  Terry Sejnowski's 2020 paper [arXiv:2002.04806] is entitled "The unreasonable
effectiveness of deep learning in artificial intelligence". However, the paper
doesn't attempt to answer the implied question of why Deep Convolutional Neural
Networks (DCNNs) can approximate so many of the mappings that they have been
trained to model. While there are detailed mathematical analyses, this short
paper attempts to look at the issue differently, considering the way that these
networks are used, the subset of these functions that can be achieved by
training (starting from some location in the original function space), as well
as the functions to which these networks will actually be applied.
