John Hopfield and Geoffrey Hinton were awarded the Nobel Prize in physics in 2024 for their groundbreaking contributions to the field of machine learning.
The scientists were recognized by The Royal Swedish Academy of Sciences on Tuesday for their groundbreaking discoveries and inventions that make machine learning possible through artificial neural networks.
Hopfield, working at Princeton University in the US, was awarded for developing a memory system that can save and recover images and patterns in data.
Hinton, employed at the University of Toronto, created a technique that can automatically discover characteristics in data, enabling it to carry out duties like recognizing particular elements in images.
The Nobel committee stated in a press release that this year’s two winners of the Nobel Prize in Physics utilized tools from physics to create techniques that serve as the basis for modern machine learning.
“The winners’ efforts have already provided significant advantages.” Ellen Moons, chair of the Nobel Committee for Physics, stated that artificial neural networks are utilized in various areas of physics, including the creation of new materials with particular characteristics.
She also mentioned that these networks are now a regular part of our everyday lives, such as in facial recognition and language translation.
Nonetheless, the committee also acknowledged the worldwide issues related to machine learning and artificial intelligence.
Moons emphasized that it is the responsibility of all people to utilize this new technology in a safe and ethical manner for the advancement of humanity.
Hinton has previously responded to those fears. He left his position at Google in order to speak more openly about the risks associated with the technology he played a role in developing.
On Tuesday, he repeated his uncertainty during a phone call to the committee, expressing his surprise at the award by saying he was “flabbergasted.”
The researcher expressed his ongoing concern regarding various potential negative outcomes of his work in machine learning, particularly emphasizing the risk of losing control over these developments.
Nevertheless, he mentioned that he would repeat the same actions once more.
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