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Silicon Flash > Blog > Power & Cooling > Nvidia and Dassault Systèmes Collaborate on Cutting-Edge Digital Twin AI Platform
Power & Cooling

Nvidia and Dassault Systèmes Collaborate on Cutting-Edge Digital Twin AI Platform

Published February 3, 2026 By Juwan Chacko
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Nvidia and Dassault Systèmes Collaborate on Cutting-Edge Digital Twin AI Platform
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Summary:

  1. Nvidia and Dassault Systèmes partner to bring virtual twin architecture to the enterprise.
  2. Virtual twin technology merges with Nvidia’s AI Infrastructure for real-world solutions.
  3. The partnership aims to revolutionize industries with digital twins for predictive maintenance and production optimization.

    —

    Article:

    Nvidia and Dassault Systèmes Collaborate to Introduce Virtual Twin Technology to Businesses

    Nvidia, a leading technology company, has joined forces with French 3D software firm Dassault Systèmes to introduce virtual twin architecture to the enterprise sector. This partnership aims to revolutionize industries by merging Dassault’s virtual twin technology with Nvidia’s AI Infrastructure, open models, and software libraries to establish practical real-world solutions.

    Virtual twins, also known as digital twins, create a data-driven virtual replica of a real-world asset, system, or process. This innovative technology offers a wide range of benefits for various industries, from manufacturing to the energy sector. In data centers, virtual twins can assist with power and cooling optimization, capacity planning for AI workloads, failure prediction, and more.

    According to Grand View Research, the digital twin market is projected to reach $328.5 billion by 2033, driven by the growing demand for predictive maintenance, remote monitoring, and production optimization. Large enterprises are expected to dominate the digital twin market as the technology continues to evolve.

    Nvidia CEO Jensen Huang emphasized the significance of physical AI as the next frontier of artificial intelligence, grounded in the laws of the physical world. He expressed his belief that the partnership with Dassault Systèmes will transform how researchers, designers, and engineers in various industries build and innovate on a larger scale.

    The collaboration between Nvidia and Dassault Systèmes will leverage Dassault’s model-based systems engineering (MBSE) to design AI factories with the Nvidia Rubin platform and integrate the Omniverse DSX Blueprint for large-scale deployment. This move signifies the evolution of the AI factory concept from a mere marketing buzzword to a solid engineering discipline.

    The infrastructure developed through this partnership will facilitate the power of virtual twins using Nvidia’s open AI models and software libraries. The companies anticipate unlocking advancements in biology and materials research, AI-driven design and engineering, and other cutting-edge fields.

    Pascal Daloz, CEO of Dassault Systèmes, highlighted the era where artificial intelligence not only predicts or generates but also comprehends the real world. He emphasized that the partnership establishes a new foundation for industrial AI that is trustworthy by design and capable of scaling innovation across the generative economy.

    In a LinkedIn comment, CortexForge Maverick Tarasoff pointed out that the partnership marks a significant step toward tangible AI benefits for enterprises. He emphasized the importance of virtual twins being grounded in physics and validated by science, making AI more usable and reliable in the real world.

    In conclusion, the collaboration between Nvidia and Dassault Systèmes represents a groundbreaking development in the integration of virtual twin technology into the enterprise sector. By combining their expertise and resources, these two industry leaders are poised to drive innovation, efficiency, and reliability across various industries through the power of digital twins.

See also  Enhanced Data Centre Solutions: DLC Improvements and Upgrades
TAGGED: collaborate, CuttingEdge, Dassault, digital, Nvidia, Platform, Systèmes, Twin
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