Eren Chen(@ErenChenAI):What stands out to me about Liber-0 is the attempt to make human experience useful to robots, not just collect more data. It was tested on 60 tasks (600 trials), with a 36% overall success rate: 63.5% on pick-and-place, 34% on non-PnP tasks, and 10.5% on the more challenging multi-step tasks. That spread is telling: zero-shot transfer is promising, and the hardest tasks are still hard. The combination of glove-grounded actions and embodiment alignment is what I’ll be watching. Curious to see how this develops.

2026.11.04 04:21

What stands out to me about Liber-0 is the attempt to make human experience useful to robots, not just collect more data. It was tested on 60 tasks (600 trials), with a 36% overall success rate: 63.5% on pick-and-place, 34% on non-PnP tasks, and 10.5% on the more challenging multi-step tasks. That spread is telling: zero-shot transfer is promising, and the hardest tasks are still hard. The combination of glove-grounded actions and embodiment alignment is what I’ll be watching. Curious to see how this develops.

LiberAI@liberai_robot

2026.11.04 02:17

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. Technical blog: