>> However the idea that you could learn from synthetic data doesn't make sense, as you could just literally use the model that generates the data in the first

>> However the idea that you could learn from synthetic data doesn't make sense, as you could just literally use the model that generates the data in the first place. If you're just learning known parameters, why waste the time training when you already have the answer? Hey, that's a really good point. But the synthetic data generators in the article are not statistical models, but 3d models. Even if it were possible to create a 3d model that is a 100% faithful likeness of some arbitrary human being, we'd still need some way to compare the 3d model to a human. Still, yeah, if we could simulate the real world with perfect fidelity we wouldn't need no machine learning.