LiberAI Releases Liber-0: Glove Data Replaces Robot Demos

Original title: This looks like a truly brilliant launch for robot training.
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Chinese startup LiberAI released Liber-0, a robot foundation model trained on data from lightweight sensor gloves. It achieved a 36% success rate on new tasks without any robot demonstrations. Experiments showed that 10K hours of glove motion data outperformed 2M hours of internet video, significantly lowering the barrier for embodied AI data acquisition.

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Rohan Paul (@rohanpaul_ai) · 2026-11-04 15

This looks like a truly brilliant launch for robot training.

Workers wear a thin 131 g sensor glove that records exact hand movements while they do ordinary tasks, so no robot is needed to collect the data.

Chinese robotics startup LiberAI (@liberai_robot) released Liber-0, the AI model that controls a robot’s arms and hands.

With no robot demonstrations of the tested tasks, Liber-0 completed 36.0% of 600 attempts at 60 new tasks. In LiberAI’s tests, 10K glove hours also beat 2M hours of internet video.

Robots normally learn a task after people steer them through it repeatedly, and Liber-0 replaces much of that with 2.2M+ hours of human experience.

Video alone shows what hands do, not the measured motion a robot must copy.

The company’s LiberSense Glove supplies that motion by logging hand poses and trajectories while people work.

Measured motion beat volume: 10K glove hours outperformed 2M hours of web video in matched runs.

Trained on 25% of the robot demonstrations plus glove data, a policy scored 75.6 for partial completion, beating 72.8 from all of them.

↳ 引用 @liberai_robot (LiberAI): Introducing Liber-0, our World Action Model for zero-shot robot manipulation—including dexterous, multi-step tasks.

Across 60 tasks proposed by GPT-6 and 600 trials, Liber-0 achieved 36% overall success without robot demonstrations collected specifically for those tasks: • Pick-and-place: 63.5% • Other manipulation tasks: 34.0% • Challenging multi-step tasks: 10.5%

Zero-shot capability extends beyond individual actions to coordinated sequences.

Pretrained on 2.2M+ hours of human experience, Liber-0 jointly predicts future observations and actions to turn human experience into robot skills.

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