Fluid Concepts And Creative Analogies: Computer Models Of The Fundamental Mechanisms Of Thought

Fluid Concepts And Creative Analogies: Computer Models Of The Fundamental Mechanisms Of Thought

Readers of earlier works by Douglas Hofstadter will find this book a natural extension of his style and his ideas about creativity and analogy; in addition, psychologists, philosophers, and artificial-intelligence researchers will find in this elaborate web of ingenious ideas a deep and challenging new view of mind.


  • Hardcover: 528 pages
  • Publisher: Basic Books (February 8, 1995)
  • Language: English
  • ISBN-10: 0465051545
  • ISBN-13: 978-0465051540
  • Product Dimensions: 1.8 x 7.5 x 9.5 inches
  • Shipping Weight: 2.1 pounds
  • Average Customer Review: 4.4 out of 5 stars See all reviews (25 customer reviews)
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  1. Where does meaning enter the picture in artificial intelligence? How can we say that a machine possesses understanding? Where, and how, does such understanding happen? These are among the deepest and hardest questions faced by the field, which, as many skeptics claim, has not yielded much about them so far. Consider, for instance, that most current research in AI can be roughly classified over two distinct classes:
    (1) Low-level perception. The best example of this type of work comes obviously from computer vision systems. These systems, given a set of input images, usually extract some important information from this input, generating, well, other images (i.e. depth image, edge contours etc.). But this extracted information is usually on a still very low, meaningless, level, to be used by, for instance, a theorem-proving system. To make it clear to all readers what is meant by “meaning”, consider the information-processing that must occur whenever an animal, given its massive sensorial information, perceives danger. Going from a set of images and sounds to a feeling of danger involves extracting meaning from the original input, and this is not what is done by current low-level perception projects. It is almost as if these perceptual processes “delegate” the extraction of meaning to another upcoming process. To get into the meaning of a situation, low-level perceptual processes are not enough; there is a clear need for further perceptual processing.
    (2) GOFAI symbolic manipulation. This is the other side of the AI coin, dubbed by philosopher John Haugeland as GOFAI, for “good-old-fashioned artificial intelligence”, where programs usually handle (syntactically) a representation that supposedly should have been formed by a perceptual process.Read more ›

  2. This book has received some poor reviews and been unfairly compared to Hofstader’s previous book, Goedel, Escher, Bach. While both are books about cognitive science, the former is a book of philosophy — it’s written for the layperson and discusses the topic in relatively abstract terms. This book is no less interesting for the fact that it deals in concretes: it discusses the actual architecture, the design of the programs which simulate the intelligent processes described so well in GEB. Those with a background in computer programming will especially appreciate the novelty of Hofstadter’s architecture, and will perhaps be inspired to implement their own. Those without a background probably won’t have any trouble visualizing the processes for themselves. The book is written as a collection of essays, so my recommendation is: skip around. Read whatever interests you, and think about it for a while. This book is neither a narrative nor an exhaustive reference, and you won’t enjoy it if you try to read it as either.

  3. For a number of years now, I’ve followed the works of Douglas Hofstadter. I was instantly hooked
    when I first read his column Metamagical Themas, which ran in Scientific American from 1981 through 1983.
    In that column, he tackled all manner of thought provoking subjects. In the interveneing years, he
    has released some pretty meme-rich tomes, none for the faint of heart. From the far-out thought
    experiments of The Minds Eye to the Pulitzer Prize winning Godel, Escher, Bach: An Eternal Golden Braid,
    to his latest (reviewed here), Mr. Hofstadter always keeps the reader on his or her mental toes.

    Many researchers in the field of Artificial Intelligence take the approach of attempting to mimick the
    behavior of people with computer programs. On the surface, this might seem a logical direction to take, and so
    AI researchers have a tendency to go and dream up batteries of tests that aim to characterize some area
    of human behavior, then the sum up all the results and come up with the range of responses that fits cozily
    into their bell-shaped curves. Armed with what they’ve assured themselves is normal human response to
    all their scenerios, the go off and attempt to write computer programs that react the same way as John or
    Jane Doe did. Once they’ve gotten a program that generally responds like ‘most of the human subjects’ did,
    they usually beef it up by programming in more and more details about the domain of the scenerio at hand.
    A good example of this line of thought is
    Deep Blue, IBM’s massively parallel chess playing supercomputer.

    What Douglas Hofstader’s latest book points out is that this sort of thinking about artificial intelligence is
    the brute force approach.Read more ›

  4. This book is, as others have commented, different from DH’s other more entertaining books.
    It is a serious attempt to discuss the real issues and difficulties with AI research. There is a lot of quite dry material and in places it is repetitive.
    It provides terrific insight into the problem of imitating human thinking at a deep level, and I found it very rewarding. It was also very interesting to follow the threads of how he went about doing research, and what he thought of other AI research.
    His views of various flavours of AI research were very instructive and inightful I thought.
    In summary a good book, but this is not (high quality) brain candy like Godel Escher Bach etc.

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