John Hopfield and Geoffrey Hinton

Dear Commons Community,

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.”

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 what the three of us were doing was nonsense,” Hinton told the AP in 2019. “My message to young researchers is, don’t be put off if everyone tells you what you are doing is silly.”

Many of Hinton’s former students and collaborators followed him into the tech industry as it began capitalizing on AI innovations, and some started their own AI companies, including Frosst’s Cohere and ChatGPT maker OpenAI. Hinton said he uses machine learning tools in his daily life.

“Whenever I want to know the answer to anything, I just go and ask GPT-4,” Hinton said at the Nobel announcement. “I don’t totally trust it because it can hallucinate, but on almost everything it’s a not-very-good expert. And that’s very useful.”

Hopfield, 91, created an associative memory that can store and reconstruct images and other types of patterns in data, the Nobel committee said.

Just as Hinton came to the field from psychology, Hopfield stressed how cutting edge science comes from crossing the borders of scientific fields like physics, biology and chemistry instead of researchers staying in their lane. It’s why this prize is a physics prize, he said, pointing out that his neural network borrows from condensed matter physics.

With big complex problems in scientific fields, “if you are not motivated by physics, you just don’t tackle the class of problems,” Hopfield said.

While there’s no Nobel for computer science, Li said that awarding a traditional science prize to AI pioneers is significant and shows how boundaries between disciplines have blurred.

Congratulations to these winners!

Tony