Categories: AI/ML News

A thermodynamic approach to machine learning: How optimal transport theory can improve generative models

Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics that deals with constantly changing systems, explains why optimal transport theory, a mathematical framework for the optimal change of distribution to reduce cost, makes generative models optimal. As nonequilibrium thermodynamics has yet to be fully leveraged in designing generative models, the discovery offers a novel thermodynamic approach to machine learning research. The findings were published in the journal Physical Review X.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

Griffith Voice – an AI-powered software that dubs any video with voice cloning

Hi guys i'm a solo dev that built this program as a summer project which…

8 hours ago

Developers lose focus 1,200 times a day — how MCP could change that

One of the most impactful applications of MCP is its ability to connect AI coding…

9 hours ago

Best 360 Cameras (2025), Tested and Reviewed

It’s a small world after all, and these cameras can capture all of it at…

9 hours ago

Why tiny bee brains could hold the key to smarter AI

Researchers discovered that bees use flight movements to sharpen brain signals, enabling them to recognize…

9 hours ago

Just tried animating a Pokémon TCG card with AI – Wan 2.2 blew my mind

Hey folks, I’ve been playing around with animating Pokémon cards, just for fun. Honestly I…

1 day ago

Busted by the em dash — AI’s favorite punctuation mark, and how it’s blowing your cover

AI is brilliant at polishing and rephrasing. But like a child with glitter glue, you…

1 day ago