MCMC for big datasets -- faster sampling with JAX and the GPU

You'll often hear people say that MCMC is too slow for big datasets. For the very biggest datasets with millions of observations, there may be some truth to that. But the developers of PyMC and Stan are constantly refining their samplers, and it's now possible to fit models to much bigger datasets than you might think. In particular, since the PyMC developers introduced it a bit over a year ago, I've been really excited about PyMC's JAX support. I've been a fan of JAX for years and think that it's a great platform for Bayesian modelling.