Recently, some impressive feats have been achieved with deep neural networks, including object classification that exceeds human performance, and of course the much-discussed victory of the computer program AlphaGo over human Go champion Lee Sedol. Clearly, to reach human-level intelligence, what we need is a deep neural network with a number of connections equivalent to that present in the human brain, right? Deep neural networks bridge the semantic gap between classical computer systems, where symbolic entities are defined in absolute terms in databases, and the fuzziness of the real world, where exceptions are the norm, and nothing can be entirely captured by absolute rules.