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Artificial Dreams: The Quest for Non-Biological Intelligence Kindle Edition

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Length: 416 pages

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Editorial Reviews

Review

"I think all undergraduate physics majors will own a copy of this book within a year. It's that good."
--Professor Krsna Dev, Middlebury College


"Morin's writing is informal and inviting, and students will almost certainly respond easily to this style... [students] will fine the book accessible."
--J.R. Buriaga, Whitman College for Choice

"Artificial Dreams by Ekbia (information science and cognitive science, Indiana Univ.) is an interesting, entertaining book on how some dreams of artificial intelligence (AI) practitioners become valued contributions while others become only unrealizable projects. A major contribution of the book is a taxonomy and historical review of the different views of AI, which is covered in individual chapters. Highly Recommended."
--C. Tappert, Pace University, CHOICE

"...Artificial Dreams: The Quest for NonBiological Intelligence is written in a clear and accessible style that lay audiences and researchers outside of AI will enjoy reading; they will find the book very interesting in its breadth of coverage and, if they are curious about doing further reading, will find its extensive references very useful....Cognitive psychologists with interests in AI but who have not kept up with it are likely to find Ekbia's coverage and treatment very interesting..."
--Michael Palij, PsycCRITIQUES, March 11, 2009, Vol. 54, Release 10, Article 4

Book Description

This book is a critique of Artificial Intelligence (AI) from the perspective of cognitive science - it seeks to examine what we have learned about human cognition from AI successes and failures. The book's goal is to separate those "AI dreams" that either have been or could be realized from those that are constructed through discourse and are unrealizable.

Product Details

  • File Size: 4401 KB
  • Print Length: 416 pages
  • Simultaneous Device Usage: Up to 4 simultaneous devices, per publisher limits
  • Publisher: Cambridge University Press; 1 edition (April 21, 2008)
  • Publication Date: April 21, 2008
  • Sold by: Amazon Digital Services, Inc.
  • Language: English
  • ASIN: B0027FFN8K
  • Text-to-Speech: Enabled
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  • Word Wise: Not Enabled
  • Lending: Enabled
  • Enhanced Typesetting: Not Enabled
  • Amazon Best Sellers Rank: #1,394,881 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Most Helpful Customer Reviews

4 of 4 people found the following review helpful By Ayzed on January 21, 2009
Format: Hardcover Verified Purchase
Well, at least, that's what Ekbia's position seems to be. He focuses on the fine differences between "true" and "artificial" (if at all) intelligence. This book is not a technical tome and makes for relatively easy reading. However, it would help if the reader was already somewhat familiar with basic AI approaches (in which the book's appendices help). Ekbia discusses computer chess (e.g. Deep Blue), case-based reasoning (e.g. Coach), artificial commonsense (e.g. Cyc), "emotional" robots (e.g. Kismet) and a selection of other examples which provide a good overview of the different perspectives both the public and researchers have about AI accomplishments. Some of Ekbia's arguments are difficult to argue against. For example, it is true that some researchers overstate their case in terms of just how "intelligent" or significant a particular approach is. Computers, after all, work in a mechanical fashion and have no real conception about the things they are working with. In many cases, this is obvious once you look "under the hood"; but in others, it is possibly just a matter of perspective. Take chess, for example. While the brute-force approach seems to work well and is purely mechanical, we cannot overlook the significance of the heuristic evaluation functions which are equally important. These are usually specifically designed by humans. Not to mention that this combination has resulted in programs running on desktop machines that can today outplay even grandmasters. In fairness, Ekbia does not trivialize this type of "success" in AI but suggests, rightfully, that we have perhaps just found a different approach to "thinking" in chess, and chess alone. But this is how it is in AI.Read more ›
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8 of 11 people found the following review helpful By Dr. Lee D. Carlson HALL OF FAMEVINE VOICE on November 30, 2008
Format: Hardcover Verified Purchase
If one referred to program lists or algorithm steps as a "reasoning pattern" and the program itself as a "cognitive structure" the author of this book would be taken aghast, and might take this as another example of what he refers to as the "generalized Eliza effect" throughout the book. The latter refers to a program, called by its creator "Eliza" that was designed to emulate the psychotherapeutic skills of a professional psychologist. Developed in the 1960's by Joseph Weizenbaum and tested on a collection of unsuspecting "patients", it apparently was able to fool some of these into believing its advice was genuine, or expert psychological counseling. The "patients" questions were recast in such a way as to create the illusion that the program had genuine understanding of psychotherapy and could offer them therapeutic assistance. But the Eliza responses were merely canned phrases, as was revealed by the patient "patient" who took the time to question it for several minutes.

The author uses this program as a paradigm for his main case against the reality of machine intelligence, viewing the program as an excellent example of the false imputation of intelligence to a machine. He gives many other examples throughout the book, all of them being quite familiar to those readers who follow the field of artificial intelligence (AI) or who are active participants in research thereof. As a whole the book is interesting, mostly due to the detail that the author brings to the history of AI and the discussions of some of the attempts to bring about machine intelligence.
Read more ›
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Format: Paperback
This book did an excellent job at articulating and critically examining the underlying assumptions behind the major approaches to AI. It did an excellent job at explaining the motivations of each approach and the major obstacles faced by that approach. By the end of the book, the reader has a good intuitive sense of the big picture of AI, where we are and what the main challenges we face. I learned a great deal from the book and strongly recommend it to those who are interested in AI.
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