Nobel Prize in Physics awarded to duo for Machine Learning

The Nobel Prize in Physics was awarded to John J. Hopfield of Princeton University and Geoffrey E. Hinton of University of Toronto for Discoveries and Inventions that formed the building blocks of Machine Learning.

The Scientists helped train Artificial Neural Networks that can recognize patterns in large data sets using tools from Physics. Such Machine Learning contributes to aspects of daily lives such as facial recognition and language translation.

“This year’s Physics laureates’ breakthroughs stand on the foundations of Physical Science,” the Nobel Committee said on X on Tuesday, as they awarded the prize in Stockholm. “They have showed a completely new way for us to use computers to aid and to guide us to tackle many of the challenges our society face.”

Artificial Neural Networks, as the name suggests, are inspired by the abilities of the human brain and the network of neurons that enable learning.

“We can recognize images and speech and associate them with memories and past experiences,” said Ellen Moons, chair of the Nobel Committee for Physics. “Millions of neurons wired together give us unique cognitive abilities.”

Machine Learning aims to mimic that ability, Moons said, and “can aid humans in making faster and more reliable decisions.”

Since the 1980s, Hopfield, 91, and Hinton, 76, have conducted important work that uses fundamental concepts from Statistical Physics to design Artificial Neural Networks that can reconstruct images and perform tasks like identifying specific elements in pictures.

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