The point is that there are many different universal function approximators, so just that adds no value to explaining why NNs are good. This type of theory is m

The point is that there are many different universal function approximators, so just that adds no value to explaining why NNs are good. This type of theory is meaningful (because it's harder to have taken anything as complex as multi-layer perceptron seriously without it back in the 80s), but it's not a fact that's going to help us make any progress nowadays. Mentioning it over and over again just distracts us from the real problems we need to address.