Defining Physical AI
Physical AI is the application of large-scale AI models — particularly foundation models trained on internet-scale data — to robots and other physical systems that interact with the real world. Unlike traditional robotics (which relies on hand-engineered perception and control) or traditional AI (which operates on text and images), Physical AI bridges both: it uses the broad knowledge of foundation models to enable robots to understand and manipulate the physical world.
Why Now?
Three converging trends make Physical AI viable: (1) Vision-Language-Action models that can directly output robot actions from visual and language inputs; (2) Affordable, capable robot hardware (arms under $10K, humanoids under $20K); (3) Open datasets and open-source models that lower the barrier to entry. SVRC exists at this intersection — providing the hardware, data infrastructure, and knowledge to make Physical AI practical.
How to Get Started
Start with a capable robot (OpenArm, ALOHA), collect 100 demonstrations of a simple task, fine-tune an open VLA model (OpenVLA or Octo), and evaluate in the real world. SVRC offers complete starter kits and guided onboarding for teams new to Physical AI.