Probabilistic computing deals with implementation of probabilistic algorithms, models, and methods for computation. It aims to build systems that can reason about and handle uncertainty, making probabilistic predictions about the world and making decisions based on those predictions.
Probabilistic inference algorithms are techniques used to compute probabilities of events or variables in the presence of uncertainty. This is a kind of a reverse process going backwards from observations to the hidden and latent variables.
This is exponentially hard and scientists have resorted to methods like MCMC, Variational Inference, Expectation-Maximization etc.
Automatski can do this deterministically. The entire set of problems in the implementation of Probabilistic Computing & Inference has been vanquished.