CERN and Mistral plan an AI foundation model for particle physics

CERN and French AI company Mistral signed a statement of intent on 15 October to build a “ Large Physics Model “, which CERN calls the first foundation model for collider physics. It will be trained on simulated Large Hadron Collider data to help reconstruct and identify particles. No budget or timeline was disclosed.

CERN and Mistral plan to build an AI model for particle physics, the European lab said on Thursday. The two signed a statement of intent for a long-term deal on AI for science.

At its centre is a “ Large Physics Model ”, which CERN calls the first foundation model for collider physics. Such a model is trained once on a huge dataset and then used for many jobs.

It will learn from billions of simulated proton collisions in the Large Hadron Collider (LHC), the world’s largest particle accelerator. CERN said it should help rebuild collisions, spot particles, flag odd signals, and test new detector designs.

Today, CERN uses a chain of separate tools to turn raw detector signals into data that physicists can use. One model could learn the whole chain instead, the lab said.

“ High-energy physics provides a unique environment in which artificial intelligence can be developed and tested with exceptional rigour, ” said Enrica Porcari, CERN’s chief information officer.

CERN has stored about one exabyte, or one million terabytes, of LHC data so far. The number of collisions will rise tenfold with an LHC upgrade due to start around 2030.

For Mistral, the deal adds to a push into science and engineering. The Paris-based firm bought Emmi AI, a physics AI startup, earlier this year and later launched an industrial engineering product.

“ Together, we have the opportunity to push the frontiers of high-energy physics, ” said Johannes Brandstetter, Mistral’s vice president of AI for engineering and a co-founder of Emmi AI.

The work will start with particle physics, but both sides said the models could later help other fields. Neither gave a budget or a timeline, Reuters reported.

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