CERN and Mistral Partner to Build First Large Physics AI Model

Overview

CERN, the European Organization for Nuclear Research, and Mistral AI have announced a strategic partnership aimed at advancing artificial intelligence for scientific discovery. The two organizations signed a statement of intent to collaborate on developing large-scale foundation models tailored specifically for physics research. This initiative combines CERN’s vast expertise in fundamental science and massive data processing with Mistral’s leadership in training large language and multimodal models.

The collaboration marks a significant step toward creating the first Large Physics Model, a pretrained foundation model designed to handle the complexities of collider physics. By leveraging the resources of both institutions, the partnership seeks to address some of the most challenging computational problems in modern particle physics while simultaneously pushing the boundaries of AI capabilities in Europe.

Strategic Partnership Goals

The primary objective of this alliance is to build a robust AI infrastructure that can support the next generation of high-energy physics experiments. While the initial focus will remain on high-energy physics, the underlying technologies and methodologies developed through this partnership are expected to benefit the broader scientific community. The goal is to create AI tools that are not only powerful but also transparent and controllable, allowing researchers to own and customize their scientific instruments.

CERN brings to the table one of the world’s largest volumes of scientific data. To date, the laboratory has stored approximately one exabyte, or one million terabytes, of experimental data from the Large Hadron Collider (LHC). This sheer scale of data provides an ideal testing ground for developing and refining AI models under conditions of extreme precision and complexity.

Mistral, headquartered in France, is recognized globally for its work in developing open-weight models and infrastructure. The company’s involvement ensures that the resulting tools will align with European values regarding technological sovereignty and accessibility. Together, the partnership aims to strengthen Europe’s position in both scientific research and advanced AI development.

The Large Physics Model

At the heart of this collaboration is the ambition to develop a single, pretrained foundation model for collider physics. Unlike traditional machine learning approaches that rely on specialized algorithms for individual tasks, this new model is designed to learn across the entire reconstruction chain. It will be trained on billions of simulated proton-proton collisions generated by the LHC, the world’s most powerful particle accelerator.

The model is intended to perform multiple critical tasks, including:

• Reconstructing particle collisions from raw detector signals
• Identifying specific types of particles produced in high-energy events
• Flagging unexpected signals that may indicate new physics phenomena
• Evaluating and optimizing future detector designs

This unified approach addresses a fundamental challenge in analyzing LHC data. Currently, the reconstruction process involves a series of specialized algorithms that progressively transform detector signals into the objects used for physics analysis. While machine learning has already improved performance in various isolated tasks, a foundation model offers the potential to integrate these advances into a cohesive system capable of handling the full scope of the reconstruction pipeline.

Scientific Context and Data Scale

High-energy physics provides a unique environment for the development and testing of artificial intelligence. The rigorous demands of the field require models to achieve exceptional accuracy and reliability. CERN’s Chief Information Officer, Enrica Porcari, emphasized the value of this partnership in advancing AI capabilities that can be shared with the wider physics community.

High-energy physics provides a unique environment in which artificial intelligence can be developed and tested with exceptional rigour. We are partnering with Mistral, a leading European AI company, to advance AI capabilities that can serve the whole physics community and be shared.

The scale of data production is set to increase dramatically in the coming years. The High-Luminosity Large Hadron Collider (HL-LHC), expected to begin operation around 2030, will increase the number of collisions by a factor of ten. This exponential growth in data volume underscores the necessity for more efficient and powerful AI-driven analysis tools.

Johannes Brandstetter, Vice-President of AI for Engineering at Mistral, highlighted the opportunity to explore what large-scale AI models can bring to the growing complexity of particle physics. He noted that the collaboration has the potential to push the frontiers of high-energy physics and lead to new scientific discoveries through advanced AI capabilities.

Future Implications

The partnership represents a step towards a new generation of AI tools capable of addressing the scale, precision, and complexity of modern science. By bringing together European excellence in AI and fundamental science, the initiative aims to create sustainable technological solutions that can be applied beyond particle physics.

The development of open-weight models and shared infrastructure aligns with broader efforts to ensure that advanced AI technologies remain accessible and beneficial to public institutions and advanced industries across Europe and beyond. As the Large Physics Model takes shape, it stands as a testament to the power of international scientific collaboration in tackling some of the most profound questions about the universe.