The two companies announced an expanded partnership at a Cadence conference in Santa Clara on Wednesday. The goal: make robot training data more accurate so physical AI systems reach real-world deployment faster.
Cadence Design Systems and Nvidia have announced an expanded partnership aimed at closing one of robotics’ most persistent problems: the gap between how robots learn inside computer simulations and how they actually perform in the physical world.
The collaboration, unveiled by the CEOs of both companies at a Cadence conference in Santa Clara, California, integrates Cadence’s high-fidelity physics simulation engines with Nvidia’s AI training platforms, including its Isaac open-source simulation libraries and Cosmos open-world models.
Cadence is best known as one of the dominant suppliers of software used to design advanced computing chips. But the company also makes physics engines that model how real-world materials interact, how metals deform, how fluids flow, how surfaces make contact.
These simulations are used in aerospace, automotive, and semiconductor design, but are now being applied to a new problem: generating the training data that robot AI systems need to learn how to handle objects and navigate physical environments.
Training robots in simulation is faster and cheaper than doing so in the real world, but the training data is only as useful as the physics engine is accurate.
“The more accurate the generated training data is, the better the model will be,” Cadence CEO Anirudh Devgan said at the Santa Clara conference.
Nvidia CEO Jensen Huang described the scope of the collaboration directly: “We’re working with you across the board on robotic systems.”
The combined stack will link Cadence’s multiphysics simulation with Nvidia’s model training pipelines and deploy the results on Nvidia’s Jetson robotics and edge AI hardware.
The output is a workflow that runs from world-model training through physics simulation to real-world deployment feedback, coordinated by AI agents throughout the lifecycle.
The announcement is part of a broader pattern of Nvidia building deep simulation partnerships across industrial engineering. The company has separately announced partnerships with Siemens and Dassault Systèmes to build industrial AI platforms and virtual twins.
For Cadence, the robotics application represents a significant expansion of its simulation software into the AI infrastructure layer at a moment when demand for accurate robot training data is growing rapidly.
