Simulation can generate robotics data at a scale physical hardware cannot easily match. But there is an obvious problem. The real world is not a simulator. Lighting changes. Objects move unexpectedly. Friction differs. People interfere. Environments are messy. This is why I think Sim to Real is one of the most important tests for @axisrobotics. Generating millions of simulated trajectories demonstrates scale. The harder question is whether training built from that pipeline eventually improves robot behavior outside simulation. That is where Physical AI becomes unforgiving. A model can look impressive inside a controlled environment and still fail when reality introduces something unexpected. Simulation may solve part of the scaling problem. Closing the gap between simulation and reality determines how valuable that scale ultimately becomes.