World Action Models tackle a basic weakness of today's robotics AI: current models learn which movements match which camera images, but they don't understand how the world actually changes as a result. A new survey organizes about a hundred papers into two architectural lines and shows a key edge: these models can learn from everyday videos that contain no robot action labels. That kind of data was nearly useless for traditional robotics AI.
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