Mistral's Physics AI Adoption: Laying the Groundwork for Accelerated Engineering

Traditional numerical physics simulations solve partial differential equations to predict fluid flow, structural deformation, and more. However, this approach has limitations: reviewing a single design variation can take anywhere from hours to weeks, and it requires expensive HPC (High-Performance Computing) resources and specialized expertise, making it difficult to sufficiently explore the design space.

To address this problem, Mistral has adopted Emmi AI. Physics AI learns from the output data of physics solvers to directly predict physical behavior from geometric structures and boundary conditions. It can compute an entire physics field in just a few seconds on a single GPU, dramatically increasing the speed of design iteration.

Physics AI does not completely replace traditional first-principles solvers, but rather serves to increase the throughput of the design loop. Traditional solvers are used for final validation and handling edge cases, while physics AI is leveraged to rapidly explore a vast range of design options.

Mistral plans to integrate this into its enterprise solutions, enabling partners such as ASML, Airbus, and Siemens Energy to implement AI-native engineering in industrial settings.