind" is a very interesting book that presents the pattern recognition theory of mind (PRTM), which describes the basic algorithm of the neocortex (the region of the brain responsible for perception, memory, and critical thinking). It is the author's contention that the brain can be reverse engineered due to the power of its simplicity and such knowledge would allow us to create true artificial intelligence. The one and only, futurist, prize-winning scientist and author Ray Kurzweil takes the reader on a journey of the brain and the future of artificial intelligence. This enlightening 352-page book is composed of the following eleven chapters: 1. Thought Experiments on the World, 2. Thought Experiments on Thinking, 3. A Model of the Neocortex: The Pattern Recognition Theory of Mind, 4. The Biological Neocortex, 5. The Old Brain, 6. Transcendent Abilities, 7. The Biologically Inspired Digital Neocortex, 8. The Mind as Computer, 9. Thought Experiments on the Mind, 10. The Law of Accelerating Returns Applied to the Brain, and 11. Objections.

Positives:
1. Well researched and well-written book. The author's uncanny ability to make very difficult subjects accessible to the masses.
2. A great topic in the "mind" of a great thinker.
3. Great use of charts and diagrams.
4. A wonderful job of describing how thinking works.
5. Thought-provoking questions and answers based on a combination of sound science and educated speculation.
6. The art of recreating brain processes in machines. "There is more parallel between brains and computers than may be apparent." Great stuff!
7. Great information on how memories truly work.
8. Hierarchies of units of functionality in natural systems.
9. How the neocortex must work. The Pattern Recognition Theory of Mind (PRTM). The main thesis of this book. The importance of redundancy. Plenty of details.
10. Evolution...it does a brain good. Legos will never be the same for me again.
11. The neocortex as a great metaphor machine. Projects underway to simulate the human brain such as Markram's Blue Brain Project.
12. Speech recognition and Markov models. Author provides a lot of excellent examples.
13. The four key concepts of the universality and feasibility of computation and its applicability to our thinking.
14. A fascinating look at split-brain patients. The "society of mind." The concept of free will, "We are apparently very eager to explain and rationalize our actions, even when we didn't actually make the decisions that led to them." Profound with many implications indeed.
15. The issue of identity.
16. The brain's ability to predict the future. The author's own predictive track record referenced.
17. The laws of accelerating returns (LOAR), where it applies and why we should train ourselves to think exponentially.
18. The author provides and analyzes objections to his thesis. In defense of his ideas. Going after Allen's "scientist's pessimism."
19. The evolution of our knowledge.
20. Great notes and links beautifully.

Negatives:
1. The book is uneven. That is, some chapters cover certain topics with depth while others suffer from lack of depth. Some of it is understandable as it relates to the limitations of what we currently know but I feel that the book could have been reformatted into smaller chapters or subchapters. The book bogs down a little in the middle sections of the book.
2. Technically I disagree with the notion that evolution always leads to more complexity. Yes on survival but not necessarily on complexity.
3. The author has a tendency to cross-market his products a tad much. It may come across as look at me...
4. A bit repetitive.
5. Sometimes leaves you with more questions than answers but that may not be a bad thing...
6. No formal separate bibliography.

In summary, overall I enjoyed this book. Regardless of your overall stance on the feasibility of artificial intelligence no one brings it like Ray Kurzweil. His enthusiasm and dedication is admirable. The author provides his basic thesis of how the brain works and a path to achieve true artificial intelligence and all that it implies. Fascinating in parts, bogs down in other sections but ultimately satisfying. I highly recommend it!

