Physical AI is more than robots, says the Nvidia veteran now investing in it

Quick take

Amulya Vishwanath, a veteran from NVIDIA’s robotics marketing team, argues that physical AI extends beyond robots. He describes robotics as still being in a “Lego era,” where basic components such as actuators, robotic hands, software, and safety standards are still under fundamental redevelopment. This framework challenges the popular narrative that robotics powered by general foundation models is about to rapidly advance or transform the field.

Why it matters

For builders, investors, and operators, Vishwanath’s view signals that physical AI’s progress will be slower and more modular than some expect. The reliance on foundational hardware and software blocks that need rebuilding means deploying capable robotic systems involves ongoing engineering at a component level, not just applying AI models. This holds back plug-and-play robotics and forces long-term investment to mature components and interfaces. It also pressures AI startups and robotics players to focus on hardware innovation and interoperability rather than only software and large model integration.

AI-driven robotics remains a complex hardware-software integration challenge rather than a quick software upgrade. This means capital and development efforts should be spread across real-world physical system design and safety assurance. It also shifts the risk profile for investors aiming to bet on the physical AI space, since scaling robotics involves more than just better AI models.

AI Quick Briefs Editorial Desk