Metrics that prove sim-to-real gap closing
Track deployment KPIs on targeted real slices before declaring sim-to-real victory.
Insights
From the field
Practical guidance for teams building real-world robotics data programs.
Teleoperation capture best practices for imitation learning
Small teleop pilot mistakes become expensive at scale, calibrate early.
Building evaluation benchmarks from real-world tails
Benchmarks copied from training distributions hide failures you will see in production.
Privacy and consent for on-site robotics capture
On-site capture needs clear consent, minimization, and transfer controls, not afterthoughts.
Running robotics data collection like a production pipeline
Pilots, QA gates, and operator runbooks turn one-off demos into reliable data supply.
What "good" physical AI data looks like
Episode volume alone does not predict deployment success, sync, calibration, and tail coverage matter.