John Hopfield and Geoffrey Hinton have won the Nobel Prize in physics 2024 for their pioneering work in the field of machine learning.
The Royal Swedish Academy of Sciences said on Tuesday the scientists were honoured “for foundational discoveries and inventions that enable machine learning with artificial neural networks”.
Hopfield, whose research is carried out at Princeton University in the United States, was recognised for creating an associative memory that can store and reconstruct images and other types of patterns in data.
Hinton, who works at the University of Toronto, invented a method that can autonomously find properties in data, allowing it to perform tasks such as identifying specific elements in pictures.
“This year’s two Nobel Laureates in physics have used tools from physics to develop methods that are the foundation of today’s powerful machine learning,” the Nobel committee said in a media release.
“The laureates’ work has already been of the greatest benefit. In physics we use artificial neural networks in a vast range of areas, such as developing new materials with specific properties,” said Ellen Moons, chair of the Nobel Committee for Physics.
Such networks have also “become part of our daily lives, for instance in facial recognition and language translation,” she added.
Fears
However, the committee also noted the global concerns surrounding machine learning and artificial intelligence.
“Collectively, humans carry the responsibility for using this new technology in a safe and ethical way for the greatest benefit of humankind,” Moons added.
Hinton has previously acted upon such fears. He quit a role at Google so he could more freely speak about the dangers of the technology he helped create.
He reiterated his doubts on Tuesday as he told the committee by phone that he was “flabbergasted” by the award.
The researcher said that 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”.
However, he added that he would still do it all over again.