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37 of 39 people found the following review helpful:
5.0 out of 5 stars
Computers a la Feynman, November 26, 2000
This reference is derived from Feynman's lectures at Caltech between 1983-1986 for the course 'Potentialities and Limitations of Computing Machines'. This small volume introduces computers as a file clerk performing his tasks, moves on to show how the 'file clerk' can be built out of simple gates, how the gates can be built out actual transistors, discusses essential issues in computation theory such as computability and Turing machines, and then discusses essential issues in information theory such as data compression. The physics of computing from a thermodynamics context is then considered. If the general reader ignores the gas equations, this chapter is fairly easy to read and enlightening. The next chapter continues with a discussion of quantum mechanical computers. The final chapter discusses how real transistors function at the atomic level and fabrication techniques for real integrated circuits. Lectures given by invited experts on computer science topics such as vision, robots, expert systems, etc, are not included. Although this reference does not discuss alternative architectures for computation, such as the ones found in the brains of animals, this reference is ideal to introduce the motivated general reader to the concept of computation and the techniques used in commercial computers.
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20 of 20 people found the following review helpful:
5.0 out of 5 stars
I like this book, November 9, 2004
This review is from: Feynman Lectures On Computation (Paperback)
Yes, I think you can teach the theory of computation from this book. And you can learn it from this book. Some of the material isn't all that recent, but much of it doesn't need to be.
35 years ago, if one were teaching a course on the theory of computation, I'd have recommended Minsky's book (it came out in 1967). That was a great text. Nowadays, there are numerous choices. But one could still use books that originally came out well before Feynman's notes, such as Lewis & Papadimitriou or Hopcroft, Motwani, and Ullman.
The question boils down to the quality of what is in the book, as well as what material it has that other books do not, and what material it is missing that most other texts have.
This book is quite readable and preserves much of Feynman's teaching style. So let's look at what it is missing. First, it doesn't talk much about real neurons. Of course, even Minsky doesn't dwell much on that, and other computation books avoid that topic too. But now, there's a more serious omission. Feynman spends something like two pages on grammars! If you were using Lewis and Papadimitriou (first edition) there would be a chapter of over 70 pages on context-free languages alone. As a teacher or a student, would you really want to miss all that?
No, as a student, you would have to read up on all that material elsewhere. And as a teacher, you would have to use another book or write your own notes. That material is too much a part of most required curricula.
But that doesn't take away from the value of the book when it comes to the rest of the material. And the final four chapters, which discuss coding and information theory, reversible computation and the thermodynamics of computing, quantum mechanical computers, and some physical aspects of computation, are all useful material that you often won't see in other computation texts.
As a student, I'd read the book. As a teacher, I'd recommend it to my students. But as either, I wouldn't expect to use it as the only textbook.
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11 of 11 people found the following review helpful:
4.0 out of 5 stars
Mostly brilliant, May 9, 2006
Of course, 'brilliant' is what you'd expect from Feynman. These lectures, originally presented in 1983-6, capture a number of the most fundamental, esoteric concepts in computing. Since Feynman is doing the explaining, however, the ideas come across clear and strong.
Chapter 3, on the basic theory of computation, introduces not only the Turing machine, but also the basic idea of what things can and can not possibly be computed and why. He also explains the "universal" machine, and the meaning of universality that mathematically steps up from any one machine to all machines. The next chapters discuss coding theory. That has body of knowledge has since become pervasive in our every-day lives, even if it's never visible. After that two chapters present the physical limits to computation, and how computation can approach those limits using quantum mechanics.
This includes the superfically odd idea of reversible computation. I say odd because, for example, knowing that two numbers add up to six doesn't tell you whether the two were five and one, zero and six, or some other combination. You normally can't run addition backwards from the sum to the summands, so standard addition is said to be irreversible. Reversibility gives amazing properties to a system, however, and things like the Toffoli gates show how it can be implemented.
The only disappointments in this book come from the very beginning and very end. The beginning describes what a computer is, as if the reader had never heard of computers before. I guess that basic level is still needed, but is no longer needed at the college level. The very end describes silicon technology, as it was known in the early 1980s. Despite some fascinating bits of device physics and some heavy editing, that discussion has aged with the rapidity you'd expect from Moore's law. And in a few places, the older discussions of biological systems have aged poorly.
Still, his explorations of the physical limits to computation as just as fresh and salient as ever. I recommend this to anyone with a beginner's interest in the foundations of coding, computing, and quantum computation.
//wiredweird
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