digital twin
digital-twin-8f0c61b8·3 events·first seen 28d agoAliases: digital twin, digital twins
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Mistral AI Acquires Physics AI Startup Emmi AI to Expand Industrial AI Capabilities
Mistral AI has entered a definitive agreement to acquire Emmi AI, an Austria-based Physics AI company specializing in large engineering models, real-time simulations, and digital twins for industrial applications. The acquisition brings over 30 researchers and engineers to Mistral's Science and Applied AI teams. Mistral aims to build best-in-class AI agents for engineers in sectors like aerospace, automotive, and semiconductors by combining Emmi's physics modeling expertise with its own foundation models. The move is framed as advancing Mistral's 'Science roadmap' and positioning it as the leading AI transformation partner for industrial enterprises.
Mistral AI Acquires Physics AI Startup Emmi AI to Expand Industrial Engineering Capabilities
Mistral AI has entered a definitive agreement to acquire Emmi AI, an Austrian Physics AI startup specializing in large engineering models, real-time simulations, and digital twins for industrial applications. The acquisition brings over 30 researchers and engineers into Mistral's Science and Applied AI teams. Mistral aims to build AI agents for engineers in sectors like aerospace, automotive, and semiconductors, replacing multi-day computations with real-time physics simulations. The move advances Mistral's stated mission to become the leading AI transformation partner for industrial enterprises.
WorldString: Actionable World Representation via Neural Architecture for Object State Modeling
This paper proposes WorldString, a neural architecture designed to model the state manifold of real-world objects by learning from point clouds or RGB-D video streams. Unlike prior approaches that rely on video generation or dynamic scene reconstruction, WorldString explicitly models object action states in a unified, principled framework. It is positioned as a foundational building block for physical world models, functioning as a versatile digital twin. Its fully differentiable structure is intended to enable integration with policy learning and neural dynamics.