The term world model is used almost everywhere in AI now.
But the more often it appears, the less clear it sometimes become.
A reinforcement learning researcher may use the term for a latent dynamics model. A robotics team may use it for an action-conditioned simulator. A video generation company may describe a large generative model as a world model. An autonomous driving company may use the same expression for a system who creates traffic scenarios.
All of these systems have something in common.
But they are not solving exactly the same problem.
