Vinci4D Touts Physics AI for Chip Design as Ex-Nvidia Exec Says Robotics Is Still in 'Lego Era'

Panneerselvam spoke during an exclusive broadcast on theCUBE, SiliconANGLE Media's livestreaming studio. He said Vinci combines a physics foundation model with a GPU-native physics kernel in an approach it calls Continuous Physics Reasoning, producing repeatable results with solver accuracy. He said teams that understand a product's physics early win the race, and that Vinci lets engineers design at the architectural level while providing performance information.

The model is trained on Vinci's own data rather than customer data, Panneerselvam said. Deployment behind the customer's firewall keeps proprietary design information with the customer. He said the platform works into existing workflows without requiring changes, ingests design files as they are and builds the model with enough automation that there is very little manual input.

Vinci is exploring applications in automotive and aerospace engineering as it expands beyond semiconductors. Its $250 million Series B funding round will support development across additional physics disciplines and industries, including planned capabilities in electromagnetics and fluid dynamics, Panneerselvam said. He also said physics AI could support physical AI, including robots and humanoid systems, by helping engineers understand how those products would behave before committing to a particular design.

Separately, Amulya Vishwanath, who spent seven years leading product marketing for Nvidia's robotics platforms, said robotics is currently in its 'Lego era,' with basic building blocks such as actuators, robotic hands, software and safety standards still being rebuilt. She spoke on TechCrunch's Equity podcast with Dominic-Madori Davis, TechCrunch AI reported on Oct. 16, 2026.

Vishwanath's view runs counter to those who believe robotics, powered by a general foundation model, is about to have its 'ChatGPT moment.' General Intuition CEO Pim de Witte told Equity earlier this year that a single general foundation model would make much of today's specialized robotics work redundant and be that moment, according to TechCrunch.

Vishwanath is founder and managing partner of Techable VC, where she is writing first checks. TechCrunch reported that she is one of the first women executives to spin out of Nvidia and launch her own early-stage firm investing in physical AI across robotics, materials science and life sciences. She defines physical AI as more than robots, saying it can be 'a molecule, a material, a medicine,' or a machine on a factory line.

On the podcast, she discussed what she calls 'conscious automation' and said the best opportunities solve big problems such as family-run factories that cannot find workers or surgeons facing burnout. She wants founders to see their venture capital investor as their moat, and TechCrunch reported that her years at Nvidia built a network she now uses for due diligence and customer introductions. She also discussed where she believes the U.S. and China each have an edge and why humanoids should be good for more than dancing.