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An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

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The Science Behind AI’s First Nobel Prize

11 min readOct 16, 2024

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Showing Nobel metals in a Hopfield network with a fire background representing its relationship to thermodynamics.
Author’s own work depicting Nobel Prizes in a Hopfield Network. Background credit: Maxim Tajer, Nobel coin image credit: hyperionforge

The 2024 Nobel Prize in Physics was just announced on 2024–10–04, and this year’s award went to Prof. John Hopfield and Prof. Geoffrey Hinton. But it’s a bit different this time. Instead of the usual discoveries about the natural world, the prize was awarded for something a little more artificial:

“for foundational discoveries and inventions that enable machine learning with artificial neural networks.”

Nobel Foundation Press Release

Two machine learning (ML) models were highlighted: the Hopfield network and the Boltzmann machine. This may surprise some, as ML can seem far removed from physics. However, many early foundational ML concepts were inspired by physical systems.

What was the significance of the award? I believe it was to highlight recent advanced in generative AI (in text/image/video generations), and to remind us that the foundations of these modern models are rooted in physics. More specifically, Hopfield networks and Boltzmann machines can be thought of as some of the original generative models, borrowing physics principles from natural…

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TDS Archive
TDS Archive

Published in TDS Archive

An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

Tim Lou, PhD
Tim Lou, PhD

Written by Tim Lou, PhD

Data Scientist @ TTD | ex Researcher @ Berkeley/LBNL | Particle Physics PhD @ Princeton | Podcast @ quirkcast.org