RoboCat
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DeepMind's self-improving foundation agent that operates different robotic arms from as few as 100 demonstrations.
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.
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