[{"data":1,"prerenderedAt":27},["ShallowReactive",2],{"nr-en-mistral-cern-flare-physics-foundation-model":3},{"slug":4,"title":5,"dek":6,"date":7,"time":8,"publishedAt":9,"updated":10,"updatedAt":10,"dateFmt":11,"updatedFmt":10,"kind":12,"tier":13,"author":14,"authorName":15,"topics":16,"tracker":10,"trackerLabel":10,"headlineStat":21,"image":22,"ogImage":23,"imageAlt":5,"csv":10,"minutes":24,"words":25,"html":26},"mistral-cern-flare-physics-foundation-model","Mistral and CERN plan to build an AI model for particle physics together","European AI developer Mistral and CERN have, according to CERN, signed a statement of intent. The goal is a large physics model to be trained on simulated proton-proton collisions.","2026-10-16","06:20","2026-10-16T06:20:00+02:00","","October 16, 2026","news","standard","ideal-syka","Ideal Syka",[17,18,19,20],"Foundation models","Particle physics","European AI sovereignty","Research","around 1 exabyte of LHC data","\u002Fnewsroom\u002Fimg\u002Fmistral-cern-flare-physics-foundation-model.webp","\u002Fog-nr\u002Fmistral-cern-flare-physics-foundation-model.en.png",1,275,"\u003Ch2>What was agreed\u003C\u002Fh2>\n\u003Cp>According to CERN, it and Mistral have signed a statement of intent to establish a long-term strategic partnership on developing foundation models for scientific research. The collaboration combines CERN's expertise in fundamental physics, scientific data and large-scale computing with Mistral's experience in training large models. Reuters reported on the partnership the same day and named the model Flare.\u003C\u002Fp>\n\u003Ch2>The planned model\u003C\u002Fh2>\n\u003Cp>At the core is a single pretrained Large Physics Model, which is meant to be the first foundation model for collision physics. It is to be trained on simulated proton-proton collisions at the Large Hadron Collider (LHC) and designed for several tasks, from reconstructing particle collisions and identifying particles to flagging unexpected signals and evaluating future detector designs.\u003C\u002Fp>\n\u003Cp>Reconstruction today relies on a chain of specialised algorithms. Machine learning already plays a role in this, but a foundation model could cover the whole chain within one model.\u003C\u002Fp>\n\u003Ch2>Data basis\u003C\u002Fh2>\n\u003Cp>CERN states it has stored around one exabyte – one million terabytes – of experimental LHC data to date. With the HL-LHC, expected to begin operation around 2030, the number of collisions is set to increase tenfold.\u003C\u002Fp>\n\u003Ch2>Context\u003C\u002Fh2>\n\u003Cp>For German businesses the main signal is that a European model developer is working with a major European research institution on its own foundation models. According to CERN's announcement, spillover into applications beyond high-energy physics is possible but not guaranteed. The partnership is so far a statement of intent with no published term, funding or results.\u003C\u002Fp>\n\u003Ch2>Sources\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.reuters.com\u002Fscience\u002Fcern-mistral-partner-build-ai-foundation-models-physics-2026-10-15\u002F\">Reuters\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fhome.cern\u002Fcern-and-mistral-join-forces-to-accelerate-ai-for-science\u002F\">Home | CERN\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cem>Editorially owned by \u003Ca href=\"\u002Fen\u002Fautor\u002Fideal-syka\">Ideal Syka\u003C\u002Fa>. Sources and method: \u003Ca href=\"\u002Fen\u002Fredaktion\">Newsroom & method\u003C\u002Fa>. Tips and corrections: \u003Ca href=\"mailto:ai@i6eal.de\">ai@i6eal.de\u003C\u002Fa>.\u003C\u002Fem>\u003C\u002Fp>\n",1792135279464]