How PsiBot Uses 100,000 Hours of Human Data to Power Embodied Intelligence

PsiBot demonstrates that, with a 100,000‑hour human‑operation dataset captured via exoskeleton gloves and ego‑vision, a world‑model (W0) and reinforcement‑learning policy (R2) can bridge the gap to robot control, offering a scalable alternative to costly teleoperation pipelines.

Embodied AIRoboticsdata collection

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How PsiBot Uses 100,000 Hours of Human Data to Power Embodied Intelligence

Machine Heart

Apr 11, 2026 · Artificial Intelligence

How 100,000 Hours of Human Data Propelled Psi‑R2 to Lead MolmoSpaces

Lingchu AI demonstrates that scaling human‑operation data to nearly 100,000 hours, combined with a two‑model system and reinforcement learning, can replace costly robot‑teleoperation data and achieve top performance on the MolmoSpaces benchmark.

Embodied AIPsi-R2Psi-W0

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How 100,000 Hours of Human Data Propelled Psi‑R2 to Lead MolmoSpaces