Rating: 
Summary: Reveals how the digital world will evolve
Review: How are basic biological discoveries helping fuel the next revolution in computers? Digital Biology reveals how the digital world will evolve, based on biological laws. From advances in medical care as systems change in response to health needs to increased repair and replacement abilities, Digital Biology considers the future of digital biology with a focus on how computers can evolve solutions, rather than designing them from scratch.
Rating: 
Summary: Maybe a good layman introduction to the field.
Review: I agree with other reviewers of this book who say that it doesn't deal with any of its topics deeply (as the author says in the book, it's just a summary of conversations he had with the scientists he gives all of about half a page to each, and material he found on the Internet) and that the writing is just a shade above mediocre. The author isn't a bad writer, necessarily, he's just very inconsistent. If he stuck with facts instead of pretending to be a fiction or magazine writer, he'd do well. Also, if he stuck with a British voice and didn't cater to Americans, that would be a good move. If you want to tailor your writing to an American audience, fine--do that and don't make a point of it. Otherwise, stick with your native tendencies, as it tends to make the book more readable.This book is just ok. A few parts were downright painful, but mainly just because of the writing. The content was never painful, just boring in many places. For anybody with a background in complex adaptive systems, current computer science research, or any of the in vogue areas like network theory or chaos, this book can easily be put aside for others. If you're a layperson just looking for an introduction to the research being done connecting computers and biology, this book might be good. For serious readers, there are better books like 'At Home in the Universe' by Stuart Kauffman (excellent) and 'Complexity' by Mitchell Waldrop (also excellent). Those books are much older, but much more thought-provoking and well-written. They may not cover some of the newest research, but this book covers everything with such lack of depth you won't really get anything more out of reading it. In short: not a bad book, but could have been much better in writing and content, and serious readers would do better elsewhere.
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Summary: Fantastic duet of computer science and biology
Review: I thoroughly enjoyed this book. Since reading it, I have refocused most of my spare time into studying artificial life, microcosms, complexity, bottom-up organization, etc...
If you have a computer science or programming background you will find the first chapter boring. Everything else is golden! I previously read Deborah Gordon's book about the social behavior of ants. And, I'm currently reading "Emergence" (Stephen Johnson). Next on the list is "Turtles, Termites and Traffic Jams" (Resnick).
Rating:
Summary: A fascinating read
Review: I've got to say that I thought this was a wonderful book. An absolutely fascinating overview of a new and developing field of science. Nicely laid out, elegantly written, very "easy style", lots of detailed material is covered for each of the areas the author touches on, so you get depth aswell as the overview. The author presents some very interesting perspectives on existing ideas about biology and machines. Useful notes at the end and the further reading section is good. Rather than be another "here is the future" book by yet another science journalist, this is a book with its feet very much in the present and written by a scientist who is active in the field (rather than a journalist). Do not be alarmed! This guy writes well. I'm not going to say it's a one- sitting read (because that would just make me too much of a techno-nerd), however it's definitely a page-turner. In terms of books available, I think that there is presently only one other non text-book that takes an overview of this field (Moshe Sipper - Machine Nature), though I'm sure there are gonna be a lot more before too long . If you want 2 books - buy both. If you just want the one - I thought Peter Bentley's had detail aswell as breadth whereas Moshe Sippers, whilst still a very good book, stayed more at an overview level.
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Summary: An excellent introductory text.
Review: It is difficult to read this book and not catch the bug of biologically inspired computing. It is fascinating, inspiring and comprehensive (even my dad read it). It clearly makes the point that by understanding the way nature solves its problems we have discovered a whole new class of computation. The book takes you smoothly through the basic domains of biologically inspired computing. Starting with the definition of a digital universe (that makes you think twice about our own), it introduces evolutionary computation, neural networks, ant colonies, artificial immune systems and other fascinating computational metaphors. It explains their foundations and underlying theories and describes their practical applications. My only complaint: there are no references to scientific papers. The motivated reader will have to spent some time searching the web for further reading, other than the books included in the bibliography.
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Summary: good book, not too dry and scientific.
Review: the author even managed to make me laugh a couple times. this book is full of interesting points about evolution and biology as well as computers. this is a good book to read if you like robots and things. first read hans moravec's "mind children" then move on to this, and you have a pretty solid understanding of how technology will influence our beautiful future.
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Summary: Very Interesting!
Review: The basic premise of "Digital Biology" is that biological systems (brains, plants, insects, etc) were "designed" in a certain way because there was an inherent advantage to this design. Therefore, if we can understand the principles behind the design, we can take these techniques and use them in our software and hardware.
Many things in nature seem as if they have no reason behind them - however, as the book illustrates, there are certainly valid, good reasons. An example would be neural networks: since our brain uses this instead of hard coded rules and programming, it is much more flexible. It can learn by trial an error the "best" approach, something traditional algorithms cannot do as efficiently. By taking this mechanism we can create very sophisticated - almost intelligent - programs and robots.
There are numerous chapters in "Digital Biology", each dedicated to a specific subject. Each chapter begins by explaining how a specific biology mechanism works (i.e., the chapter on "immune systems" gives a short tutorial on how the body's immune system works). Then, different ways that similar mechanisms are used in artificial applications are demonstrated.
