"JEPA-Anything: Learning Predictive Models across Different Worlds" This research proposes one world-modeling framework that works across vision, biology, control, molecules, physics, weather, and clinical data. They used something called Orthogonal Predictive Factorization, which splits a single JEPA latent state into complementary factors that predict different parts of the world and recombine into a complete state. This improves all 10 matched dynamics tasks and even produces factors that…