Rating: 
Summary: Dissapointed
Review: I couldn't wait to crack this book. I am entirely pre-disposed to the idea that modern mathematics does not capture the elegance of nature and needs to be redone. But the more I read this book, the more disappointed I became. In my opinion, the insights in it are not fundamentally much stronger than insights that can be gained by reading a large variety of the math and physics books that can be bought off the shelf [...], and then interjecting a dose of one's own imagination and creativity in the middle. Imagine, for example, starting with the Dover book by Nelson and Fuller, the Mathematics of Classical and Quantum Physics, re-writing all the formulas that are based on gaussian assumptions of normal and orthonormal functions and replace those with integrated formulas that can generate in 3-D or n-dimensional space non-linear randomness, self-similar repeating functions and the like. Sort of Nelson & Fuller meet Feigenbaum and Deutsch. Maybe that's a stupid idea, but hey, I only thought about it for 18 seconds, not 18 years, as in the case of Dr. Wolfram.At least Einstein was wise enough to "stand on the shoulders of giants" as it is said. In Dr. Wolfram's case it is not a matter of giving credit to the right people, it seems that he is actually blind to the fact that other giants actually exist in the world besides himself. However powerful his mind may be, Dr. Wolfram would have served science better by trying to build on, and integrate the work of other giants. At least that's what I (humbly) think.
Rating: 
Summary: Sory, ... I'm late!
Review: just read John Dunbar's comments! I totally agree with him. Besides that, I would like to say that many biologists will be very upset ...their problem! Still, the problem of conciousness is not explained. There are sytems whose computation is irreducible but show no conciousness!! Anyway, though he is not nice ...the book is!.
Rating:
Summary: The Great Pretender
Review: Though Wolfram is a key character in science and software development (even if I did not know that his contributions to particle physics and cosmology are considered "lasting"), and cellular automata are an interesting subject, if I consider that I have been waiting this book for so long a time (I preordered it one year and half ago), I have to recognize that it is not worth the long wait and its cost. To be honest, I do not realize which or where the new kind of science is. I do not understand whether it represents either the work of a genius (because Wolfram has really been like that) gone out of his head or a clever, and profitable, publishing operation of the CEO of a successful company, producing one of the best scientific sw products in the world. But the author's authority by itself does not turn a common book into an excellent one. The result is a slightly interesting, and heavily boring, book, with an accurate, and overvalued, editorial setting: a paperback and lighter edition would have been more suitable to a collection of Wolfram's results; you must have a very strong interest in cellular automata to really appreciate this book, and enough time and will to read its flat, inflated and repetitive style.
Rating: 
Summary: useless rehash
Review: wolfram is perhaps the most egocentric scientist ever. he either ignores the achievements of others or co-opts them by remarking that they didn't see the significance of their findings. his main point seems to be that certain cellular automata can reproduce any phenomenon in the universe. this is not a novel or unique. indeed, one of the ideas behind quantum computation is that a universal turing machine can simulate any physical process in the universe. the difference between 'reproducing' in wolfram's sense and 'simulation' in this sense is difficult to find. if you want to understand the new ideas behind universal computation read chuang and neilsen's book on quantum computation. if you want to understand complexity theory in the sense that it's used in this book pick up any book on the theory of computation or computational complexity -- papadimitriou's book 'computational complexity' for example. if you want a layman's view of the applicability of theoretical computer science to the real world (economics, politics, the internet, biology) read barabasi's 'linked'
Rating:
Summary: Boring Rehash of OLD Concept
Review: this one goes in the return bin, not something I do very often. Highly disappointed...
Rating:
Summary: Wolfram ignores algorithm complexity; builds O(N^2) engine
Review: In this review I will skip the topics of entropy, mathematical proof, leopard spots and quarks, in an effort to focus on what I see as the main contribution of the book: the proof of universality of rule 110 and the implications this has. One of the main statements in the book is the following: There is something called "the princple of computational equivalence"; It says that if we have two methods of computation that are both equivalent to a Turing machine, and one method is simpler than the other, we should study the simpler one and ignore the more complex one because they are equivalent in all other respects (what "simpler" means is not rigorously defined). Wolfram then clearly states many times that because of the universality of rule 110, literally no other computation method is more efficient, i.e. you can't outrun or short-cut a computation that is performed using rule 110. What Wolfram completely ignores is something called computational complexity, the study of which is central to computer science. His principle of computational equivalence basically states that an O(1) algorithm is computationally equivalent to an O(N^4) algorithm. So now we can describe the problem with the rule 110. It lies in the fact that this rule requires a lot of space to compute anything. On each iteration, the working space is increased by two cells. These cells take part in all subsequent iterations. Thus, the total number of operations needed to make N iterations is proportional to the square of N: O(N^2). This makes rule 110 a very inefficient computer in time and space, although it is certainly compact in description. Any algorithm whose running time grows as a square of the input size is extremely limited, which is a widely known fact. For example, say we implement Photoshop using rule 110. If it takes 1 second to save a 10x10 image as a JPEG file, then it will spend 3 years working on a 1000x1000 image. This example uses an extremely favorable assumption that a problem of size N can be encoded in O(N) bits using rule 110. So my question is: who needs a computer that takes any linear algorithm and makes it quadratic?
