World Labs turns one robot demo into thousands of training runs

World Labs, founded by AI researcher Fei-Fei Li, built a simulation engine that generates thousands of variations from a single real-world robot task. Models trained this way ran for an hour each on five different robot platforms without human intervention.

Why it matters: Simulation-based training could sharply cut the cost and time needed to teach robots new tasks, a key bottleneck for scaling real-world robotics. It's part of a broader industry shift toward simulation-first training also seen in Dyna Robotics' recently covered world-action model.