Probabilistic Programming and Model-Based Machine Learning

I would argue that for a human being, it's impossible to think of a process that generated the data without you thinking about it in causal terms. And so probabilistic programming is just a really, really easy way of going about that. They're all very kind of contextualized within the kinds of machine learning problems that somebody with a machine learning background might be used to. But they can be generalized to more deeper and more nuanced, more complex models.