Rating:
Summary: Close, but no cigar.
Review: In science, we define the term Computational Equivalence as follows: "Computational equivalence is defined to be that the time taken and the effort required to draw an inference from two different representations is the same." This is a good and practical one. Mr. Wolfram defines The Principle of Computational Equivalence as follows: "Whenever behavior is observed that is not obviously simple, it can be thought of as corresponding to a computation of equivalent sophistication (Wolfram 2002, p. 5)." This is merely a fashion of speculation, but not about scientific methodology. And this definition is the central theme of all that opus, which took Mr. Wolfram 15 years. The principle has been taken by scientists and philosophers for hundreds of years. It often failed to describe the "principle" of a system. A good example is that Deep Blue reveals the mind of a chess player, and the machine is just like a human's brain. Some people even claimed that this kind of machine is threatening!! Obviously, this is wrong. The machine is far more stupid than Kasparov. No matter how far that machine evolves, it cannot help understand how the mind of a chess player works. Deep Blue merely looks up and compares lots of patterns in the database, i.e., searching by brute force. The whole thing is called "simulation." Simulation is the way to represent a system when we don't really know how it works. The purpose is usually art, but not science. Another sort of simulation is that when we have already understood the principle of a system, we can write a program and demonstrate the process. And we don't need to experience the same process, such as earthquake. In that sense, simulation is meaningful and useful. Another example is that the L-system and Fractal Geometry could make a computer draw beautiful plants on the screen. However, the system doesn't explain how a tree grows. The process of growth of tree is far more complicated than the simple algorithm. It involves the effect of sunlight, and fertilizer contained in the soil, etc. Think about starting off some simple rules, and feed them into a computer, so that the computer would draw lots of beautiful patterns which are similar to some physical systems. And we conclude that the systems work just like the program.... Well.. this is called dogmatism. Another problem with this book is that we cannot find the bibliography. We can list tens of books in that section, if not hundreds. I would keep this book in my shelf if someday Mr. Wolfram could do that for curious and serious thinkers like me. If you are interested in research in Japan, you would find that Japanese researchers like to do that -- pretend that they discovered the whole theory, just reinvent those jargons. It's very usual in Japan's circles of science. A Caltech-trained scientist should not do that. Thanks in advance! "Good artists copy, great artists steal." -- Picaso.
Rating:
Summary: Misses the point of it all
Review: It is not about how long your program is or what it is about, existence and meaning don't really exits outside of your head, but the relationship of this to that and this again. This is ugly mathematics or physics or whatever it is. It is a grubby view from the underbelly of God. We pray for him to open his Heart and see. Like most in the cellular field he is just boring. Interesting printing style and pretty pictures. And we are compelled to read it just as we use his buggie Mathematica. This book is a love hate relationship rolled into a paper printing. Maybe on a more generous day this is a 2+. Or not.
Rating:
Summary: Outstanding book on Cellular Automata, Controversial
Review: This is a stunning book in its physical properties. It's huge, well illustrated, and easy to read. On the negative side, it's too huge to read on an airplane, it's ponderous in reading, it makes my left wrist hurt from holding it up when I read. But overall I highly recommend it for anyone wanting to read how cellular automata can apply to fields showing complexity not solved with tradional mathematical approaches (just about all). I'm appalled by some of the negative reviews of this book here on Amazon. I think alot of these ad hominem attacks are due to the author's over hyping the book before releasing it, and his general ego-centric personality. But, the reviews should be on the book, not the author's personality. I found the book to be very easy to read. Those that say he needed an editor probably did not read the book... particularly the beginning where he describes why he took an informal approach to his writing. Those that claim he grabs credit for Cellular Automata also missed this beginning where he credits those who came before him. Now, I will admit that Wolfram doesn't hesitate to overuse the "I" word, but again... he tells you upfront why he does so. I found it to be only mildly irritating. Scientists are often egotistical, heck... look at Linus Pauling. In this regard I think we could say that Wolfram is egotistical, but in no way showing hubris. I think this is a monumental book, and may defy categorization. The purpose of this book was to show how Cellular Automata are at the base of many things complex and currently beyond description or understanding. To do this he describes Cellular Automata in enough detail so that everyone can understand it, and the experts could not say that something was missed. This is why the book is ponderously slow. I found myself jumping ahead to read his conclusions and theories. I will concur with some other reviewers that it is more computation than theory. I wish the book had been reduced down to 1/3 of the size and more theory and consequences given. However, that would probably defeat Wolfram's long term goals with the book. Again, he describes why he structures the book the way he did in the first part of the book. I'm very pleased with my purchase of this book and recommend it to others that have an interest in mathematics. I particularly liked his discussion of biology and Cellular Automata, and I agree with him that it may offer a better explanatory model than natural selection in evolution. John Dunbar
Sugar Land, TX
Rating:
Summary: a new kind of science? yes. A good kind of science? no!.
Review: The only thing I learned was to be wary of the media that hypes up non-events. So what if Wolfram is a genious or an ex-child prodigy. He doesnt have anything interesting to say. He displays interesting patterns with similarities to natural patterns. Is there a connection? How? There is also a tendency to not credit others who have related or competing theories in complexity. It sounds like he merely selling his ideas like one sells a commercial product. I hope this is not how science is done in this century.
| 
