Robotics
Robot learning, embodied AI and robot foundation models. 5 notes.
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Robot-Use Agents: When Frontier Models Leave the Screen
Robot-use agents use language models, skills, physical prompts and verified trials together, with constraints from contact, latency and hardware protection.
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From Human Video to Robot Action: Five Interfaces Across the Embodiment Gap
Compare five methods for learning robot actions from human video. They include latent actions and contact-aware retargeting, with different tasks and evaluations.
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Embodied AI World Models
Robot world models connect prediction and action. This guide examines representations, planning, policy learning, aligned data, uncertainty and deployment.
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From π0 to π0.7: A Tutorial on Open-pi and Robot Foundation Models
The tutorial examines Physical Intelligence’s open-pi work: continuous action chunks, robot transfer, context, memory, feedback and real-time control.
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On 3D, Video World Models, and the Approaching ImageNet Moment of Perception-Action Learning
This article examines 3D geometry and video world models for perception-action learning. It gives proposed ImageNet-style transfer tests for robotics.
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