New paper advised by Yann LeCun! "H-JEPA: End-to-End Learning of Hierarchical World Models for Visual Planning" Most world models plan in a single latent space and at one timescale, which makes long-horizon planning expensive and forces one representation to handle both low-level motion and high-level goals. H-JEPA instead stacks JEPA world models across multiple timescales, with higher levels predicting farther into the future. The highest level first figures out roughly where the agent…