C-JEPA teaches AI physics of object interactions

C-JEPA is a world model built on the Joint Embedding Predictive Architecture that embeds a causal inductive bias into learning. It enables AI to reason about object interactions and counterfactual scenarios. In tests, C-JEPA performed predictive control tasks over eight times faster than standard models using roughly 1% of typical input features.