AI pioneers win Nobel Prize in physics

Two pioneers of artificial intelligence — John Hopfield and Geoffrey Hinton — won the Nobel Prize in physics Tuesday for helping create the building blocks of machine learning that is revolutionizing the way we work and live but also creates new threats for humanity. Hinton, who is known as the godfather of artificial intelligence, is a citizen of Canada and Britain who works at the University of Toronto, and Hopfield is an American working at Princeton. “These two gentlemen were really the pioneers,” said Nobel physics committee member Mark Pearce. The artificial neural networks — interconnected computer nodes inspired by neurons in the human brain — the researchers pioneered are used throughout science and medicine and “have also become part of our daily lives,” said Ellen Moons of the Nobel committee at the Royal Swedish Academy of Sciences. Hopfield, whose 1982 work laid the groundwork for Hinton’s, told The Associated Press, “I continue to be amazed by the impact it has had.” Hinton predicted that AI will end up having a “huge influence” on civilization, bringing improvements in productivity and health care. “It would be comparable with the Industrial Revolution,” he said in an open call with reporters and officials of the Royal Swedish Academy of Sciences. “We have no experience of what it’s like to have things smarter than us. And it’s going to be wonderful in many respects,” Hinton said. “But we also have to worry about a number of possible bad consequences, particularly the threat of these things getting out of control.” Warning of AI risks The Nobel committee also mentioned fears about the possible flipside. Moons said that while it has “enormous benefits, its rapid development has also raised concerns about our future. Collectively, humans carry the responsibility for using this new technology in a safe and ethical way for the greatest benefit of humankind.” Hinton, who quit a role at Google so he could speak more freely about the dangers of the technology he helped create, shares those concerns. “I am worried that the overall consequence of this might be systems more intelligent than us that eventually take control,” Hinton said. For his part, Hopfield, who signed early petitions by researchers calling for strong control of the technology, compared the risks and benefits to work on viruses and nuclear energy, capable of helping and harming society. At a Princeton news conference, he made reference to the concerns, bringing up the dystopia imagined in George Orwell’s “1984,” or the fictional apocalypse inadvertently created by a Nobel-winning physicist in Kurt Vonnegut’s “Cat’s Cradle.” Neither winner was home to get the call Hopfield, who was staying with his wife at a cottage in Hampshire, England, said that after grabbing coffee and getting his flu shot, he opened his computer to a flurry of activity. “I’ve never seen that many emails in my life,” he said. A bottle of champagne and bowl of soup were waiting, he added, but he doubted there were any fellow physicists in town to join the celebration. Hinton said he was shocked at the honor. “I’m flabbergasted. I had no idea this would happen,” he said when reached by the Nobel committee on the phone. He said he was at a cheap hotel with no internet. Hinton’s work considered “the birth” of AI Hinton, 76, helped develop a technique in the 1980s known as backpropagation instrumental in training machines how to “learn” by fine-tuning errors until they disappear. It’s similar to the way a student learns, with an initial solution graded and flaws identified and returned to be fixed and repaired. This process continues until the answer matches the network’s version of reality. Hinton had an unconventional background as a psychologist who also dabbled in carpentry and was genuinely curious about how the mind works, said protege Nick Frosst, who was Hinton’s first hire at Google’s AI division in Toronto. His “playfulness and genuine interest in answering fundamental questions I think is key to his success as a scientist,” Frosst said. Nor did he stop at his pioneering 1980s work. “He’s been consistently trying out crazy things and some of them work very well and some of them don’t,” Frosst said. “But they all have contributed to the success of the field and galvanized other researchers to try new things as well.” Hinton’s team at the University of Toronto wowed peers by using a neural network to win the prestigious ImageNet computer vision competition in 2012. That spawned a flurry of copycats and was “a very, very significant moment in hindsight and in the course of AI history,” said Stanford University computer scientist and ImageNet creator Fei-Fei Li. “Many people consider that the birth of modern AI,” she said. Hinton and fellow AI scientists Yoshua Bengio and Yann LeCun won computer science’s top prize, the Turing Award, in 2019. “For a long time, people thought w