Sometimes, deep learning is too simple to actually work. (complex games with hidden state, exploration, generating art, decision making etc.) Those use cases a

Sometimes, deep learning is too simple to actually work. (complex games with hidden state, exploration, generating art, decision making etc.) Those use cases are in constant flux and research. (Though teams like DeepMind are making some serious inroads.) Other problem is that DL is still highly sample inefficient - it needs many more examples than you'd want or sometimes even have to bootstrap.