CERN and Mistral sign intent to build a foundation model for collider physics

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CERN and Mistral sign intent to build a foundation model for collider physics

CERN and Mistral signed a statement of intent for a long-term strategic partnership to build a Large Physics Model, described as the first foundation model for collider physics.
The model will be trained on billions of simulated proton-proton collisions from the Large Hadron Collider and designed for tasks from particle reconstruction and identification to flagging unexpected signals and evaluating future detector designs.
CERN stores about one exabyte of experimental LHC data, and the HL-LHC, expected to begin operation around 2030, will increase the number of collisions tenfold.
The initial focus is high-energy physics, but the partnership is said to have the potential to produce AI approaches for the wider scientific community.

Hacker News opinions

Mistral has been behind the curve since it started, so I'm not sure it's the best pick for science. If they were the only one willing to build a custom LHC model, fine, but this reads more like moving CERN money into a European AI company.

Fair, but I doubt a frontier lab would bother with a collider-only model. It wouldn't be great PR for them, so the EU angle might be the only way this gets built at all.

Neural nets were standard for signal/background separation in Higgs work around 2012. The ATLAS discovery paper used them to identify photons and for the H->WW b-tagger, so this isn't new to physicists.

Symbolic AI proof search is old but real. Schoonschip helped show Yang-Mills gauge theories are renormalizable back in 1971, which is more science than most modern demos have done.

I saw a post where AI agents audited papers for flawed conclusions and flagged about 15% of them. Auditing like that is already useful, even if it's not glamorous.

Maths is the only solid case so far in my view. I'm curious whether experimental science gets its first big win from speeding up the scientists before the simulations get good enough to replace them.

Does a model trained on detector data even count as a large language model? It sounds like the name is doing marketing work here.