Table of Contents
1. Why This NVIDIA–Dassault Deal Matters
2. Jensen Huang’s Bigger Vision for AI and Industry
3. A Partnership 25 Years in the Making
4. What “Virtual Twins” Really Mean (In Simple Words)
5. NVIDIA’s Technology Stack Explained Clearly
6. Moving From Offline Simulation to Real-Time AI
7. How Life Sciences Will Change With AI Virtual Twins
8. Automotive Engineering Enters a New Era
9. Software-Defined Factories and Smart Robotics
10. The Rise of AI Factories at Gigawatt Scale
11. Virtual Companions: AI That Works With Engineers
12. Why This Partnership Signals a Major Industrial Shift
13. Final Takeaway: The Next Phase of AI Is Physical
NVIDIA CEO Jensen Huang believes the future of artificial intelligence is no longer limited to screens and software. In his latest announcement with Dassault Systèmes, Huang revealed NVIDIA’s largest partnership ever focused on building AI-powered virtual twins that work in real time.
This move signals a major shift in how industries design products, factories, and even entire systems.
01.Why This NVIDIA–Dassault Deal Matters
In simple terms, NVIDIA and Dassault Systèmes are joining forces to make digital simulations faster, smarter, and more realistic than ever before.
Dassault is known for its “virtual twin” platform, which allows companies to simulate products, factories, and systems before they are built. NVIDIA brings accelerated computing and AI that can turn those simulations into real-time, living digital environments.
Together, they are aiming to change how engineering, science, and manufacturing work at a global scale.
02.Jensen Huang’s Bigger Vision for AI and Industry
During the announcement, Jensen Huang framed this moment as part of a much larger transformation.
According to Huang, computing platforms are being reinvented from the ground up. Instead of fixed designs and slow simulations, industries are moving toward software-defined systems powered by AI.
Huang compared AI’s importance to basic infrastructure like electricity and the internet. In his view, AI is no longer just a tool it is becoming foundational.
03.A Partnership 25 Years in the Making
This collaboration is not new.
Huang and Dassault’s leadership explained that their partnership goes back more than 25 years, starting during the shift from Unix workstations to Windows-based systems.
Early work with OpenGL helped define modern graphics. NVIDIA’s CgFX later evolved into CUDA, which today powers AI workloads across the world.
What is being announced now is simply the biggest step yet in that long relationship.
04.What “Virtual Twins” Really Mean (In Simple Words)
A virtual twin is a digital copy of something real.
It could be:
• A car
• A factory
• A robot
• A data center
• Even a biological system
The difference now is that these twins are no longer static models. With AI and accelerated computing, they can behave, learn, and respond in real time.
This allows companies to test ideas safely, faster, and at much lower cost.
05.NVIDIA’s Technology Stack Explained Clearly
As part of this partnership, Dassault will integrate several NVIDIA technologies directly into its platform:
• NVIDIA CUDA-X for high-speed computing
• NVIDIA AI, including physical and agentic AI
• NVIDIA Omniverse, NVIDIA’s digital twin technology
Together, these tools allow massive simulations to run faster and with far more detail than before.
Huang said this integration could increase compute-driven workflows by 100x, 1,000x, and eventually even a million times.
06.Moving From Offline Simulation to Real-Time AI
Traditionally, simulations were slow and done offline. Engineers would wait hours or days for results.
This partnership aims to move simulations into real time.
Examples include:
• Real-time wind tunnel testing
• Live robot training inside virtual factories
• Continuous validation during product design
Over the next five to ten years, this could become standard across major industries.
07.How Life Sciences Will Change With AI Virtual Twins
One of the most powerful use cases discussed was life sciences.
By combining NVIDIA AI with Dassault’s BIOVIA platform, companies can build digital models of biological systems.
This allows researchers to:
• Understand DNA, proteins, and cells
• Design new materials and chemicals
• Develop healthier food products faster
A real example shared was Bel Group, which aims to create healthier foods while using less water and fewer physical tests.
Instead of hundreds of lab experiments, AI-powered virtual twins can generate and test protein designs digitally.
08.Automotive Engineering Enters a New Era
The automotive industry also stands to benefit greatly.
Jensen Huang explained how AI can combine physics-based simulations with predictive models to speed up development while staying accurate.
NVIDIA’s PhysicsNeMo platform can deliver predictions up to 10,000 times faster.
Dassault cited Lucid Motors as an example, where engineers design not just the shape of a vehicle, but its behavior crash safety, aerodynamics, and performance right from the start.
09.Software-Defined Factories and Smart Robotics
Factories are becoming more complex, with robots, sensors, and AI working together.
Huang described future factories as systems of millions of interacting objects, all simulated and managed inside virtual twins.
Dassault highlighted OMRON as an example of designing factories to be software-defined from day one, allowing greater flexibility and resilience.
This approach helps companies adapt faster to changes in demand and technology.
10.The Rise of AI Factories at Gigawatt Scale
Huang also introduced the idea of AI factories.
These are massive facilities designed to:
• Build chips
• Assemble supercomputers
• Train and operate AI systems
According to Huang, a single gigawatt-scale AI factory can cost around $50 billion, and many are already being built worldwide.
NVIDIA itself uses Dassault’s virtual twin tools to design and operate these facilities before construction begins.
11.Virtual Companions: AI That Works With Engineers
Another key topic was AI assistants, described as “virtual companions.”
These AI tools can:
• Turn images into 3D models
• Help manage complex designs
• Track regulations and compliance
• Learn an engineer’s preferences
Huang stressed that these tools are not meant to replace engineers. Instead, engineers become managers of AI companions, guiding and supervising them.
This allows human creativity and judgment to remain central.
12.Why This Partnership Signals a Major Industrial Shift
This NVIDIA–Dassault collaboration is not just about better software.
It represents a shift toward:
• Knowledge factories
• Real-time digital worlds
• AI-driven decision making
• Software-defined industries
Without real-time simulation and AI, many of these advances would not be possible.
13.Final Takeaway: The Next Phase of AI Is Physical
AI is moving beyond chatbots and data analysis.
With virtual twins, AI is now shaping the physical world how we design products, build factories, and manage complex systems.
NVIDIA and Dassault are positioning themselves at the center of this transformation.
And this partnership may define the next decade of industrial innovation.
If you want to stay ahead of how AI, virtual twins, and industrial computing are reshaping the global economy, follow Econ AI for clear explanations, expert analysis, and real-world AI business insights. The future of AI is no longer virtual it’s becoming real.
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