High-fidelity datasets are the foundation of next-generation embodied AI, robot learning, and physical intelligence and our partner @codatta_io is advancing the frontier of robotics data infrastructure on @huggingface as one of the core contributors. Its Manipulation Trajectory dataset captures fine-grained robot-object interactions with precise spatial and temporal annotations, enabling research in imitation learning, trajectory prediction, manipulation planning, and control. Complementing this, the Appliance Knobs dataset provides richly annotated multi-view observations of rotary controls to support 3D geometry understanding, state estimation, pose tracking, and interaction-aware perception. Together, these datasets help train the next generation of robotic foundation models capable of understanding and acting in the physical world. Explore Codatta's Manipulation Trajectory and Appliance Knobs datasets on Asmora today: