AI Researcher Explains Deep Learning’s Collision Course with Particle Physics

For a particle physicist, the world’s biggest questions — how did the universe originate and what’s beyond it — can only be answered with help from the world’s smallest building blocks.

James Kahn, a consultant with German research platform Helmholtz AI and a collaborator on the global Belle II particle physics experiment, uses AI and the NVIDIA DGX A100 to understand the fundamental rules governing particle decay.

The AI Podcast · AI Researcher James Kahn Explains Deep Learning’s Collision Course with Particle Physics – Ep. 143

Kahn spoke with NVIDIA AI Podcast host Noah Kravitz about the specifics of how AI is accelerating particle physics.

He also touched on his work at Helmholtz AI. Khan helps researchers in fields spanning medicine to earth sciences apply AI to the problems they’re solving. His wide-ranging career — from particle physicist to computer scientist — shows how AI accelerates every industry.

Key Points From This Episode:

The nature of particle physics research, which requires numerous simulations and constant adjustments, requires massive AI horsepower. Kahn’s team used the DGX A100 to reduce the time it takes to optimize simulations from a week to roughly a day.
The majority of Kahn’s work is global — at Helmholtz AI, he collaborates with researchers from Beijing to Tel Aviv, with projects located anywhere from the Southern Ocean to Spain. And at the Belle II experiment, Kahn is one of more than 1,000 researchers from 26 countries.

Tweetables:

“If you’re trying to simulate all the laws of physics, that’s a lot of simulations … that’s where these big, powerful machines come into play.” — James Kahn [6:02]

“AI is seeping into every aspect of research.” — James Kahn [16:37]

You Might Also Like:

Speed of Light: SLAC’s Ryan Coffee Talks Ultrafast Science

Particle physicist Ryan Coffee, senior staff scientist at the SLAC National Accelerator Laboratory, talks about how he is putting deep learning to work.

A Conversation About Go, Sci-Fi, Deep Learning and Computational Chemistry

Olexandr Isayev, an assistant professor at the UNC Eshelman School of Pharmacy at the University of North Carolina at Chapel Hill, explains how deep learning, abstract strategy board game Go, sci-fi and computational chemistry intersect.

How Deep Learning Can Accelerate the Quest for Cheap, Clean Fusion Energy

William Tang, principal research physicist at the Princeton Plasma Physics Laboratory, is one of the world’s foremost experts on how the science of fusion energy and HPC intersect. He talks about how he sees AI enabling the quest to deliver fusion energy.