Rating: 
Summary: What about for a beginning scientist/ intellectual?
Review: I Hvae given this book 3 stars because I did not want to upset the average- I have not really read the book and I am wondering whether to purchase it or not. I can understand how people experienced in the fields that Wolfram deals with might be disappointed, but what about this book for a beginning scientist/ intellectual? Would it be fascinating for someone not very knowledgeable in complexity theory, etc? Could reviewers give their opinions on this either before or after their critiques? I'm a poor college kid and don't have a lot of time to waste on useless books.
Rating: 
Summary: Review and Reviewers
Review: Having read several reviews of the book in newspaper kind of publications and weekly newspapers who purport to write seriously, I was left in no doubt that this is a book I should read. Having in the past been disappointed by monologues written by single minded individuals though I decided to check out the reviews by scientists (1-2 stars) who actually read the book, rather than journalists who read the marketing blurb (5 start superhero - at least in UK reviews). I give it 2 stars to give it the benefit of the doubt and if I don't allocate any stars which is the honest thing to do, as I haven't read the book, I can't post these views ....Sorry, had to say this once.The reasons for the difference in the ratings I leave to you to consider, prior to purchase. But in August, when this will be in [the] bins in the US, I will buy a copy for the pretty diagrams, yes. If Mr Wiolfram wants to ship me a copy for serious review to be published in a journal, I'd also do that for him. Also, I was amazed to see it at no2 in the Amazon best Seller lists...power of marketing?
Rating:
Summary: Read the book first, BEFORE writing the review!
Review: Let me preface by saying that I have not yet read Wolfram's new book, but I am absolutely incensed that a group of complete bafoons would write such negative reviews when they obviously have not even bothered to read the book! The initial reviews came in a mere few days after the book started shipping, hardly giving anyone time to read 100 pages, let alone it's 1200+ pages. The people who have been so quick to blindly judge are committing a violation much greater than what they accuse Wolfram of.
Rating: 
Summary: Plagarism
Review: The most egregious aspect of A New Kind of Science is its lack of a bibliography, or lip service in the text, to show that Wolfram acknowledges his source material. He not only omits the references, he claims that most of the ideas were his (which they were not). Attributing the origin of previously published material to yourself is a well-known literary misdemenor--it's called plagarism. Wolfrom has insulted his previously sympathetic audience, and he owes the scientific world an apology. Nice graphics, though.
Rating:
Summary: Fails to justify its thesis
Review: Wolfram's ideas just don't pan out. Generation of patterns of one kind or other doesn't establish intelligence in the ``pseudo-random" generator. I am astonished that Wolfram would have made the claims that he has about cellular automata.
Rating:
Summary: Worth reading..but dont hurry
Review: Wolfram is a brain - there is no doubt about that once you conquer this sprawling work. You can however, get a pretty good idea of what it's about by reading some of the longer reviews on this site. There are likely a couple of hundred other books that you would be better off reading first, so decide if this is what you want to do with your reading time. What's more, while it is worth reading, dont hurry, there will be plenty of used copies available in the future.
Rating:
Summary: Not new, not science, or not Wolfram
Review: Of course I didn't read *everything* in this enormous
book, but 100% of the sample passages read so far
can be described by the title of the review. For example,
the idea that the universe may be run by a simple cellular
automaton is not new (I heard it from Edward Fredkin 15 years
ago), and the Principle of Computational Equivalence is
not science, since it is stated so vaguely it can never
be disproved. The one *very nice* new scientific result
found in the book so far, that the rule 110 is computationally
universal, is not due to Wolfram, but to his young
employee Matthew Cook, who does receive some acknowledgment
in the small print in the back of the book, but who was prevented
to publish his work by Wolfram's lawyers for years, while
the Master was finishing his Book. As a review of ideas close to Wolfram's heart, this
could be an interesting book to read, but it suffers
terribly from repetitious self-congratulations and
high-flying but vague pronounciations. A good editor
should have made the book about 300 pages long, then
I would have probably recommended it. A scientist
who works in isolation needs a high degree of self-criticism
to succeed, and this is exactly what Wolfram sorely lacks.
