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Embodied AI agents can now continuously self-improve by co-evolving their policies, training curricula, and judges, overcoming the bottleneck of static evaluation.
Language, when self-evolving and treated as a physical representation, can unlock state-of-the-art physical plausibility in video world models, even surpassing proprietary systems.
