I fully agree. The synthesized data itself is of no value, the value is in mapping the correlations and dependencies. But using a neural network to model the dependencies is basically cheating as you don't end up with a model, only a number spewing orifice. It's like Isaac Newton publishing a lookup table of falling times of spheres of different weights with no accompanying formula.
