RoboCat

Cross-embodiment: Single agent controls multiple different robotic arms and grippers, generalizing across hardware.

Self-improving loop: Generates new training data via fine-tuning on its own demonstrations, progressively improving its own capabilities.

Few-shot adaptation: Adapts to new tasks from as few as 100 demonstrations - practical for real-world deployment.

Robotics foundation agent: A key data point that robotics was moving toward the same foundation-model + self-improvement paradigm as LLMs.