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The Quest for Artificial Intelligence
Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today’s AI engineers. AI is becoming more and more a part of everyone’s life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book’s many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.
580 pages, Paperback
Published October 30, 2009
57 people are currently reading
737 people want to read
About the author
Nils J. Nilsson
30 books15 followersNils J. Nilsson is Kumagai Professor of Engineering, Emeritus, in the Department of Computer Science at Stanford University. He is the author of The Quest for Artificial Intelligence: A History of Ideas and Achievements and other books. He lives in Oregon.
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Displaying 1 - 13 of 13 reviews
August 21, 2018
A sweet informal history of AI research from a Stanford doyen. In places it is actually oral history -
Like any history, the history of computing is full of little myths - e.g. that Lovelace was the first programmer, that von Neumann originated stored-program memory, that ENIAC was the first true computer, that hardware and software is a clean and natural division in kind... Nilsson calmly lets out the air of these and more.
[Free here]
...Jack was the Director of DARPA from 1987 to 1989 and presided over some cutbacks in AI research (including the cancellation of one of my own research projects)
Like any history, the history of computing is full of little myths - e.g. that Lovelace was the first programmer, that von Neumann originated stored-program memory, that ENIAC was the first true computer, that hardware and software is a clean and natural division in kind... Nilsson calmly lets out the air of these and more.
[Free here]
February 6, 2016
Love love love this book!
I got an interest in AI from reading Kevin Warwick's excellent book "Artifical Intelligence- The Basics" and this book highlights the history of the movement and builds from there. If you dig programming, cognitive science and philosophy then this book could be the book for you.
It's so easy to read! There's also some humorous anecdotes. For example, the US in the 80's was terrified of a much publicized Japanese push into AI and invested heavily in AI systems for its army, navy and airforce. The army project was a self driving truck which worked ok to detect the road, provided it was summer and there was a stable terrain. However in autumn when the sun was lower and there were leaves on the road, the truck's cameras often meant it went off-road by accident. Not great for the combat field. The navy project was for the most efficient deployment of ships in the Pacific fleet and cut decision making from minutes to hours. The US admirals stated while this was an improvement, in practice it took days for the ships to travel and in case, they were not about to take early retirement anytime soon!
So AI has met with many set-backs, but many of the processes that have been developed to overcome them, such as Bayesian networks, are outlined here in a relatively straightforward manner for a university grad to understand. There's info on the funding politics behind AI and why AI is so different to human intelligence i.e. Deep Blue beating Kasparov at chess by brute force rather than "intelligence". And even if you are not involved in the AI field yourself, it's often by thinking about AI problems that we learn more about how our own brains work.
I got an interest in AI from reading Kevin Warwick's excellent book "Artifical Intelligence- The Basics" and this book highlights the history of the movement and builds from there. If you dig programming, cognitive science and philosophy then this book could be the book for you.
It's so easy to read! There's also some humorous anecdotes. For example, the US in the 80's was terrified of a much publicized Japanese push into AI and invested heavily in AI systems for its army, navy and airforce. The army project was a self driving truck which worked ok to detect the road, provided it was summer and there was a stable terrain. However in autumn when the sun was lower and there were leaves on the road, the truck's cameras often meant it went off-road by accident. Not great for the combat field. The navy project was for the most efficient deployment of ships in the Pacific fleet and cut decision making from minutes to hours. The US admirals stated while this was an improvement, in practice it took days for the ships to travel and in case, they were not about to take early retirement anytime soon!
So AI has met with many set-backs, but many of the processes that have been developed to overcome them, such as Bayesian networks, are outlined here in a relatively straightforward manner for a university grad to understand. There's info on the funding politics behind AI and why AI is so different to human intelligence i.e. Deep Blue beating Kasparov at chess by brute force rather than "intelligence". And even if you are not involved in the AI field yourself, it's often by thinking about AI problems that we learn more about how our own brains work.
January 31, 2015
Excellent introduction to the history of artificial intelligence.
I figure as an AI practitioner I ought to know the history of my field, so I picked up this book last month.
I found this useful in understanding the long-term historical trends of AI, and also in collecting general paper references for AI.
(I have a nice reading list with books and papers for understanding more deeply now!)
I figure as an AI practitioner I ought to know the history of my field, so I picked up this book last month.
I found this useful in understanding the long-term historical trends of AI, and also in collecting general paper references for AI.
(I have a nice reading list with books and papers for understanding more deeply now!)
May 21, 2020
and the quest continues ..
July 16, 2018
The best book I have come across on the history of artificial intelligence. Tells a reasonably coherent story of AI without getting lost in biographical detail, i.e. it sticks to the ideas where possible. I'm looking forward to being able to re-read this once I've learned more about the subject, e.g. the Russell and Norvig textbook (which is referenced constantly throughout).
