When A Huge Breakthrough Was Made In Future Of AI Research And Neural Networks, Tech Giants From Around Globe Were Immediately Interested.

By Cate Metz

When A Huge Breakthrough Was Made In The Future Of AI Research And Neural Networks, Tech Giants From Around The Globe Were Immediately Interested. But the man who discovered how to teach computers to think for themselves wasn’t going to share his research for nothing

In 2012, a British computer scientist named Geoff Hinton produced a research paper demonstrating how he and his team at the University Of Toronto had built a neural network – a mathematical system modelled on the neurons in the human brain – which could learn to identify everyday objects better than any ever developed before. The concept had been around since the 1950s but, until Hinton and the two students working with him proved otherwise, had been considered a dead end, a largely impractical concept hovering on the fringes of AI. Interest quickly piqued in the research and Chinese tech giant Baidu soon stepped forward to offer Hinton $12 million for the rights to his work. But Hinton wondered if there was a better way to monetise the concept.

Here, in an extract from his upcoming book, Genius Makers, author Cade Metz recounts how, on the advice of a Toronto lawyer, Hinton founded a three-person start-up and set up an auction that he ran from a hotel room in eastern California, on the shores of Lake Tahoe, receiving bids via email from four major tech companies who hoped to acquire his research. Three were world-renowned: Baidu, Google and Microsoft. The fourth was a two-year-old start-up named DeepMind, a London company founded by a young neuroscientist named Demis Hassabis that would grow to become the most celebrated and influential AI lab of the decade.

In the foothills of the Sierra Nevada, representatives from the four bidders gathered for an auction that would shape the future of artificial intelligence forever. The week of the auction, Alan Eustace, Google’s head of engineering, flew his own twin-engine plane into the airport near the south shore of Lake Tahoe. He and Jeff Dean, Google’s most revered engineer, had dinner with Hinton and his students in the restaurant on the top floor of Harrah’s, a steak house decorated with a thousand empty wine bottles. Baidu, Microsoft and DeepMind also sent representatives to Lake Tahoe for the conference, and others played their own roles in the auction. Kai Yu, the Baidu researcher who’d kicked off the race, held his own meeting with the Toronto researchers before the bidding began. But none of the bidders ever gathered in the same place at the same time. The auction played out over email. Hinton hid the identity of each bidder from all the rest.

He ran the auction from his hotel room, number 731 in the Harrah’s tower, which looked out over the Nevada pines and onto the snowy peaks of the mountains. Each day, he set a time for the next round of bidding, and at the designated hour, he and his two students would gather in his room to watch the bids arrive on his laptop. The laptop sat on a trash can turned upside down on a table at the end of the room’s two queen-sized beds, so that Hinton could type while standing up. The bids arrived via Gmail, the online email service operated by Google, just because this was where he kept an email account. But Microsoft didn’t like the arrangement. In the days before the auction, the company complained that Google, its biggest rival, could eavesdrop on its private messages and somehow game the bids. Technically, Google could read any Gmail message. The terms of service said it wouldn’t, but the reality was that if it ever violated those terms, no one was likely to know. In the end, both Hinton and Microsoft set their concerns aside – “We were fairly confident Google wouldn’t read our Gmail,” he says.


The auction rules were simple: after each bid, the four companies had an hour to raise the buying price by at least a million dollars. DeepMind bid with company shares, not cash, but it couldn’t compete with the giants of the tech world and soon dropped out. That left Baidu, Google and Microsoft. As the bids continued to climb, first to $15 million and then to $20 million, Microsoft dropped out, too, but then it came back in. At about $22 million, Hinton temporarily suspended the auction for a discussion with one of the bidders, and half an hour later, Microsoft dropped out again. That left Baidu and Google, and as the hours passed, the two companies took the price still higher. Kai Yu handled the initial Baidu bids, but when the price reached $24 million, a Baidu executive took over from Beijing. From time to time, Yu would stop by room 731, hoping to glean at least a small sense of where the auction was headed.

The price climbed so high, Hinton shortened the bidding window from an hour to 30 minutes. The bids quickly climbed to $40 million, $41 million, $42 million, $43 million. One evening, close to midnight, as the price hit $44 million, Hinton suspended the bidding again. He needed some sleep. The next day, about 30 minutes before the bidding was set to resume, he sent an email saying the start would be delayed. About an hour later, he sent another. The auction was over. At some point during the night, Hinton had decided to sell his company to Google – without pushing the price any higher.

This, he later admitted, was what he had wanted all along. Even Kai Yu had guessed that Hinton would end up at Google, or at least another American company, because his back would keep him from traveling to China. As it was, Yu was happy just for Baidu to have taken its place among the bidders. By pushing its American rivals to the limit, he believed, the Baidu brain trust had come to realise how important deep learning would be in the years ahead.

Hinton stopped the auction because finding the right home for his research was ultimately more important to him than commanding the maximum price. When he told the bidders at Google he was stopping the auction at $44 million, they thought he was joking – that he couldn’t possibly give up the dollars that were still coming. He wasn’t. He and his students were academics, not entrepreneurs, more loyal to their idea than to anything else.


But Hinton didn’t realise how valuable their idea would prove to be. No one did. Alongside a small group of other scientists, Hinton and his students soon pushed this single idea into the heart of the tech industry. In doing so, they suddenly and dramatically accelerated the progress of artificial intelligence, including talking digital assistants, driverless cars, robotics, automated healthcare and automated warfare and surveillance. “It changed the way that I looked at technology,” Alan Eustace says. “It changed the way many others looked at it too.”

This news was originally published at GQ Magazine.