[samps]

(I'm the author of the lecture notes.) I totally agree, and this is an underappreciated view in the PP community. The hype says "you just write your model; you'll get inference for free," but that obscures that current languages do nothing to help with cooking up an efficient inference algorithm for a particular situation. That's still a hard problem. When the only inference algorithm anyone actually uses is some MCMC variant, I think that's a broken promise.

There's some chance we'll be able to find clever new ways to derive better inference algorithms in specific situations using program analysis, but I wouldn't hold my breath. And it's impossible, of course, for anything like that to work for every possible program in a Turing-complete language.

[dagss]

Thanks for confirming my suspicion. So would it be fair to say that PP is an interface to statistics, so that those who know how to code but not advanced stats can do stats without learning it? (On simple problems)

[samps]

As it stands, I'd agree with that---but the characterization definitely depends on who you talk to. I might be in the minority among "PP people," since the hype is still going strong and some smart people seem to see more potential than I (and you) do.