The Beijing Academy of Artificial Intelligence trained Orca on 125,000 hours of video without using any action labels. It predicts abstract world states rather than pixels, matching the specialized π0.5 across five robotics tasks. This approach bypasses the need for expensive labeled datasets. It offers a scalable path for training generalist robotic agents.