Warehouse robots underperform in production not because of the model, but because training data missed the edge cases that matter.
Sub-millimeter precision, HIPAA compliance, and credentialed operators — surgical robot data has requirements general robotics programs cannot meet.
Robotics data quality is not a review meeting. At production scale it is automated validation, per-operator metrics, and same-day feedback loops.
Robot annotation is not image labeling with a new name. Temporal structure and task semantics demand distinct tooling and annotator qualification.
Simulation offers unlimited training data at zero cost. The sim-to-real gap is a structural problem, not a rendering one.
Language models scaled on internet data. Embodied AI must build its data from the physical world — and that changes everything.