Among the most interesting chapters: "Evolution", this chapter elaborates on the principles of Evolution and how they can be used in Computation. What are Evolutionary Algorithms ? What are Genetic Algorithms? What is Genetic Programming? Evolvable Hardware, and more. "Brains" - this chapter was FASCINATING. It started with a short introduction of how we believe brains work, and how these principles can be a foundation for AI and ALIFE: by using Neural Networks. "Insects"- Insects are interesting because in many ways a group of insects acts as one larger organism. Sometimes many simple organisms can form one fairly intelligent "Creature". There are ways to use these techniques in computation as well, as this chapter shows. (Swarm Intelligence, Boids, etc)
Overall this is a very interesting book. It covers a lot of subjects, yet does NOT go too deeply into any of those - I don't think that was the purpose of the author. My main criticism is the way the book was written - some chapters are very raw, the examples chosen could've been better. (I think my favorite one was where the immune system is being compared to the music industry, and antibodies are compared to boy bands. Probably the strangest analogy I have read in my life). I also think that there was too much emphasis on real biology, especially since in many subjects there was no analogy in digital biology. Nonetheless, if the idea of using biological mechanisms in software or hardware appeals to you, this should serve as a fascinating introduction.
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Summary: Computers / Life and Life / Computers
Review: There are so many "revolutionary" developments in science, and especially in computer science, that it is hard to keep track of them all, and hard feel that they can all be as revolutionary as they claim to be. You have to suspect, though, that if Peter J. Bentley is claiming a revolution, then something wonderful is happening; he is a scientist in the very field of computers, not a reporter, and so his book _Digital Biology: How Nature is Transforming Our Technology and Our Lives_ (Simon & Schuster) is that excellent form of popular science writing, enthusiastic witnessing from an expert in the field. It is obvious that he loves his work, and that it has far-ranging implications, but it is even better that he can communicate the enthusiasm and let the reader share in it.
Digital biology represents a remarkable two way street. Natural processes such as evolution or ant colony behavior can be modeled within a computer to build stronger problem-solving tools. In turn, computer programs can illuminate aspects of behavior of systems large and small in nature, showing just how physics, genes, and evolution have accomplished the complexities we see around us. The best part of Bentley's book is that he has plenty of examples of how these ideas are already at work. Consider what seems to be an inescapable metaphor for brains and for computers, the ant colony. Ants are themselves, like all other insects, tiny robots able to take in small degrees of data and perform small feats of manipulation. One ant is a very limited creature indeed. (Are you getting the analogy? One neuron, too, is practically useless as is one flip-flop gate.) But a mass of ants in a colony starts to show real intelligence. Put a little food out a distance from the colony, and by laying pheromone trails, and following the stronger trails, the huge numbers of ants will in effect calculate the shortest, most efficient way of getting back and forth to it. Making digitally simulated "ants" and electronic "pheromone trails" is already solving difficult problems; "Ant Colony Optimization" is already a respected field in computer science. It has been used to solve the otherwise almost intractable classic Traveling Salesman Problem: A salesman has to get to many different cities on his rounds; what is the most efficient route? Solving this problem took too long for even the fastest of ordinary computers, but letting the digital ants go at it works. It isn't just a matter of solving puzzles, either; such optimization programs are already being applied to communication network routing and electronic circuit design. In some ways this book is a primer on evolution of different types, and while some fundamentalists continue to make religious objections to evolution in nature, it is obvious from the examples Bentley gives that evolution really does happen in many ways separate from our world of DNA creatures. Bentley draws from examples in many disciplines, and is interested in finding commonalities between them. He demonstrates that from DNA to ants to brains to growth to programming code to evolution to universes, complexity is generated by interactions of similar things, controlled by feedback, and subject to change from the outside. This pattern is more important than the stuff the system is made of. This has not quite the clear universal ring of a Newtonian law, perhaps, but it is certainly an illustrative pattern which is played at all sorts of levels. To Bentley, the pattern is so much more important that the stuff which shows it that he sees no basic difference between biological life and life within a computer. His quickly paced, entertaining book is a good introduction to one of the new ways computers are changing how we look at everything.
Rating: 
Summary: Disappointing
Review: This book did not deliver what I was expecting. I thought there would be detailed examples of the use of biological concepts in computing. Unfortunately I was very wrong. There are some examples, however they are very vague with little or no detail. Frequently the author asserts a technique has too many applications to go into in any detail without boring the reader. Next he proceeds to rattle off a dozen vague applications such as scheduling, optimization, etc. without giving enough information about the application to be useful. The center of the book contains a number of pictures that are the result of one technique or another. Unfortunately he does not elaborate on how any of them were created. I enjoyed seeing the coffee table his computer designed. Unfortunately the only explaination he gave on how the program worked was something to the effect that it was complicated. A bit more detail or perhaps even code would have been much better. Beyond my perceived technical shortcomings, the author's style did not appeal to me. For example he wrote a fairly detailed account of what it might be like (as though a virus could think) to be a virus invading a host. Perhaps this was an attempt to engage the readers' imaginations. If so, the effect was wasted on this reader. Two stars seemed right as there are worse books in the world. However I doubt most people would gain much from reading it.
Rating:
Summary: Too basic and not well written
Review: This book was as primer on how biological structures are being implemented into computer software. The biology sections were generally weak - for example, there are no explanatory diagrams, which I think would have been very helpful to the reader, at least if biology textbooks are trustworthy in their pedagogical methods. Admittedly, there were a few color plates stuck in the middle of the book, but these were more of the gee-whiz variety rather than informative support for the prose. Also Bentley does a lot of name dropping, but does little to specifically outline the projects of those he mentions, sometimes giving merely a paragraph to researchers who are apparently doing "cutting-edge" work in digital biology. Finally, the writing style is inconsistent. Sometimes Bentley writes as if he's a researcher, sometimes as if he's a magazine writer, sometimes as if he's playing short-story fiction writer. This was very distracting. I think the audience that would find this book useful are people who are starting at ground zero in their investigations into computer modeling / implementation of biological structures into computer software. Those with more advanced interests are advised to look elsewhere (cf. Steven Johnson's book on Emergence).
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