Can robotic world models scale predictably like LLMs? RoboJEPA trains JEPA world models from 22M to 8B parameters on data from 12 robot platforms, learning to predict how the world changes under different actions. And they found that prediction error follows a scaling law, with larger models achieving better robotic planning. When scaled enough, capabilities like obstacle avoidance and object manipulation emerge, with successful zero-shot deployment on real…