Further suggestions: "Subliminal: How Your Unconscious Mind Rules Your Behavior" by Leonard Mlodinow, "The Believing Brain: From Ghosts and Gods to Politics and Conspiracies---How We Construct Beliefs and Reinforce Them as Truths" by Michael Shermer, "The Scientific American Brave New Brain: How Neuroscience, Brain-Machine Interfaces, Neuroimaging, Psychopharmacology, Epigenetics, the Internet, and ... and Enhancing the Future of Mental Power" by Judith Horstman, "The Blank Slate: The Modern Denial of Human Nature" by Steven Pinker, "Who's in Charge?: Free Will and the Science of the Brain" and "Human: The Science Behind What Makes Us Unique", by Michael S. Gazzaniga, "Hardwired Behavior: What Neuroscience Reveals about Morality 1st Edition by Tancredi, Laurence published by Cambridge University Press Paperback" by Laurence Tancredi, "Braintrust: What Neuroscience Tells Us about Morality" by Patricia S. Churchland, "The Myth of Free Will" by Cris Evatt, "SuperSense" by Bruce M. Hood and "The Brain and the Meaning of Life" by Paul Thagard.
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115 of 124 people found the following review helpful
4.0 out of 5 stars The Cortex Spins its Tales with Hidden Markov Models, November 14, 2012
By 
Bob Blum (California, USA) - See all my reviews
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Like a news commentator explaining a bad day on Wall Street,
the cortex has an explanation for everything -
it generates our subjective universe. To paraphrase George Box,
all our brain's models of the world are wrong,
but some are useful, generative, and simple (but not too simple).

In How to Create a Mind acclaimed inventor Ray Kurzweil
puts forth a model of how the brain works:
the pattern recognition theory of mind (PRTM).
The brain successively interiorizes the world as a set of patterns.

Kurzweil's framework uses hierarchical hidden Markov models (HHMMs)
as its main stock in trade. HHMMs add to the PRTM model the notion
that those patterns are arranged into a hierarchy of nodes,
where each node is an ordered sequence of probabilistically matched lower nodes.

So, the key question for me is this: are HHMMs
really the key to understanding and building a mind?

Ray has been on this track since the sixties,
when he and I were classmates at MIT. In a spectacular
career spanning decades, Ray invented systems for OmniPage OCR,
text to speech (famously for Stevie Wonder), and
automated speech recognition as in Dragon Naturally Speaking.
Nuance bought Ray's precursor company.

All automatic speech recognition nowadays is done using HHMMs,
and the results are astounding. For example, see Microsoft Research
Chief Rick Rashid's YouTube "Speech Recognition Breakthrough."
A computer transcription of Rick's talk appears in
real time and is quite accurate.

The amazing success of HHMMs in handling speech and language is
a story that needs to be understood by AI aficionados, and
Kurzweil presents this topic in a beautifully comprehensible exposition.

Kurzweil elaborates a story here that 1) the cortex is
the key to thought; 2) it is hierarchically organized into
300 million pattern recognizers; 3) each pattern recognizer
consists of a 100 neurons in a vertical minicolumn, and
4) those pattern recognizers communicate with one another
via a Manhattan-like grid (similar to an FPGA) -
end of story for the neocortex.

This is a story similar to the one told by entrepreneur Jeff Hawkins in
On Intelligence, and one that Hawkins, his former associate Dileep George
(now at Vicarious), and Kurzweil himself are trying to capitalize on
in cortex-engineering startups. I eagerly follow their results.

So, HHMMs work well and are a required part of a computational
neuroscience curriculum, but ARE THEY THE MASTER KEY that will unlock
the doors not only to a full understanding of the mind
but also to a future of superintelligent AIs? How to Create a Mind
is a good story but IS IT FICTION or nonfiction?

While HHMMs are required reading for automatic speech recognition,
they DO NOT DO all the brain's heavy-lifting. Rather, the brain employs
MANY mechanisms (which robots that aspire to humanity
may need to incorporate or emulate.)

Five stars for HHMM exposition. Subtract one star for giving short shrift
to the following pivotal neuroscience principles: 1) attentional mechanisms,
2) brain-wide dynamical networks, 3) gamma oscillations and inhibitory networks
and also 5) the role of insula and brain stem in emotion, 6) reward based learning
including the essential role of basal ganglia and midbrain,
and 7) hippocampus and memory.

Despite its corticocentric focus, Kurzweil's impressive engineering
successes make this an important story; furthermore, it is engagingly told.
I cover neuroscience and AI at bobblum.com . Below are two recent 'DO NOT MISS'
FIVE STAR stories.)

Addendum: 30 Nov 2012 - Today's issue of SCIENCE (and Ray K's newsletter)
features a story about a new 2.5M spiking neuron model (SPAUN) that
performs 8 tasks and outputs to a physically modeled arm.
See the videos at NENGO > Videos > Collection of Spaun.
That is the state of the art!

