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A general Agent OS can boost long-horizon robotic execution and enable continual learning through structured memory management and self-evolution.
For the first time, a scaling law for quadruped motion tracking reveals that performance consistently improves with larger training datasets, unlocking new capabilities in robotic locomotion.