NVIDIA (NASDAQ:NVDA) CEO Jensen Huang joined Dassault Systèmes leadership on stage to outline what both executives described as a major new phase in their long-running partnership, centered on bringing accelerated computing and artificial intelligence deeper into Dassault’s “virtual twin” platform.
The discussion framed the current period as a broad “reinvention” of the computing stack and industrial workflows, with both leaders repeatedly pointing to a shift toward “software-defined” products and operations, real-time simulation, and AI-driven design and manufacturing.
A decades-long collaboration, now aimed at “reinventing the computing platform”
Both executives argued that a new platform shift is underway. Huang said industries are moving from structured representations—where engineers explicitly define geometry and materials—toward “a generative computing model,” requiring the computing stack to be rebuilt with AI as a core component. He described AI as becoming infrastructure, comparable to water, electricity, and the internet.
Expanded integration of NVIDIA technologies into Dassault’s platform
Huang said the companies are announcing what he called “the largest collaboration our two companies have ever had,” stating that Dassault Systèmes will integrate multiple NVIDIA technologies:
- NVIDIA CUDA-X acceleration libraries
- NVIDIA AI for “physical AI” and “agentic AI”
- NVIDIA Omniverse, described as NVIDIA’s digital twin technology
Huang said fusing these technologies into Dassault’s environment is intended to bring accelerated computing and AI to users at significantly larger scale—citing “100 times, 1,000 times, and very soon a million times greater” than before. He also emphasized a goal of shifting tasks that were previously “pre-rendered” or “offline simulations” into real time, including real-time wind-tunnel simulations, real-time robot operation in virtual factories, and real-time validation workflows, which he said could unfold over the next five to 10 years.
Use cases highlighted: life sciences, automotive engineering, and software-defined factories
The event featured several examples meant to demonstrate how “virtual twins” paired with AI could alter engineering and R&D workflows.
Life sciences and food science: The executives discussed integrating NVIDIA AI with Dassault’s BIOVIA, framing it around building a “world model” grounded in biology, physics, and material science. Huang described the need to “understand the language of life”—DNA, proteins, and cells—and then use generative methods to translate and create new proteins, chemicals, and materials with desired properties.
As an example, Pascal cited Bel Group (maker of Babybel), saying the company aims to produce healthier foods while consuming less water and complementing dairy proteins with non-dairy proteins. He said that where development previously required “hundreds of physical tests for one single product,” the company can now “generate automatically the protein from the virtual twins,” resulting in faster innovation and what he described as more “certified decisions.”
Automotive simulation and emulation: Huang described combining “principled simulations” with AI prediction models—what he called surrogate and emulation models—to reduce runtime while staying grounded in physics. He pointed to NVIDIA’s PhysicsNeMo as a “physics-aware AI model simulation system and AI framework,” saying it can deliver predictions “10,000 times faster.” Pascal referenced Lucid as a customer example, saying the company embeds crash behavior, aerodynamics, and vehicle performance earlier in development so engineers design not just shape but also behavior, with certification in mind.
Factories and robotics: Huang argued factories are becoming systems of millions of objects, robots, and AI, and said they will be “simulated and operated completely inside a Virtual Twin.” Pascal cited OMRON as an example of engineering a “software-defined factory,” emphasizing designing autonomy from day one to improve flexibility, resilience, and adaptability.
AI factories and virtual twins for large-scale infrastructure buildouts
Huang also discussed what he called “AI factories,” describing three fast-growing, interlinked industrial buildouts: chip factories (including packaging), computer factories that assemble supercomputers, and AI factories that use those systems to “manufacture the AIs.” He said a “gigawatt AI factory is about $50 billion,” and claimed “tens of gigawatts” are being built globally. He characterized this as the “largest industrial infrastructure buildout in human history.”
To reduce risk and improve first-time success, Huang said NVIDIA uses Dassault’s MBSE (model-based systems engineering) along with mechanical design tools to plan and simulate data centers and their systems before construction, including running networks and supercomputers inside the virtual twin. He added that virtual twins can be used during operations as AI systems modulate performance, power, temperature, and cooling over time. Huang also said NVIDIA is “the first customer” in this context.
“Virtual companions” and the role of engineers
The leaders also discussed AI assistants—referred to as “virtual companions”—that can help engineers move faster, including converting unstructured inputs (like images) into structured 3D data and parametric models. When asked whether this will replace engineers, Huang argued the opposite: designers will become managers and architects of teams of AI companions, and usage of Dassault tools could expand to include both human and AI users.
Pascal cited NIAR (the National Institute for Aviation Research) as an example, suggesting virtual companions could ingest regulations and continuously verify conformity—shifting compliance to “compliance by design.” Huang contrasted language models with “world models,” saying world models must obey the laws of physics, understand causality, and use simulation and examples to learn physical behavior.
On protecting knowledge, Huang said future companions would codify a user’s preferences and domain expertise and should not be public, likening it to the accumulated knowledge represented by his own inbox.
Both executives closed by characterizing the partnership as a way to deliver “knowledge factories” that power virtual twins and AI companions with accelerated computing, enabling new categories of software-defined products and operations that they said would be difficult or impossible without real-time simulation and AI.
About NVIDIA (NASDAQ:NVDA)
NVIDIA Corporation, founded in 1993 and headquartered in Santa Clara, California, is a global technology company that designs and develops graphics processing units (GPUs) and system-on-chip (SoC) technologies. Co-founded by Jensen Huang, who serves as president and chief executive officer, along with Chris Malachowsky and Curtis Priem, NVIDIA has grown from a graphics-focused chipmaker into a broad provider of accelerated computing hardware and software for multiple industries.
The company’s product portfolio spans discrete GPUs for gaming and professional visualization (marketed under the GeForce and NVIDIA RTX lines), high-performance data center accelerators used for AI training and inference (including widely adopted platforms such as the A100 and H100 series), and Tegra SoCs for automotive and edge applications.