Addendum: Jan 2013: Want to know where the brain stores meaning? (YOU DO!)
See Alex Huth's 5 min YouTube from Jack Gallant's lab. Search:
Alex Huth, gallantlabucb "Perceptual Object and Action Maps in the Human Brain."
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100 of 112 people found the following review helpful
5.0 out of 5 stars The Path to True Artificial Intelligence, November 13, 2012
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In "How To Create a Mind," Ray Kurzweil offers a fascinating and readable overview of his theory of how the human brain works, as well as a road map for the future of artificial intelligence.

Kurzweil makes a compelling argument that choosing the proper scale is critical when approaching the problem of how the brain works. Many skeptics believe that we are no where near understanding or simulating the human brain because of its overwhelming complexity. However, Kurzweil suggests that a complete understanding of the micro-level details (such as individual neurons or even biochemistry) is really not necessary. Instead, the brain can be understood and simulated at a higher level. The book gives many examples in other fields of science and engineering where such a high level approach has produced tremendous progress.

The core of Kurzweil's theory is that the brain is made up of pattern processing units comprised of around 100 neurons, and he suggests that the brain can be understood and simulated primarily by looking at how these lego-like building blocks are interconnected.

The book includes accounts of some of the most important research current research in both brain science and AI, especially the "Blue Brain Project" (that is working on a whole brain simulation), and also the work on IBM's Watson (Jeopardy! champion) computer.

Kurzweil continues to assert that we will have human-level AI by around 2029. A typical human brain contains about 300 million pattern processing units, but Kurzeil thinks that AIs of the future might have billions, meaning that machine intelligence would far exceed the capabilities of the human mind.

Ray Kurzweil is clearly an optimist both in terms of the progress he foresees and its potential impact on humanity. If he is even partly right in his predictions then the implications could be staggering. Machines that are as smart, or even smarter, than people could completely transform society, the economy and the job market.
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22 of 24 people found the following review helpful
2.0 out of 5 stars Old news in a new package, June 2, 2013
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Ray Kurzweil writes as an authority on AI (artificial intelligence). As a practitioner in that field myself, I am not impressed by his expertise. He knows one or two subfields of AI well and is a talented inventor, but his vision of the future of AI simply doesn't hold water.

An informed layman who has never read an AI textbook (or history, such as Nils Nilsson's or Pamela McCorduck's) and knows nothing about cognitive neuroscience (see recent books by Michael Gazzaniga and V. S. Ramachandran) may find this book impressive. It is a place where a great deal of mediocre information is contained between two covers. However, I don't think Kurzweil knows enough about human learning (a large and complex field) and human intelligence (ditto) to get a solid handle on what tasks machine learning and machine intelligence must be able to perform and in what order their respective subtasks will probably be mastered.

There are gifted multidisciplinary thinkers in AI and cognitive science who have proved their ability to run rings around Kurzweil, and none of them purports to be a "futurist." Ever since Herbert A. Simon predicted (in 1957) that in a decade the strongest chess player in the world would be a machine (it was four decades before IBM's DEEP BLUE beat World Chess Champion Gary Kasparov in tournament play in May, 1997), serious AI researchers have been very cautious in making predictions about the not-so-near future.

There is an established literature on mind design and Kurzweil has contributed very little to it. This book does not summarize that literature or move it forward. I sincerely doubt it will be remembered five years from now. There are too many good people, from Steven Pinker (who explains the mind for those who aren't experts in it) and John Robert Anderson (one of the experts) to Daniel Dennett and Patricia Churchland (the latter two being examples of a brave new philosophy of mind), who have made contributions to how minds can realistically be designed for us to waste our time with the mediocre thoughts of "futurists" and others who aren't telling us a believable story about how they will be built.

We already know a great deal more about mind design and implementation than Ray Kurzweil does, a field I was working in more than 30 years ago. To be blunt, Kurzweil isn't plugged into enough of the right sources of information.
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57 of 69 people found the following review helpful
3.0 out of 5 stars Overselling and self-promotion, December 18, 2012
This would be a pretty good book if it would be half as long and the author would have taken a more objective (and therefore modest) view point.

