In applied machine learning not so much. They feel ancient! But some use them to study the physics of computation. They were used to make the connection between renormalization group (RG) and machine learning. RG is one of the main workhorses of quantum field theory and condensed matter physics. The fact that there's a mapping from RG to RBMs means that we can understand how deep learning works by using the same techniques that modern physicists use to understand the world! Here's a nice article on this topic if you're interested https://www.quantamagazine.org/20141204-a-common-logic-to-se...