Hours after artificial intelligence pioneer Geoffrey Hinton, a Nobel Prize in Physicshe drove a rental car to Google’s headquarters in California to celebrate.
Hinton no longer works at Google. The former professor at the University of Toronto also did not do his groundbreaking research at the technology giant.
But his impromptu party reflected AI’s moment as a commercial blockbuster that has also reached the heights of scientific recognition.
That was Tuesday. Then, two employees from Google’s AI division won a prize early Wednesday Nobel Prize in Chemistry for using AI to predict and design new proteins.
“This is truly a testament to the power of computer science and artificial intelligence,” said Jeanette Wing, professor of computer science at Columbia University.
When asked in an email Wednesday about the historic back-to-back science awards for AI work, Hinton said only: “Neural networks are the future.”
It didn’t always seem that way to researchers decades ago experimenting with interconnected computing nodes inspired by neurons in the human brain. Hinton shares this year’s Physics Nobel with another scientist, John Hopfield, for his contribution to developing the building blocks of machine learning.
The advances in neural networks came from “fundamental, curiosity-driven research,” Hinton said at a news conference after his win. “Not to throw money at applied problems, but to let scientists actually follow their curiosity to try to understand things.”
Such work started long before Google existed. But a bountiful technology industry has now made it easier for AI scientists to pursue their ideas, even as it has challenged them with new ethical questions about the social impact of their work.
One reason why the current wave of AI research is so closely tied to the technology industry is that only a handful of companies have the resources to build the most powerful AI systems.
“These discoveries and this opportunity couldn’t happen without massive computing power and massive amounts of digital data,” Wing said. “There are very few companies – technology companies – that have that kind of computing power. Google is one. Microsoft is another.”
The Nobel Prize in chemistry awarded on Wednesday went to Demis Hassabis and John Jumper of Google’s London DeepMind laboratory, along with researcher David Baker of the University of Washington, for work that could help discover new drugs.
Hassabis, the CEO and co-founder of DeepMind, which Google acquired in 2014, told the AP in an interview Wednesday that his dream was to model his research lab after the “incredible storied history” of Bell Labs. Founded in 1925, the industrial laboratory in New Jersey was for decades the workplace of several Nobel Prize-winning scientists who contributed to the development of modern computers and telecommunications.
“I wanted to create a modern industrial research laboratory that did truly cutting-edge research,” Hassabis said. “But of course that requires a lot of patience and a lot of support. We got that from Google and it was great.”
Hinton joined Google late in his career and quit last year so he could talk more freely about his concerns about the dangers of AI, particularly what happens when humans lose control of machines that become smarter than us. But he stops criticizing his former employer.
Hinton, 76, said he was staying in a cheap hotel in Palo Alto, California, when the Nobel Committee woke him up with a phone call early Tuesday morning, forcing him to cancel a medical appointment for later that day.
By the time the sleep-deprived scientist reached Google’s campus in nearby Mountain View, “he seemed quite lively and not very tired at all” as colleagues opened bottles of champagne, said computer scientist Richard Zemel, a former Hinton doctoral student who joined Hinton added. him at the Google party on Tuesday.
“It’s clear that there are now big companies trying to cash in on all the commercial success and that’s exciting,” says Zemel, now a professor at Columbia.
But Zemel said what’s more important to Hinton and his closest colleagues is what the Nobel Prize recognition means for the basic research they have tried to advance for decades.
Guests included Google executives and another former Hinton student, Ilya Sutskever, co-founder and former chief scientist and board member at ChatGPT maker OpenAI. Sutskever helped lead a group of board members that briefly ousted OpenAI CEO Sam Altman last year in unrest that symbolized the industry’s conflict.
An hour before the celebration, Hinton used his Nobel laureate pulpit to throw shade at OpenAI during opening remarks at a virtual press conference hosted by the University of Toronto, thanking former mentors and students.
“I am extremely proud of the fact that one of my students fired Sam Altman,” Hinton said.
Asked to elaborate, Hinton said OpenAI started with a primary goal of developing better-than-human artificial general intelligence “and making sure it was safe.”
“And over time it turned out that Sam Altman was much less concerned about safety than about profits. And I think that’s a shame,” Hinton said.
In response, OpenAI said in a statement that it “prides itself on delivering the most capable and secure AI systems” and that they “safely serve hundreds of millions of people every week.”
Conflicts are likely to continue in a field where building even a relatively modest AI system requires resources “far beyond those of a typical research university,” says Michael Kearns, a professor of computer science at the University of Pennsylvania.
But Kearns, a member of the committee that chooses the winners of computer science’s top prize – the Turing Award – said this week marks a “major victory for interdisciplinary research” that has been decades in the making.
Hinton is only the second person to win both a Nobel Prize and a Turing. The first, the Turing-winning political scientist Herbert Simon, began working on what he called “computer simulation of human cognition” in the 1950s and won the Nobel Prize in Economics in 1978 for his research into organizational decision-making.
Wing, who met Simon early in her career, said scientists are just beginning to find ways to apply computers’ most powerful capabilities to other areas.
“We are just scratching the surface when it comes to scientific discoveries using AI,” she said.
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AP Business Writer Kelvin Chan contributed to this report.