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
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How to Create a Mind: The Secret of Human Thought Revealed 3.8 out of 5 based on 0 ratings. 12 reviews.
popscipopulizer More than 1 year ago
*A full executive summary of this book will be available at newbooksinbrief dot com on or before Monday, November 26. When IBM's Deep Blue defeated humanity's greatest chess player Garry Kasparov in 1997 it marked a major turning point in the progress of artificial intelligence (AI). A still more impressive turning point in AI was achieved in 2011 when another creation of IBM named Watson defeated Jeopardy! phenoms Ken Jennings and Brad Rutter at their own game. As time marches on and technology advances we can easily envision still more impressive feats coming out of AI. And yet when it comes to the prospect of a computer ever actually matching human intelligence in all of its complexity and intricacy, we may find ourselves skeptical that this could ever be fully achieved. There seems to be a fundamental difference between the way a human mind works and the way even the most sophisticated machine works--a qualitative difference that could never be breached. Famous inventor and futurist Ray Kurzweil begs to differ. To begin with--despite the richness and complexity of human thought--Kurzweil argues that the underlying principles and neuro-networks that are responsible for higher-order thinking are actually relatively simple, and in fact fully replicable. Indeed, for Kurzweil, our most sophisticated AI machines are already beginning to employ the same principles and are mimicking the same neuro-structures that are present in the human brain. Kurzweil takes us through both the neuroscience and the latest in artificial intelligence in order to convince us that this is the case. Given that our AI machines are now running according to the same principles as our brains, and given the exponential rate at which all information-based technologies advance, Kurzweil predicts a time when computers will in fact be capable of matching human thought--right down to having such features as consciousness, identity and free will (Kurzweil's specific prediction here is that this will occur by the year 2029). What's more, because computer technology does not have some of the limitations inherent in biological systems, Kurzweil predicts a time when computers will even vastly outstrip human capabilities. Of course, since we use our tools as a natural extension of ourselves (figuratively, but sometimes also literally), this will also be a time when our own capabilities will vastly outstrip our capabilities of today. Ultimately, Kurzweil thinks, we will simply use the markedly superior computer technology to replace our outdated neurochemistry (as we now replace a limb with a prosthetic), and thus fully merge with our machines (a state that Kurzweil refers to as the singularity). This is the argument that Kurzweil makes in his new book 'How to Create a Mind: The Secret of Human Thought Revealed'. Kurzweil lays out his arguments very clearly, and he does have a knack for explaining some very difficult concepts in a very simple way. My only objection to the book is that there is a fair bit of repetition, and some of the philosophical arguments (on such things as consciousness, identity and free will) drag on longer than need be. All in all there is much of interest to be learned both about artificial intelligence and neuroscience. A full executive summary of this book will be available at newbooksinbrief dot com, on or before Monday, November 26; a podcast discussion of the book will be available shortly
Anonymous More than 1 year ago
Starts off strong and on target, but slips into too much vanity exhibitionism there for a while. Recovers some of its initial pace later on.
Gardenmax More than 1 year ago
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.
Professor_A More than 1 year ago
I was eager to read the book, based on a few comments I had heard, but, regrettably, I found it disappointing and ultimately set it aside. I suppose I was expecting something more forward looking and evocative, yet I continuously felt like I was reading an historical account with frequent digressions that seemed to be a personal defense. I am sure there are readers who were delighted by the book, but, for me personally, it was a bit of a letdown for the reasons I just explained.
Tunguz More than 1 year ago
Ever since I read “Singularity is Near” I’ve been fascinated by Ray Kurzweil – his wirings, ideas, a predictions. He’s not been afraid to go on the limb and make some brave and seemingly outlandish forecasts about the upcoming technological advances and their oversize impact on people and society. One of the main reasons why I always found his predictions credible is that they can, in a nutshell, be reduced to just a couple of seemingly simple observations: 1. Information-technological advances are happening exponentially, and 2. Information technology in particular is driving all the other technological and societal changes. The rest, to put it rather crudely, are the details.  In “How to Create a Mind” Kurzweil zeroes in on just one scientific/technological project – creating a functioning replica of the human mind. He uses certain insights from information technology and neurology to propose his own idea of what human mind (and by extension human intelligence) are all about, and to propose how to go about emulating it “in silico.” Here too Kurzweil reduces a seemingly intractable problem that the humanity has grappled with for millennia to just a couple of overarching insights. In his view the essence of virtually all cognitive processes can be reduced to the scientific paradigm of “pattern recognition” – an ability of computational agent to identify and classify patterns. And the information theoretical and engineering tool for emulating the kind of pattern recognition that goes on in a mind is the mathematical technique called “hierarchical hidden Markov chains” (HHMS). What gives Kurzweil confidence about this insight and this kind of approach are the successes that he has had in starting and marketing companies which used HHMS for speech and character recognition. Many of these technologies and their derivatives have in recent years made it to the wide ranging set of consumer products (Apple’s Siri is just one such example), so it’s not surprising that Kurzweil would be feeling exceptionally confident about his insights. However, the history of computation and artificial intelligence is filled with examples of paradigms that seemed promising at one level of “thinking” complexity only to be proven ineffective at tacking more sophisticated problems. Furthermore, even though I am not an expert at neuroscience, Kurzweil’s descriptions of what goes on in an actual biological brain come across as not too sophisticated. He is obviously well informed on many neurobiological topics, far above what even a well-educated reader may know, but from what I know about biology the intricacies of the brain are still too complex to be reduced to a simple (simplistic?) model. Kurzweil may still turn out to be right about what he is proposing in this book (and if I had to bet I would loath to bet against him), but the evidence that he presents leaves a lot of potential gaps and pitfalls that would need a lot more convincing to completely bridge. This is definitely a very well written book with a lot of interesting and though-provoking insights and predictions. Anyone interested in scientific and technological progress in the upcoming years and decades would greatly benefit from reading it, especially since it’s such an enjoyable book. I highly recommend it. 
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Ummmmmmmmm... first thats such a weird title..... what are you frankenstein?........ i wish i could put 0 stars!!!!!!