李飞飞的世界模型，终于开始训练机器人了

TL;DR - World Labs launched R2S2R, a real-to-simulation-to-real engine for training, evaluating, and deploying robot policies. It aims to make robot learning scalable by turning real tasks into reusable virtual environments that preserve relevant visual and physical behavior.

• Real-to-Sim reconstructs robots, sensors, objects, and task dynamics; Sim-to-Real trains policies, probes failures, and deploys them back to hardware.
• Simulation-only policies reportedly transferred to several robot platforms and completed selected manipulation tasks autonomously for one hour without failure or intervention.
• In an ALOHA task, simulation evaluations generally preserved real-world checkpoint rankings and similar success/failure patterns.
• The launch follows World Labs’ acquisition of robotics simulation startup SceniX, combining its robotics expertise with World Labs’ generative 3D world modeling.