Physics AI research that’s shaping the industry.
Mistral has acquired Emmi AI, reinforcing its focus on Physics AI for industrial sectors such as aerospace, automotive, semiconductors, and energy. The acquisition brings Emmi’s work on enabling faster product development and continuous performance gains at scale. Mistral highlights several published breakthroughs, including a new 3D CFD dataset for transonic wings, a technical report adding datasets for AB‑UPT, and the development of the Anchored‑Branched Universal Physics Transformer for large‑scale aerodynamics CFD and multi‑physics processes.
The Core Development
The acquisition of Emmi AI has highlighted Mistral’s commitment towards pushing the state-of-the-art in AI research and enterprise solutions for industrial engineering.
Emmi’s work, now part of Mistral, is dedicated to fundamentally enabling engineers to build the next generation of products faster and secure continuous performance gains in operations at scale for their customers.
We are doubling down on building foundational Physics AI for the industries that shape the physical world, such as aerospace, automotive, semiconductors, and energy.
How It Works & Technical Architecture
Anchored-Branched Universal Physics Transformer (AB-UPT) for aerodynamics CFD. Handles raw geometry without remeshing at 9M surface and 140M volume cells on a single GPU.
Strategic Perspective & Ecosystem Impact
Existing aerospace datasets predominantly focus on 2D airfoils, neglecting these critical 3D phenomena. To address this gap, we present a new dataset of CFD simulations for 3D wings in the transonic regime. The dataset comprises volumetric and surface-level fields for around 30,000 samples with unique geometry and inflow conditions.
Driven by the advancement of GPUs and AI, the field of Computational Fluid Dynamics (CFD) is undergoing significant transformations. This paper bridges the gap between the machine learning and CFD communities by deconstructing industrial-scale CFD simulations into their core components.
In this technical report, we add two new datasets to the body of empirically evaluated use-cases of AB-UPT, combining high-quality data generation with state-of-the-art neural surrogates.
Why it matters
By integrating advanced Physics AI models and large datasets, Mistral aims to accelerate engineering workflows and improve real‑time simulation capabilities, which can reduce development time and cost in high‑impact industries.