"JEPA-Anything: Learning Predictive Models across Different Worlds"
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"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 recover Kepler’s scaling law and nominate a biologically validated intervention. https://www.alphax
Posted by alphaXiv (55.9k followers) 1 h ago · 30 likes · 1.7k views · view the original post on X. Kept by the AI Radar as AI research. Tools mentioned: alphaXiv.
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