[vibrio_bobtail]

I wouldn't contrast it with machine learning or deep learning. Probabilistic programming is focused on building languages or libraries that incorporate fundamental probabilistic building blocks, model building statements and inference strategies as first class citizens within the language. Its been remarkably successful, check out Stan, Pyro, PyMC, Tensorflow Probability, JAGS, BUGS and Turing as very successful projects that have been used to tackle challenging and diverse problems with probabilistic modeling . The more modern probabilistic programming languages are actually designed to incorporate the advances of deep learning by making it easy to embed ANNs into models by using them to parameterize random variables, Pyro and Tensorflow Probability are probably the best examples of this.