I was reading this book about deep learning by Ian and Aron. In the description of DBN they says DBN has fallen out of favor and is rarely used.
Deep belief networks demonstrated that deep architectures can be successful, by outperforming kernelized support vector machines on the MNIST dataset ( Hinton et al. , 2006 ). Today, deep belief networks have mostly fallen out of favor and are rarely used, even compared to other unsupervised or generative learning algorithms, but they are still deservedly recognized for their important role in deep learning history.
I don't understand why.