Princeton physicist wins Nobel Prize in Physics for groundbreaking AI research

An American professor at Princeton University and a British-Canadian professor at the University of Toronto won the Nobel Prize in Physics on Tuesday for research that formed “the building blocks” of a key component of artificial intelligence.

John J. Hopfield, 91, received the honor along with Geoffrey E. Hinton, 76, who left his job at Google last year so he could speak freely about his concerns about the technology.

Since the 1980s, the two have used tools from physics to develop the foundations of so-called “machine learning,” one of the core concepts of AI that is widely used today.

Their research “formed the building blocks of machine learning that can help people make faster and more reliable decisions,” Ellen Moons, chairwoman of the Nobel Committee for Physics, said at a news conference. The use of this technology has “become a part of our daily lives, for example in facial recognition and language translation,” said Moons, while warning that the “rapid development of AI also raises concerns about our future.”

Machine learning involves feeding computers massive amounts of data so they can “learn” how to do everything from diagnosing diseases to knowing which streaming series people like to watch.

Hopfield has been a key influential figure in the field since 1982, when he invented the “Hopfield network” – a method that has been widely used ever since. Hinton used this foundation to develop the “Boltzmann machine,” which can be used for tasks such as classifying images.

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This article was originally published on NBCNews.com