Rating:
Summary: nothing new
Review: I don't see how this book is revolutionary. He says that models based on simple programs operating on discrete elements can do a much better job of capturing the real behavior of the universe than mathematical equations. But surely everyone knows that right? That's why we have finite element analysis, computational fluid dynamics, etc. The math is still the foundation, and is useful for describing simple cases exactly, but to model the universe effectively in all its complexity you often need a computer. In Chapter 8, he shows a simple cellular automaton that models crystal growth. He says that his model is superior to standard models that are based on traditional mathematical equations because it does a much better job of capturing the intricate structure of real crystals. I find it hard to believe that he is the first person to come up with the idea of modelling crystal growth using a computer, and even if he is, I don't see that as particularly groundbreaking. His cellular automata do an OK job of modelling one particular type of snowflake growth, for example, but that's because he has tuned the rules to get
the expected result. His automaton does not cover other types of snowflakes though, and they do not give much insight into how and why real snowflakes grow. Also in that chapter he presents a (crude, IMHO) fluid dynamics simulation using cellular automata and shows how turbulent flow occurs in his simulation. No surprise there, since people have been running fluid dynamics simulations for some time now to study turbulent flow. In the notes he seems to indicate that his simulation is superior to existing fluid dynamics simulations because existing simulations are discretized, ignoring the fact that his simulation is discrete as well. Then he shows how seemingly complex patterns in biology, like the structure of leaves and trees, can be reproduced using simple rules. To anyone who has read a book on fractals this will not be new information. The interesting question is, why do those simple rules work so well for describing nature? What is it about leaves that make them grow in that pattern? He didn't spend much time on that. Later he comes up with a cellular automaton with reversible rules that does not obey the second law of thermodynamics. He uses this to show that not all systems in nature (notably biological ones) obey the second law. Well that's fine with me, as long as all thermodynamic systems obey it. It's a strange book but still an interesting one, as a review of a lot of info about science and fractals and cellular automata and how they interrelate, complete with lots of pretty pictures, but I don't really see how it's groundbreaking. He makes some radical assertions (like saying that the universe may be a big cellular automaton) but I don't find them particularly compelling. I believe that the universe is some large mechanism with fairly simple rules that result in complex behavior (and I thought everyone agreed on this point; that's the goal of physics, to find the fundamental equations and them use them to model reality, right?) but I think mathematics are a much better way of expressing the rules, and existing computational models are a much better way of applying them.
Rating: 
Summary: Same old science put another way?
Review: The best bits are a cellular automata model of physics and a demonstration that a cellular automaton (rule 110) operates as a universal computer. Can the same old science put another way, impressive as it is, make fundamentally different predictions?
Rating:
Summary: A New Kind of Ego
Review: Wolfram does a great deservice for science in his new book. Not for scientists themselves, who can easily find out that more than half the overblown statements in the book are well known old science ideas. But a deservice for the non-scientific reader, who may actually be infused by the mantra that science is just purely speculation, without actually experimentation or show-and-tell. I can speculate as much as I want about any single model. In fact, if a model is Turing Complete, as a CA is well-known to be, any speculation can always be verified by my model! But science is about proving with experiments one's theories. Or at least showing some interesting predictions that can be made based on chosing the proposed model. But neither of them are present in the book. In fact, in the beginning of the book itself Wolfram warns the reader that scientists are non-believers and will try to destroy his idea. So he is now in a comfortable place. He has a Turing machine, and can therefore adjust the model to explaining anything. He claims due to the nature of the model he can predict little (interesting, isn't that the decidability problem?), and that
all scientists will atack him because what he believes is true.
This is circular reasoning. Fractals have shown us that simplicity generates complexity. Even caos models that can be run on hand calculators show that. Or a double pendulum. It is a very well-known result (shown in the 50s/60s) that the game of life is Turing complete (ie. can compute any function given an appropriate program). CA are also Turing complete, so where is the news? I can compute anything. Writing a CA that generates prime numbers amounts to finding the right "program"... What is disappointing is that most claims are not based on any theory or verification. Let us say that he cannot really run lab experiments to check his ideas. Or even that is too early to predict any new pheonomenon based on his ideas. Well, the least he could do is to use the powerful tools of Complexity Theory (especially Kolmogorov complexity) to measure the complexity of the patterns generated by a CA. Or to at least have some results veryfying the behavior of his set of axioms ... Ok, provide with
some useful examples on how to apply CA to important problems in bioscience, engineering, etc ... Not toy computing (!). But what he cannot do is to use ideas from other people without giving them proper credit (ok, he puts a tiny side note) or just assume that arrogance, young academic brilliance, or money can justify science. When he claims that all the major revolutions happened like this, I would suggest him to take a look at the first writings of Newton, Gauss, Einstein, Von Neumman, etc ... His predecessors had ideas that revolutionized science, but they always provided results for the scrutiny of other scientists as well. Moreover, their models and ideas could be translated to verifiable statements or allowed new and interesting predictions. Science is about communication as much as it is about ideas. If one cannot convince other people rationally of the validity of the ideas, and also verify such ideas through experiments (the true hallmark of a scientific theory is checking predictions against experiments) then he is not scientific. He is just creating a cult. Not even a religion, because that assumes that God is not oneself. And Wolfram is convinced he is some kind of
superhero. Well, I finally understand the title of the book. A new kind of science is about follow-the-leader and do not question, have faith, because my ego is the answer you have been waiting (not even 42)...
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