A British-Canadian researcher has won the Nobel Prize in physics for work developing the foundations of machine learning and artificial intelligence.
The University of Toronto’s Geoffrey Hinton was awarded the prize Tuesday morning, along with Princeton University researcher John Hopfield.
“I’m flabbergasted. I had, no idea this would happen,” Hinton said when reached by the Nobel committee on the phone Tuesday.
The Royal Swedish Academy of Sciences says the prize was awarded to Hinton and Hopfield for “foundational discoveries and inventions that enable machine learning with artificial neural networks.”
Ellen Moons, a member of the Nobel committee at the Royal Swedish Academy of Sciences, says the two laureates “used fundamental concepts from statistical physics to design artificial neural networks that function as associative memories and find patterns in large data sets.”
She says that such networks have been used to advance research in physics and “have also become part of our daily lives, for instance in facial recognition and language translation.”
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While the committee honoured the science behind machine learning and artificial intelligence, Moons also mentioned its flip side, saying that “while machine learning 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 shares those concerns. He quit a role at Google so he could more freely speak about the dangers of the technology he helped create.
Hinton said he continues to worry “about a number of possible bad consequences” of his machine learning work, “particularly the threat of these things getting out of control,” but still would do it all over again.
The physics prize carries a cash award from a bequest left by the award’s creator, Swedish inventor Alfred Nobel.
— with files from The Associated Press.
© 2024 The Canadian Press