Ray Kurzweil claims that he has a very good grasp of the working of the brain. While his statements are rooted in true scientific facts, he does not seem to provide any new or substantial insights to the topic. Especially, he falls short on his main promise: explaining how to build a generic AI mind.

This is far from surprising: if he had some unique insights, he would be better off capitalizing on it rather than just giving it away.

Still, the book is entertaining and worth reading, but his shameless self-promotion and overstating his own contributions to the area while hardly giving any credit to anyone else leaves a very bad aftertaste.
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76 of 96 people found the following review helpful
1.0 out of 5 stars Disappointed, November 14, 2012
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Being an avid Ray Kurzweil fan, had expected something interesting from him. For all
practical purposes, i knew that there would be no ground-breaking secret revealed.
Rather, i had expected a nice framework, a platform to step upon or at least one new
perspective.

This book is just a slightly different take on Jeff Hawkins work On Intelligence.

By the time, i reached chapter 3 and read about the PRTM, i wanted to quickly read the rest
of the book and get over with it. Somehow, i felt that the book "On Intelligence" by Jeff
Hawkins and Sandra Blakeslee was much better and more logical with apt experiments
documented to highlight every point.

This book taught me "Hierarchical hidden markov models", a lot of things that happened at
Ray's former offices, loads of marketing for Nuance and Siri and frankly, nothing else.

Ray, if you happen to read this comment, nothing personal. Just a great fan of yours ranting
about his disappointment here.
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11 of 12 people found the following review helpful
1.0 out of 5 stars Does not explain how to create a mind., March 20, 2014
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This book is written by an upper management type who has not been in the trenches for years. He has very little knowledge of AI and this book is an exploration into unproven theories of intelligence production. He starts out with what he calls "Pattern Recognizers " and then continues to quote the use of those without ever providing a solid explanation for what they are and what they do. He just says they work and that he did a lot of research on them.

He talks about the biological functions of the brain but never makes a connection for how that view of the brain produces intelligence (a mind). He gives a complicated view of the brain and shows the storage methods the brain might use, the way words are stored and other unimportant facts that do nothing to make the reader understand how a mind is produced.

He also attempts to explain the functions of the human brain in computer science terms which may be OK for computer science professionals but is probably cumbersome for the layman. I have a computer science background and I found it a very hard read. He never gives even a perfunctory explanation of how the brain produces thought, which I would assume would be included in a book that claims it knows how to create a mind. The book does nothing of the sort.

Secret of human thought revealed? I don't think so!
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28 of 36 people found the following review helpful
2.0 out of 5 stars Disappointing - poor explanations, especially from a scientist, December 7, 2012
By 
I had high hopes for this book, as I've read - or tried to read - a couple of others in the field of consciousness. I thought surely the great Ray Kurzweil would be able to do the topic justice.

He doesn't, although he gives it a fair try. The book is a bit scattered, and not completely coherent. He basically doesn't answer the question "How to Create a Mind" - he merely makes a prediction that by about 2029, we'll have the computational power available to simulate one. I thought that he would discuss the actual ways we could recognize consciousness better, but he doesn't. He leaves that to the philosophers.

He puts forth the proposition that the way the human brain (and other brains as well) do what they do is through pattern recognition. He refers to this as the "pattern recognition theory of mind," or PRTM. However, even though he is a scientist, he falls into the layman's trap of calling this a theory. It is not. He provides little proof for it in the book, and prefaces some of his statements about it with "I believe." Well, that and $2.25 will get you a ride on the subway. This is not a scientifically proven theory, like the theory of gravity, or the theory of electromagnetism. This is merely his hypothesis. And the reason it is his hypothesis because he has worked extensively field of speech recognition, and this is how he did it. That's nice, and it's relatively interesting, but that's no theory.

I also didn't think he did that great a job in explaining what he did choose to explain. According to him, a lot of computer learning nowadays - meaning how computers are able to refine what they do and get better at it - comes from something called "hidden hierarchical Markov models," or HHMM. This, he insists will be the key to computer consciousness in the future, and he refers to it often in the book. He tries to explain how the HHMM works, with different weights on different variables, strengthening or weakening signals. But he doesn't provide a clear example of how an HHMM does what it does. I'd love to know how computers learn. He didn't provide it.

