This isn't my area of expertise, but I've spoken to computer vision researchers who apparently use generated data for training models for self-driving vehicle a

This isn't my area of expertise, but I've spoken to computer vision researchers who apparently use generated data for training models for self-driving vehicle autonomy. Maybe they only use generated data for the train set and then do cross-validation on real data? I'd like to hear them chime in on this thread if any are reading here. Theoretically speaking if the generated data has the same distribution and parameters as the real data [1], and encodes similar nonparametric features like seasonality and user activity, I think generated data might be fine. [2] _________ 1. Admittedly tricky if you have limited data and no insight into the underlying population distribution/features, just those of the sample. But then you have a worse problem for modeling diagnostics anyway. 2. In the sense that anything is "fine", which is a spectrum that requires some critical skepticism in statistics. There are always caveats but it may still be robust and useful.