[anon8]

After stating their hypothesis the authors disclaim the issues CNNs with the following:

... we feel the need to stress that it is not fair to compare the generalization performance of CNN to a human being. In contrast to a CNN, a human being is exposed to an incredibly diverse range of lighting conditions, viewpoint variations, occlusions, among a myriad of other factors.

Why is it that evolutionary heritage is so rarely stated as an important factor in these comparisons (as far as I have seen)? I appreciate that evolution can be framed as another form of learning, but it is much more powerful than that employed by standard CNNs, in that it can change the network structure (and the I/O interface) as well as the network weights.