When training robots, flawless runs aren't actually the most valuable thing. The real unlock in @axisrobotics task design is Post-training Correction, you step in right when the robot model gets stuck or messes up, and manually guide it out. That recovery moment is where the model actually learns. You can't just spam movements eitherthere’s a strict Quality Score running under the hood. Jittery inputs, hesitation, and sloppy paths get filtered out immediately. Only smooth, successful trajectories hit the score threshold and get recorded on Base. Junk data goes straight to the trash. Running MuJoCo locally via WASM in the browser makes this actually usable. Zero server lag, so your micro adjustments land with real-time reflex precision. Physical AI doesn't need infinite raw inputs; it needs clean, human corrected edge cases.