horse911

Not an either-or situation. Many ML algorithms can be formulated in a probabilistic way, and PPLs can represent them. But the choice of the underlying inferential algorithm (MCMC, variational, etc) greatly affects the scale and type of solvable problems, so it's not just the language itself.

PPLs using MCMC (e.g., Stan and pymc) are first-choice tools for Bayesian inference on small to medium data analysis, which is lots more common than Google-scale data analysis.