That&#x27;s mostly tautological: the networks you call &quot;deep&quot; are the ones that use more layers. Unless you need funding or media attention, in which case you call everything &quot;deep&quot;.<p>But you&#x27;re making it sound like shallow networks are a thing of the past. I would compare this to the field of NLP, where it seems we don&#x27;t have a good general idea what to do with deep networks, and the things that work so far are mostly shallow.<p>word2vec is one layer plus a softmax. GloVe is similar to a one-layer network. char-rnn seems to do as well with two layers as it does with three. All the gradient-descent classifiers out there are equivalent to one-layer networks.