All in all, he is an good writer, and discusses topics in a thought-provoking way. But if you're looking for the answer to "what is consciousness?", this isn't it.
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25 of 32 people found the following review helpful
1.0 out of 5 stars Fails to deliver, February 3, 2013
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The areas of cognitive neuroscience and artificial intelligence have grown by leaps and bounds in the last two decades, and both of these areas have found real-world application. These applications are the consequence of the concentrated efforts of hundreds of researchers, technicians, and venture capitalists, who typically had to spend a lot of time in the trenches doing the grudge work that is the rule rather than the exception for difficult areas such as these. There were false leads and conceptual barriers that had to be overcome, and success was and is measured by working applications, and not by the ability to counter arguments against those who claimed that advances in machine intelligence were either impossible or very limited. There is much remaining to be done, but whatever goals are set and attained should not be dictated by marketing hype or philosophical objections to the idea of artificial intelligence.

The author of this book has been one of the early innovators in domain-specific artificial intelligence, meaning that the applications and devices he helped to created are limited to very narrow domains of expertise and knowledge. In that respect he is not so much different than most of the talented individuals who have contributed to the field of machine intelligence. The major difference between the author and others lies in his vision of the future of this field. Progress in this field will be hyper-exponential he has argued in prior books, and this progress will include the creation of an artificial brain that can not only perform the functions of the human brain, but do them much, much faster. This book gives an overview of how to build such a brain, with pattern recognition being the predominant tool by which this brain will deal with knowledge and build its expertise. Such a tool is the primary method by which humans deal with the world, the author argues, and he gives some evidence drawn from the field of neuroscience to support his claim.

Although the author's discussions are interesting and thought provoking, as a whole the book does not deliver, and one of the main reasons for this is the lack of a quantitative measure of intelligence that will gauge progress in the development of an artificial brain. The word "intelligence" appears in at least sixty-five places in this book in the context of both human and machine intelligence, but absolutely no quantitative measure of it is described or articulated upon. If progress in machine intelligence is "hyper-exponential" as the author claims, than he needs to inform the reader to what extent a machine is for example 2 times, or 4.6 times more intelligent than another machine. Such a measure would not only support his case on the rate of advance in machine intelligence but would also be extremely valuable to AI researchers as a whole. The field of AI is begging for a workable/practical definition and measure of intelligence.

Readers will have to accept the qualitative assessments the author makes in the book regarding the advances in AI. He seems to be very impressed with the IBM Watson machine and its ability to understand both spoken and written language in any domain of knowledge, but the author does not give any examples where Watson has taken the initiative to seek out or create new knowledge on its own. The reviewer is not aware of a Watson-like machine that can devise new theories independent of domain or area of knowledge. Humans of course are able to do this with gusto, and more than ever it is this ability, and not token assimilation of existing knowledge, that characterizes human intelligence.

There are also many other problems with this book, even anecdotal ones like the authors mistaken notion of the motion of the Crookes radiometer, and the lengthy diatribes on consciousness and free-will. The book ends with even more refutation of arguments raised by philosophers and academics against the notion of machine intelligence. The author is successful in the refutations of these arguments, but the building of an artificial brain depends on constructive work, not the winning of philosophical debates. If the author could refrain from indulging in these debates and get on with the difficult task of creating intelligent machines, the AI research community, and the popular audience he is addressing would be much better served. As it stands, the book offers no constructive guidance to creating an intelligent machine, and its contents would be very different if it did.
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44 of 58 people found the following review helpful
1.0 out of 5 stars Buy "On Intelligence" instead, November 27, 2012
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Spoiler summary: String Markov Models around Jeff Hawkins &co theories (in print 8 years ago), repeatedly remind everyone that you're Ray Kurzweil and the key insight in this idea is somehow, fundamentally yours, talk about the old days, and voila: mind created!

This book is a sad fumble: a rehash of his old books (almost word-for-word in some cases), punctuated by some vaguely interesting personal nostalgia, and an awkward landgrab as he reveals his grand "PRTM" (that looks uncomfortably like other people's work).

Go and buy "On Intelligence" by Jeff Hawkins instead.
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How to Create a Mind: The Secret of Human Thought Revealed
How to Create a Mind: The Secret of Human Thought Revealed by Ray Kurzweil (MP3 CD - August 27, 2013)
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