Rating: 
Summary: A comprehensive book on science, highly recommended
Review: First, I agree with many of the negative reviews that criticize the book's abundance of self-claimed "discoveries" and lack of references to other research works. They are annoying at times, but nevertheless, the book contains so many educational ideas in such a grand scale that I'm willing to ignore those annoyance and praise it as the best science book I've ever read and recommend it to everyone who is interested in science and education.I have a Ph.D in computer science. I read every page of the book's main text and many of the notes. The book satisfied me at many levels for covering different fields of science. In the field of computer science, which I am most familiar with, the book covers areas such as computability, complexity, AI, cryptography, and many more. I found it very refreshing to go over these areas with a new perspective. The universality proof of rule 110 cellular automata, arguable the best technical contribution of the book, is elegant and well~~ presented. For
other fields like theoretical physics, biology, chaos theory, etc, I found it very educational to have this book review many of the historical discoveries in these areas, and present them together with new thoughts, under a new paradigm of computing with cellular automata. The most amazing achievement of the book is it's breadth. It covers so many different fields, yet consistently presents them under the same paradigm. Although many discoveries are made by others, this book~~ is one of its kind that covers multiple classical and modern scientific fields with detailed explanations. This by itself is a great contribution. I respect the author's tremendous effort in researching all these fields. I'm also impressed by the book's detailed yet non-academic presentation. Overall, this book does give me a new perspective in understanding the world, the nature, the science, and the technology development. Whether the new perspective is THE correct one or not is not that~~ important to me. What I appreciate the most is that the book presents this perspective in such a consistent and clean style with such a comprehensive coverage.~
Rating: 
Summary: Comme ci, comme ca
Review: If you are interested in cellular automata (CA), then going through Wolfram's tome will be interesting and may provide ideas for further research and development. Yet, even though Wolfram's ideas are logically set out developed enough, they lack the kind of definitiveness that one would expect from a book so named. To the book's further detriment, the unnatural and excessive use of first person used throughout the book give the text an air of superiority (possibly arrogance as others have mentioned but I don't feel this that much), which is undesirable of course in a technical document which this claims to be. If A New Kind Of Science was pushed to slightly a different angle, then it may have come off a little better.
However for those with an inquiring, scientific mind, A New Kind Of Science will prove a fascinating, intriguing read.
Rating: 
Summary: indispensible
Review: For years I have been searching for something heavy enough to stop my back door flying open in strong winds. A New Kind Of Science by Stephen Wolfram is perfect for this use, highly recommended for back doors everywhere. May also be useful for wonky tables or for short people who need to reach a high shelf. Indispensible.
Rating:
Summary: people don't get it
Review: it's not what the book says, it's simply the SIZE of the book that is impressive. you can take this book with you to your local denny's, and plop it down like a boat anchor on the middle of the table, and you'll barely have any room for coffee and food. then, you page through it and look at the pictures. and you waitress with think you're really smart. or a really big geek with a really big book.
Rating:
Summary: A few comments
Review: As others here have already commented better than I could on the application of Wolfram's ideas to other sciences, I thought I would limit my comments to one area--the brain sciences. This will require my discussing some technical details of neurobiology a little bit, so I apologize in advance for that, and hope that you will bear with me. Although Wolfram's new magnum opus is controversial and has gotten very mixed reviews, as I said, I was hoping his ideas might be useful in a very specific area of biology myself, neurophysiology, which is where my background mostly is. Wolfram's ideas about cellular automata may have significant potential in the brain sciences area. In fact, Wolfram's idea isn't so different from one that I had about 20 years ago. But Wolfram is a lot better at things like math and cellular automata than I am, so I'm happy he ended up doing all the work instead of me! But getting on to the specifics, sensory neurophysiology has been shown to be quite mathematical as a result of the work of a pioneering mathematician by the name of David Marr 25 years ago, whose ideas revolutionized neurobiology almost overnight, after which the field was never the same. To mention just a few of his important ideas, Marr's demonstrations that retinal receptive-field geometry could be derived by Fourier transformation of spatial frequency sensitivity data, that edges and contours could be detected by finding zero crossings in the light gradient by taking the Laplacian or second directional derivative, that excitatory and inhibitory receptive fields could be constructed from "DOG" functions (the difference of two Gaussians), and that the visual system used a two-dimensional convolution integral with a Gaussian prefilter as an operator for bandwidth optimation on the retinal light distribution, were more powerful than anything that had been seen up to that time. It was as if vision research suddenly acquired its own Newtonian Principia Mathematica, or perhaps General Relativity Theory, in terms of the new explanatory power Marr's theories provided. Basically, in one fell sensory neurobiology also became an area of theoretical physics rather than purely biology, giving the area a rigor and elegance never before seen--an amazing achievement for a young man who died so prematurely from leukemia at the age of 36. But getting back to Wolfram's book, since most of the mechanisms for information processing in the brain ultimately depend on cell assemblies or individual circuits of few to many neurons, the analogy between cellular automata and neural circuits is an interesting and possibly valid one. Although we don't have a very good idea about more complex kinds of circuits in the brain, except in very broad, functional terms such as the kinds of questions and answers cognitive neuroscience can frame and provide, many of them may operate according to the principles of cellular automata. So although it may be too early to conclude Wolfram's ideas apply to all complex phenomena, I'm hopeful that at least some complex biological systems, especially those relating to human psychobiology, such as limic system mechanisms, which don't seem very amenable to mathematical analyses of the type that have worked so well in sensory neurophysiology, can be explained by simple, rule-based programs of the sort Wolfram has described, in addition to the neural circuits themselves. The difficulty in accounting for more complex behavior comes as no surprise, since although the brain's "hardware" ultimately must function according to well-understood neurophysiological and biophysical mechanisms (as in the case of nerve conduction) the brain's "wetware" or "software" is obviously very different and can operate according to very different principles, some of which may be explained by Wolfram's ideas, although it's possible that the more biophysical properties of neural networks themselves may be amenable to cellular analysis. In any case, Wolfram has provided at the very least a heuristic impetus further research in the brain area, and I hope, some powerful explanations as well. Despite the bold claims Wolfram makes for his ideas, which challenge traditional approaches, Wolfram's ideas need to be taken seriously and fairly evaluated. In some cases, they may represent a better alternative for understanding at least complex neural systems than purely mathematically-based ones. I had one final comment. In our universe, the devil seems to be in the details, so no doubt some of Wolfram's rules will turn out to applicable and useful in the real world (such as Rule 30), and others won't. This is to be expected. As in the case of theoretical physics, one can write down many differential equations that are mathematically correct; the problem is determining which ones apply to our actual universe. I'm sure it won't be any different with Wolfram's Rules, but, as with Maxwell's field equations, the Schrodinger equation, and Einstein's famous E=MC^2, the ones that do work will result in major advances in the understanding of our universe. Looking to the future, perhaps the next revolution will be the synthesis of mathematical explanations with cellular automata. But we may need to wait for another once-in-a generation-genius like Marr or Wolfram to get that. In the meantime, research in cellular automata will no doubt continue, and I'm sure we'll soon see whether Wolfram's ideas are valid or not for at least some complex systems.
