A Tutorial on World Models and Physical AI

The article presents a tutorial on world models in AI, distinguishing between explicit and implicit world models for predictive reasoning and decision-making. It emphasizes the significance of these models in advancing physical AI applications, particularly in robotics and autonomous driving, while addressing challenges in hierarchical reasoning, long-horizon planning, and autonomous goal formation. This framework aims to unify diverse approaches to world modeling, highlighting the potential for integrating perception, prediction, and action in the pursuit of artificial general intelligence.