Foundation Models

RoboCat

RoboCat is a self-improving generalist manipulation agent from Google DeepMind, introduced in 2023 and built on the Gato-style decision transformer architecture with a VQ-GAN image tokenizer. Trained across multiple real and simulated arm embodiments, it adapts to new tasks or robots from as few as 100 to 1,000 demonstrations, then generates its own rollout data with the fine-tuned policy to grow the training set for subsequent, more capable generations.

Why it matters for physical AI

RoboCat provided early evidence for the self-improvement flywheel, in which a generalist policy's own deployments produce the data that trains its successor, a loop central to scaling robot foundation models.