Physics Colloquium

Some of the most powerful techniques developed in ML are rooted in physics, such as MCMC, Belief Propagation, and Diffusion based Generative AI. 

We have recently witnessed that the flow of information has also reversed, with new tools developed in the ML community impacting physics, chemistry and biology. 

Examples include faster DFT and MD simulations, PDE Neural Surrogate models, generating druglike molecules, and many more. In this talk I will review the exciting opportunities for further cross fertilization between these fields, and discuss in some detail some projects I have been involved in, ranging from transition path sampling to classical DFT methods. 

I will close by arguing that the analogy between Generative AI and Nonequilibrium Thermodynamics might run deeper than people might realize and that a fruitful new field on the interface may be emerging.

Join via Zoom:
https://caltech.zoom.us/j/81866929019
Meeting ID: 818 6692 9019

The colloquium is held in Feynman Lecture Hall, 201 E. Bridge.