CCERN operates the Large Hadron Collider, the world's largest particle accelerator, through an international collaboration of 25 member states. Its four major experiments—ALICE, ATLAS, CMS, and LHCb—probe fundamental questions about matter and the universe, leading to discoveries like the Higgs boson. What sets CERN apart is its role as a neutral ground for global scientific cooperation, having also given rise to the World Wide Web. The goal is to advance humanity's understanding of the fundamental laws of nature.
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CERN and Mistral AI join forces to develop AI foundation models for science. 19 October 2026 CERN and Mistral AI will work together on foundation models for scientific discovery, starting with high-energy physics. | (C) CERN - Mistral AI CERN in Geneva and AI developer Mistral AI have signed a statement of intent for a long-term strategic partnership on foundation models for scientific discovery. The first goal is a "Large Physics Model" for high-energy physics. CERN and Mistral AI have signed a statement of intent for a long-term strategic partnership on foundation models for scientific discovery. CERN contributes its expertise in fundamental physics, scientific data and large-scale computing, while Mistral AI brings large-scale model training. The initial focus is high-energy physics, but the work could also inform AI approaches for the wider scientific community. A foundation model for collider physics. The central goal is a single pretrained model, described as the first foundation model for collider physics: a "Large Physics Model". It would be trained on billions of simulated proton-proton collisions at the Large Hadron Collider (LHC) and support several tasks, including reconstructing particle collisions, identifying particles, flagging unexpected signals and evaluating future detector designs. Today, reconstruction relies on a chain of specialized algorithms that progressively convert detector signals into physics objects. Machine learning already improves individual steps of this chain, and a foundation model could learn across all of it within a single model. The volume of data involved is considerable. CERN has stored about one exabyte (one million terabytes) of LHC experimental data to date, and the High-Luminosity LHC (HL-LHC), expected to start operating around 2030, will increase the number of collisions tenfold. Shared AI capabilities for physics. Enrica Porcari, CERN Chief Information Officer, says high-energy physics offers "a unique environment in which artificial intelligence can be developed and tested" with strong rigor, and that the partnership aims to create AI capabilities that the wider physics community can share. Johannes Brandstetter, Vice-President of AI for Engineering at Mistral AI, says the company is proud to work with CERN to explore what large-scale AI models can offer to particle physics, with the potential for new scientific discoveries.
CERN and Mistral partner to build Flare, a new AI model for physics Published on 10/15/2026 at 08:14 am EDT - Modified on 10/15/2026 at 09:07 am EDT or by email * Stock Market * Stock Market News * CERN and Mistral partner to build Flare, a new AI model for physics
CERN and Mistral partner to build Flare, a new AI model for physics. 15 Oct 2026 08:02PM (Updated: 15 Oct 2026 09:01PM) Add CNA as a trusted source to help Google better understand and surface our content in search results. Oct 15: European physics research centre CERN and Mistral AI have established a long-term strategic partnership to develop a foundation model for scientific discovery, the two organisations said on Thursday. The statement of intent gives the French AI company access to one of the world's largest scientific datasets as it seeks to compete on frontier science. Mistral Chief Executive Arthur Mensch wrote in an article published in Le Monde on Thursday that frontier models were "now indispensable to scientific progress" and criticised companies that keep their advantages to themselves. CERN Chief Information Officer Enrica Porcari said the new partnership would "advance AI capabilities that can serve the whole physics community and be shared". The partners aim to build a "Large Physics Model", called "Flare", which CERN said in a statement would be the first foundation model for collider physics, trained on billions of simulated particle collisions. It will use the same idea as the large language models behind generative AI but be trained on collision data rather than text, a CERN spokesperson told Reuters. It is meant to replace some specialised algorithms now used to reconstruct and identify particles. The spokesperson said CERN has been using AI to turn raw data from experiments into pictures of the events for a decade, but with multiple tools used for each step. CERN holds about one exabyte, or 1 million terabytes, of experimental data from the Large Hadron Collider, and expects the volume of collisions to increase tenfold after its ongoing upgrade, expected around 2030. "High-energy physics provides a unique environment in which artificial intelligence can be developed and tested with exceptional rigour," Porcari said. No timeline or budget was disclosed. Both sides said the models could later serve other sciences. The Paris-based lab, broadly viewed as Europe's best chance to catch up with US and Chinese competitors, this month unveiled a new open-weight model it says can challenge its rivals. It will be released to the public on October 27. Users can download open-weight models from platforms and use them on their own hardware.
