The difference with deep neural networks is that they can do so much of their own feature generation. It's very different to bayesian networks or SVMs. Because

The difference with deep neural networks is that they can do so much of their own feature generation. It's very different to bayesian networks or SVMs. Because they can create their own features (to a large extent) they can handle unstructured data more simply and more accurately. Neural nets are dramatically improving every month. Recently, the major developments have been around using a wider variety of differentiable functions as layers in the network - see for example Spatial Transformer Networks, and also the more general architectures such as Neural Turing Machines.