"Adversarial examples are just one way to prove that deep learning fail at generalization"

Do you know what proof is? Adversarial examples demonstrate that there is one esoteric failure mode of current deep learning models, one that for all we know is present in human vision (we can't take derivatives with respect to the parameters of our own neurons). It will likely be solved in the next few years. At a minimum you start training on adversarially generated examples.

This response is absolute hyperbole and clearly devoid of any factual knowledge of the nature of deep conv nets and their properties.