From world models to active agents: the next step for physical AI

This post discusses the transition from passive world modeling to active agents in physical AI, highlighting the need for agents to sense, reason, plan, and act within their environments. It references research presented at the CVPR 2026 Workshop on World Models Meet Active Sensing and Closed-Loop Planning (WMAS), including work on RoboWM-Bench, GEM-4D, and SAW-Bench. The post emphasizes that generative models are becoming part of the action loop, forming a continuous cycle of sense-understand-predict-plan-act. It also touches upon agent security testing and prompt injection defense as critical aspects of developing intelligent physical AI systems.