Synthetic training data. Sometimes it's cheaper / safer / easier to work with simulated data rather than real world sensor data. For some types of machine learning, a simulation is "real enough".

Someone asked me to build a startup doing the same. His most convincing use case was training camera systems to detect people falling overboard on cruise ships, etc. It's impractical / dangerous to use real world camera data for that.

There are other advantages, e.g., being able to generate simulations where everything is already labeled.