Not much I can fault it for except with the pace of the field being so fast it urgently needs a 10-year anniversary update to take account of the years 2009-2019. Also it's weak on the implications of AI and AI safety, but to be fair that's not the focus of the book. No Bostrom, but you do get Hanson (as the final citation, no less).
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(Guide to my rating system)
5☆ - A classic. Influential on a 50-year scale and/or something which I have very strong personal feelings for.
4☆ - A great book. Influential on a 10-year scale and/or something which I really enjoyed reading.
3☆ - A good book. Influential on a 1-year scale and/or something which I liked reading.
2☆ - A not-so-good book. Possibly not worth the time to read and/or something which I disliked reading.
1☆ - A near-useless book. Probably not worth the time to read and/or something which I really disliked reading.
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Not much I can fault it for except with the pace of the field being so fast it urgently needs a 10-year anniversary update to take account of the years 2009-2019. Also it's weak on the implications of AI and AI safety, but to be fair that's not the focus of the book. No Bostrom, but you do get Hanson (as the final citation, no less).
---
(Guide to my rating system)
5☆ - A classic. Influential on a 50-year scale and/or something which I have very strong personal feelings for.
4☆ - A great book. Influential on a 10-year scale and/or something which I really enjoyed reading.
3☆ - A good book. Influential on a 1-year scale and/or something which I liked reading.
2☆ - A not-so-good book. Possibly not worth the time to read and/or something which I disliked reading.
1☆ - A near-useless book. Probably not worth the time to read and/or something which I really disliked reading.
---
May 20, 2022
Excellent reading
This book contains the most complete and detailed historical review of AI development I have ever seen. Although I don't agree with everything said there, I still recommend is as a must read for everyone who wants to know how it all started and why.
This book contains the most complete and detailed historical review of AI development I have ever seen. Although I don't agree with everything said there, I still recommend is as a must read for everyone who wants to know how it all started and why.
July 10, 2024
I took my time reading this because it was not only nearly 600 pages, but the pages were very large and the text was very small. This is a book about the detailed history of Artificial Intelligence research and development, and Dr. Nilsson is a major participant in addition to being the historian author of this book.
Nils does a fantastic job of surveying the landscape and walking the reader through. This is a book that does get into logically complex descriptions of AI technology, but it is not a book that asks a reader to look at complex math or solve problems - it is not a math/science textbook, but it could serve as a history textbook in a class on AI / machine learning.
This one gets 4 stars because it completely delivers what it proposes to, but given the nature of the subject matter, it inevitably cannot satisfy the appetite of a 2024 reader. This is a book that could use a new edition that brings us current, and in fact would be a great benefit to the industry and academia. Not sure how old Nils is, but if he's not up to the task, I see an opportunity for someone else to pick up the torch and bring this type of technological history into the present.
Nils does a fantastic job of surveying the landscape and walking the reader through. This is a book that does get into logically complex descriptions of AI technology, but it is not a book that asks a reader to look at complex math or solve problems - it is not a math/science textbook, but it could serve as a history textbook in a class on AI / machine learning.
This one gets 4 stars because it completely delivers what it proposes to, but given the nature of the subject matter, it inevitably cannot satisfy the appetite of a 2024 reader. This is a book that could use a new edition that brings us current, and in fact would be a great benefit to the industry and academia. Not sure how old Nils is, but if he's not up to the task, I see an opportunity for someone else to pick up the torch and bring this type of technological history into the present.
October 28, 2024
Solid. Non-nonsense and comprehensive.
Kind of nice reading about AI before the ML boom of the 2010s and GenAI boom of the 2020s. Many of the core ideas already existed. But at the same time many ideas now seem painfully outdated.
Kind of nice reading about AI before the ML boom of the 2010s and GenAI boom of the 2020s. Many of the core ideas already existed. But at the same time many ideas now seem painfully outdated.
July 6, 2019
Interesting introduction into AI history, worth to read
November 2, 2019
Μια ιντερναλιστική ιστορία της ΤΝ.
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October 3, 2023
Not a textbook, not a history book. Not rigorous enough to be a computer science textbook not objective and thorough enough to be a history book.
March 18, 2017
I have just become an immediate fan of AI and the AI world we're moving toward, warts and all. But I'm a fan because I think it's inevitable. This was a life-changing read.
April 12, 2014
Breezy read and, at that, very much full of pointers to the past, present and future of artificial intelligence. I was very pleased to learn about MIT's Common Sense Computing Initiative, especially given that they have released freely reusable software libraries that drive their work. Hope to find out more about "hierarchical" approaches to artificial intelligence, as the author calls them, such as the work being done at Numenta. Information on these projects has been hard to come by but now I might have more of an idea of where to look.
Displaying 1 - 13 of 13 reviews