Rating: 
Summary: Cellular Automata will not make it.
Review: With this book, Stephen Wolfram believes he will change the scientific world as we know it. His cellular automata methodology would radically change all scientific fields. It would change the scientific method, and also change the way we teach science in school. Strangely enough, you probably will never hear of cellular automata again. Why would we replace a scientific method that is based on exploring rational cause and effect, developing powerful and brilliant equations (law of gravity, and theory of relativity come to mind) that very efficiently capture the essence of our universe with cellular automata. There is no question that cellular automata are very intriguing. That you can use them to apparently duplicate many natural phenomena in nature that appear completely random. But, will we be able to predict earthquakes, the movement of stock markets, I don't think so. In other words, can you really think of a realistic valuable practical application for cellular automata. I don't think so. Yes, you can replicate the pattern of shells such as they are described on the cover page. And, that is pretty amazing. But, this has no practical application whatsoever. Stephen Wofram is a brilliant man. But, I am looking forward to his next intellectual venture. I am done with this one.
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Summary: When reading this book...
Review: ... I could almost hear the "snapping of the twig" in Stephen's mind. Although his "twig" didn't snap, mine sure did. This book blew me away, I'm sure it'll blow your minds and "snap your twigs" as well.
Rating:
Summary: Challenging--A Collector's Item
Review:
Generally I read two-thirds of the books I buy, and review two-thirds of the ones I read. Stephen Wolfram's book proved to be too much for me. Although I was not planning to review it because I cannot claim to have read it properly, I decided to post a recommendation: buy this book even if you might not read it all. The author has subsidized the work, and the book is far more valuable than its price.
Rating:
Summary: awesome
Review: ok, so im 17 and just about to graduate highschool, when i was told that i had to read a book for a final project in a math class. i have never been a fan of reading books, whether for school or pleasure. nothing has ever seen to catch my attention, however once i picked up this book, i couldn't put it down. i know its corny, but that is truely what happened. i had 2 months to read a book; this one was 1192 pages long and it only took my 3 weeks to read it. and with it being may, my seniortits has already set in. at first it's very confusing to follow, but once the plots thicken, the stories became very clear. this is a great book, and probably the only book i have ever enjoyed reading for school in the past 12 years. love, mystery and suspense all play a key role in a wonderfully written book. if it can keep a senior's attention one month before graduation, it must be good!!!
Rating:
Summary: Blind for God¿s Finger in One¿s Eye
Review: The Principle of Computational Equivalence (PCE), suggested by Stephen Wolfram in his book A New Kind of Science, is expression of the fundamental self-similarity of the real objects. This self-similarity leads to the discovered discrete 3D-spiral genetic code of nature, which is in every bit of the universe, as shown in Savov's theory of interaction. So we have the God's finger in the PCE and we cannot prove it with tools different from the discovered self-similar structure of reality. This structure reduces everything, including the observed diversity of nature, to self-reproducing and so self-similar finite and discrete 3D-spiral interactions (or computations if you like to use computer science terms). The PCE points that at some basic level things are essentially equivalent and it is a matter of more or less computational iterations to create more or less complex shapes (behaviors). This great finding feels like knocking on a gate toward one final revelation the discrete self-similar 3D-spiral structure of reality, implying universal equivalence (scaling) between the objects expressed in its terms. Stephen Wolfram has made a discovery gazing at his computer. He indicates the crucial importance of simplicity to account for the perplexing diversity of this world. Although this concept is not new and has some prehistory the demonstration of its power and far reaching unexplored implications create a path toward A New Kind of Science. The keen intuition of the author lays open new vistas to mathematicians and physicists. If you would like to see yourself light years behind the competition you may overlook books like Stephen Wolfram's A New Kind of Science, Yurij Baryshev and Pekka Teerikorpi - Discovery of Cosmic Fractals and Eugene Savov's Theory of Interaction the Simplest Explanation of Everything. Mathematics and physics exchange ideas on the road to a proper understanding of nature. There is much to explore and discover along not well-trodden paths.
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