CERN partners with Mistral to build a Large Physics Model. Chart unavailable for this asset. Select Chart to retry. Europe's particle physics lab and its leading AI startup signed a statement of intent to train a foundation model on collider data an hour ago Sponsored: Vera - AI-powered prediction market intelligence, built for serious analysts Explore Vera CERN has spent decades smashing protons together to understand the universe. Now it wants an AI model that can make sense of the wreckage. On October 15, 2026, the European Laboratory for Particle Physics signed a statement of intent with Mistral AI, the French developer behind the Mistral family of language models. The goal is a pretrained Large Physics Model, a foundation model built specifically for high-energy physics. What the two sides are building. The model is expected to train on billions of simulated proton-proton collision events tied to the Large Hadron Collider (LHC). The idea is to give physicists a general-purpose tool rather than a pile of narrow, single-task algorithms. Three applications sit at the top of the list. The first is collision reconstruction, which means working backward from detector signals to figure out what actually happened in a collision. The second is particle identification, sorting out which particles flew out of a given event. The third is anomaly detection, flagging events that don't match what known physics predicts. The data problem driving the deal. CERN does not lack raw material. Its LHC experiments have produced close to one exabyte of data. The High-Luminosity LHC upgrade, projected for around 2030, is expected to raise collision rates by a factor of ten. Traditional analysis pipelines were not designed with that volume in mind, which helps explain why CERN is looking for an AI partner now rather than later. AI, tech, and the markets they move - in one daily briefing. Daily. Free. Join 34,000+ readers across crypto, finance, and policy. Mistral brings the other half of the equation: experience training very large models. The company previewed Mistral Large 4 on October 6, 2026, a model with 1 trillion parameters. How Cryptobriefing got here. CERN and Mistral have held earlier exchanges and presentations dating back to 2025, laying groundwork before anything was put in writing. Neither organization has disclosed timelines, funding figures, or specific milestones beyond the initial agreement. What this means. For physicists, the stakes are practical. If a single pretrained model can handle reconstruction, identification, and anomaly detection reasonably well, research teams could spend less time building bespoke tools and more time asking questions. The risks are the usual ones for an early-stage scientific AI effort. Models trained on simulated data have to prove they hold up against real detector output, and physics demands a level of rigor that tolerates very little hallucination. What to watch next is straightforward. Look for a formal agreement with defined funding and deadlines, any published benchmarks on reconstruction or anomaly detection, and signs of whether the model is being readied ahead of the High-Luminosity era around 2030. Disclosure: This article was edited by Diego Almada Lopez. For more information on how Cryptobriefing create and review content, see its Editorial Policy.
CERN and Mistral partner to build Flare, a new AI model for physics. By Thomson Reuters Oct 15, 2026 | 8:02 AM By Leo Marchandon Oct 15 (Reuters) - European physics research centre CERN and Mistral AI have established a long-term strategic partnership to develop a foundation model for scientific discovery, the two organisations said on Thursday. The statement of intent gives the French AI company access to one of the world's largest scientific datasets as it seeks to compete on frontier science. Mistral Chief Executive Arthur Mensch wrote in an article published in Le Monde on Thursday that frontier models were "now indispensable to scientific progress" and criticised companies that keep their advantages to themselves. CERN Chief Information Officer Enrica Porcari said the new partnership would "advance AI capabilities that can serve the whole physics community and be shared". The partners aim to build a "Large Physics Model", called "Flare", which CERN said in a statement would be the first foundation model for collider physics, trained on billions of simulated particle collisions. It will use the same idea as the large language models behind generative AI but be trained on collision data rather than text, a CERN spokesperson told Reuters. It is meant to replace some specialised algorithms now used to reconstruct and identify particles. The spokesperson said CERN has been using AI to turn raw data from experiments into pictures of the events for a decade, but with multiple tools used for each step. CERN holds about one exabyte, or 1 million terabytes, of experimental data from the Large Hadron Collider, and expects the volume of collisions to increase tenfold after its ongoing upgrade, expected around 2030. "High-energy physics provides a unique environment in which artificial intelligence can be developed and tested with exceptional rigour," Porcari said. No timeline or budget was disclosed. Both sides said the models could later serve other sciences. The Paris-based lab, broadly viewed as Europe's best chance to catch up with US and Chinese competitors, this month unveiled a new open-weight model it says can challenge its rivals. It will be released to the public on October 27. Users can download open-weight models from platforms and use them on their own hardware. (Reporting by Leo Marchandon in Gdansk; Editing by Toby Chopra, Emelia Sithole-Matarise and Joe Bavier)
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Industries
Company Size
5,001-10,000
Company Stage
N/A
Total Funding
N/A
Headquarters
Meyrin, Switzerland
Founded
1954
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