In beautiful Nobel win, AI researchers Hopfield and Hinton take 2024 Physics Prize – Cyber Tech

Methods drawn from physics

The win is already turning heads on social media as a result of it appears uncommon that analysis in a pc science discipline like machine studying may win a Nobel Prize for physics. “And the 2024 Nobel Prize in Physics doesn’t go to physics…” tweeted German physicist Sabine Hossenfelder this morning.

From the Nobel committee’s perspective, the award largely derives from the truth that the 2 males drew from statistical fashions utilized in physics and partly from recognizing the developments in physics analysis that got here from utilizing the boys’s neural community methods as analysis instruments.

Nobel committee chair Ellen Moons, a physicist at Karlstad College, Sweden stated through the announcement, “Synthetic neural networks have been used to advance analysis throughout physics matters as numerous as particle physics, materials science and astrophysics.”

Hopfield, a 91 year-old theoretical biologist with a physics background, made a breakthrough in 1982 by growing a community that described connections between nodes as bodily forces, as Nature describes in a report. His innovation, often called the Hopfield community, makes use of ideas from physics that describe how atomic spins behave in supplies. Particularly, it shops patterns as low-energy states, permitting the system to recreate photographs when prompted with related patterns. This strategy mimicked associative reminiscence, resembling how the mind remembers phrases or ideas.

Hinton, who’s 76, constructed upon Hopfield’s within the early Eighties by growing a layered model of the Hopfield community that integrated possibilities. Hinton drew parallels to physics research of huge techniques of comparable parts like fuel molecules. As a substitute of monitoring particular person molecules, physicists look at collective properties like strain or temperature. The Boltzmann equation from Nineteenth-century physics calculates the chance of various states in such techniques. Hinton utilized this idea to neural networks, naming his 1985 methodology the “Boltzmann machine,” which highlighted the connection between machine studying and statistical physics. A Bolzmann machine is able to recognizing and classifying photographs and producing new examples primarily based on its coaching knowledge.