Xiaomi robot study finds more data beats bigger models

Xiaomi trained its Xiaomi-Robotics-1 model on more than 100,000 hours of motion data captured by people using camera-equipped handheld grippers, rather than data collected from robots themselves. Adding more data improved performance far more than increasing model size, though absolute success rates remain low and gains haven't plateaued.

Why it matters: This echoes the 'data over parameters' lesson learned in language models, now showing up in robotics: data scale, not model size, looks like the current bottleneck for real-world manipulation. Collecting motion data via handheld grippers instead of expensive robot teleoperation could meaningfully lower the cost of scaling training data across the industry.