[Review] A Brief History of Artificial Intelligence (Michael Wooldridge) Summarized.

[Review] A Brief History of Artificial Intelligence (Michael Wooldridge) Summarized.
9Natree
[Review] A Brief History of Artificial Intelligence (Michael Wooldridge) Summarized.

Oct 19 2026 | 00:10:40

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Episode • October 19, 2026 • 00:10:40

Show Notes

A Brief History of Artificial Intelligence (Michael Wooldridge)

- Amazon USA Store: https://www.amazon.com/dp/B088DTDQHH?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/A-Brief-History-of-Artificial-Intelligence-Michael-Wooldridge.html

- Apple Books: https://books.apple.com/us/audiobook/a-brief-history-of-artificial-intelligence/id1545080506?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree

- eBay: https://www.ebay.com/sch/i.html?_nkw=A+Brief+History+of+Artificial+Intelligence+Michael+Wooldridge+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/B088DTDQHH/

#TuringTest #SymbolicAI #AIwinters #Deeplearning #Artificialgeneralintelligence #ABriefHistoryofArtificialIntelligence

Michael Wooldridge’s A Brief History of Artificial Intelligence: What It Is, Where We Are, and Where We Are Going is a concise popular science account of AI, written by an Oxford computer scientist with long experience in the field. Published in 2021, it combines intellectual history, technical explanation, and cautious discussion of future possibilities. Its central purpose is to replace popular myths about thinking machines with a clearer account of what AI researchers actually build: systems that perform particular tasks associated with intelligence. Wooldridge traces the field from Alan Turing’s foundational questions and early symbolic programs through periods of disappointment, the rise of machine learning, and modern successes in language, vision, games, robotics, and scientific discovery. Rather than treating every impressive system as evidence of human-like understanding, he examines the methods, data, computation, and narrow task definitions behind progress. The result is an accessible overview that situates contemporary AI within a longer research tradition while keeping questions of consciousness, risk, work, and social responsibility in view.

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