Classification is only one problem in machine vision. As in, not even 10% of the whole.

Edit: Btw I just had a look to confirm and what you're saying about "1000 equally balanced classes" is inexact, to put it midly. ImageNet has 100,000 SynSets (as in WordNet) and aims to have about 1000 images illustrating each. Individual images may illustrate several synsets- you don't get one image per class, say.

Also: AlexNet was not a cat recogniser and having unbalanced classes is a problem for machine learning, but not a dealbreaker, per se.