Big Brains: New Books on Artificial Intelligence


“For my part, I welcome our new IT overlords,” wrote an ironic Ken Jennings in 2011 after his decisive loss in “Jeopardy!” by IBM’s Watson computer and the artificial intelligence that powers it. A decade later, Mr. Jennings’ feelings seem premonitory. Alexa and Siri inhabit our homes and devices. Digital transformation has overtaken our workplaces. AI-powered recommendation engines help determine what movies we watch, what products we buy and what information we receive, influencing our preferences and igniting our politics.

However, the concept of intelligent computers, put forward by the British mathematician Alan Turing in 1950, is not new; the term “artificial intelligence” is also not used for the first time at a research conference in 1956. What has changed is the power and reach of AI, especially with the arrival of what is called “deep learning” – the ability of powerful pattern recognition, with apparently little human instruction required.

In “Genius Makers” (Dutton, 370 pages, $ 28), New York Times tech reporter Cade Metz tells the fascinating story of the scientists who developed deep learning, a small group of researchers “who nurtured an idea for decades, often in the face of outright skepticism before ‘she does not suddenly come of age’.

At the epicenter of the effort is Geoff Hinton, descendant of a long line of prominent British academics. Captivated by the idea that computers could mimic the brain, Hinton followed his passion from Edinburgh to Pittsburgh to the University of Toronto, where he and his students, in the early 2010s, showed that a mathematical system “modeled on the neural network in the brain” could identify common objects “with a precision that previously seemed impossible.” The feat was achievable as long as the computer could first learn from the vast treasures of The approach quickly shifted from detecting chats in YouTube videos to intuitive digital assistants and software designed to report credit card fraud.

Mr. Hinton and his students quickly worked for Google, while colleagues were snatched up by other tech powers like Facebook in California and Baidu in China, companies “caught in the same global arms race” for technology and AI expertise. The search for talent was so intense that a Microsoft executive compared the cost of acquiring an AI researcher to the cost of acquiring an NFL quarterback.


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