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What Computers Still Can't Do: A Critique of Artificial Reason

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What Computers Still Can't Do: A Critique of Artificial Reason Cover

 

Synopses & Reviews

Publisher Comments:

When it was first published in 1972, Hubert Dreyfus's manifesto on the inherent inability of disembodied machines to mimic higher mental functions caused an uproar in the artificial intelligence community. The world has changed since then. Today it is clear that "good old-fashioned AI," based on the idea of using symbolic representations to produce general intelligence, is in decline (although several believers still pursue its pot of gold), and the focus of the Al community has shifted to more complex models of the mind. It has also become more common for AI researchers to seek out and study philosophy. For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field.At a time when researchers were proposing grand plans for general problem solvers and automatic translation machines, Dreyfus predicted that they would fail because their conception of mental functioning was naive, and he suggested that they would do well to acquaint themselves with modern philosophical approaches to human beings. What Computers Can't Do was widely attacked but quietly studied. Dreyfus's arguments are still provocative and focus our attention once again on what it is that makes human beings unique.Hubert L. Dreyfus, who is Professor of Philosophy at the University of California, Berkeley, is also the author of Being-in-the-World. A Commentary on Heidegger's Being and Time, Division I.

Book News Annotation:

**** Revision of What Computers Can't Do, MIT Press, 1979 (listed in BCL3).
Annotation c. Book News, Inc., Portland, OR (booknews.com)

Synopsis:

Argues that artificial intelligence based on the idea of using symbolic representations to produce general intelligence is in decline, and that the focus has shifted to more complex models of the mind. Dreyfus outlines these changes, assessing both connectionism and neural networks.

Synopsis:

For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field.

Synopsis:

For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field.

About the Author

Hubert L. Dreyfus is Professor of Philosophy at the University of California at Berkeley.

Product Details

ISBN:
9780262540674
Author:
Dreyfus, Hubert L.
Publisher:
Mit Press
Author:
Dreyfus, Hubert L.
Location:
Cambridge, Mass. :
Subject:
Reference
Subject:
Technology
Subject:
Computers and computer technology
Subject:
Reference - General
Subject:
Artificial Intelligence
Subject:
Artificial Intelligence - General
Subject:
Intelligence (AI) & Semantics
Subject:
Computers Reference-Beginning and Reference
Edition Description:
Trade paper
Series:
What Computers Still Can't Do
Series Volume:
9436
Publication Date:
19921031
Binding:
TRADE PAPER
Grade Level:
from 17
Language:
English
Illustrations:
Yes
Pages:
408
Dimensions:
7.9 x 5.3 x 1 in

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What Computers Still Can't Do: A Critique of Artificial Reason New Trade Paper
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Product details 408 pages MIT Press - English 9780262540674 Reviews:
"Synopsis" by , Argues that artificial intelligence based on the idea of using symbolic representations to produce general intelligence is in decline, and that the focus has shifted to more complex models of the mind. Dreyfus outlines these changes, assessing both connectionism and neural networks.
"Synopsis" by , For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field.
"Synopsis" by , For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field.
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