Why ​Physical AI Needs A New Architecture To Scale

Dr. Greg Ombach argues that current vision, language, and action models (VLAs) in physical AI face scaling challenges between large, data-heavy models and smaller, less transferable ones. He proposes a modular architecture emphasizing geometry and physical understanding to enable robots to learn quickly, operate locally, and transfer skills reliably across environments, crucial for applications beyond structured settings like aerospace and healthcare.