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Build a lightweight vision-language-action-inspired embodied agent that learns to perceive, plan, predict, and replan directly from pixel observations in a grid world environment.
Yann LeCun introduces LeWorldModel (LeWM), a new framework targeting JEPA collapse in pixel-based predictive world modeling. This advancement could significantly improve how AI systems learn meaningful representations from raw visual data.
