The people who are teaching machines to make sense of the world

A closely-linked network of several score brilliant men and a few women are pushing the boundaries of artificial intelligence research. You’ll meet many of these high-achieving and sometimes eccentric individuals in the pages of Genius Makers. You’ll get a glimpse inside Google, Facebook, Baidu, and other major institutions where most of the cutting-edge AI research is underway. And in these pages, you’ll gain perspective on the issues and uncertainties that trouble this rarefied community. In a more general sense, Genius Makers will also show how the shifting currents of peer pressure influence the course of scientific research.

One approach among many

The emergence of deep learning

The high-profile events that have brought AI to the world’s attention in recent years are all based on deep learning. For example, the defeat of the world’s top chess masters and Go champions. The increasing facility of machines in understanding spoken language. The advances made in self-driving cars. And the now-widespread use of face recognition. In Genius Makers, New York Times technology reporter Cade Metz profiles the scientists who made all this possible — for good or ill.

Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World by Cade Metz (2021) 382 pages ★★★★☆

This chart from DataFlair purports to show how neural networks work. Does it do the job for you? It doesn’t for me. Even after reading dozens of books on AI, I can understand only the most superficial aspects of how the technology works. Is it magic? Arthur C. Clarke might have thought it would be hard to tell.

Seven key players

Geoff Hinton

British-Canadian cognitive psychologist and computer scientist Geoff Hinton (born 1947) Is the grand old man of the researchers profiled in Genius Makers. If anything, he is the central figure in this story, the founding father of the deep learning movement. As Metz puts it, “Hinton and his students changed the way machines saw the world.” It was he who stubbornly continued to advocate for the use of neural networks in developing artificial intelligence in the face of near-universal disapproval within the field. A 1969 book by MIT legends Marvin Minsky and Seymour Papert was the cause. The book savagely attacked AI research using that approach and turned the tide against it for decades.

In Metz’s words, Hinton is “the man who didn’t sit down.” A back injury had prevented him from sitting for seven years when Metz arrived to interview him in December 2012. And Metz describes the elaborate arrangements Hinton must make when he travels. It’s quite remarkable that the man could function at all.

Hinton teaches at the University of Toronto. He joined Google in 2013 but lives and continues to work with his students in Canada. Hinton received the 2018 Turing Award, together with Yoshua Bengio and Yann LeCun, for their work on deep learning. He is the great-great-grandson of logician George Boole (1815–64). Boole’s work in mathematics (Boolean algebra) much later helped ground the new field of computer science.

Yoshua Benguio

Demis Hassabis

Alex Krizhevsky

Yann LeCun

Andrew Ng

Ilya Sutskever

About the author

Cade Metz covers AI research, driverless cars, robotics, virtual reality, and other emerging technologies for the New York Times. He had earlier worked for Wired magazine. Genius Makers is his first book. James Fallows’ review of the book, along with a second one on AI by another Times reporter, recently appeared in the paper’s Sunday Book Review. Fallows explains, “Much of Metz’s story runs from excitement for neural networks in the early 1960s, to an ‘A.I. winter’ in the 1970s, when that era’s computers proved too limited to do the job, to a recent revival of a neural-network approach toward ‘deep learning,’ which is essentially the result of the faster and more complex self-correction of today’s enormously capable machines.”

In the notes at the conclusion of the text, Metz describes the research he conducted in writing Genius Makers. “This book is based,” he writes, “on interviews with more than four hundred people over the course of the eight years I’ve been reporting on artificial intelligence for Wired magazine and then the New York Times, as well as more than a hundred interviews conducted specifically for the book. Most people have been interviewed more than once, some several times or more.”

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Author, book reviewer, serial entrepreneur, board member