Even if I know the exact probability distribution over images, there is an algorithmic problem (namely, how to do the inference), so your view is definitely at least a little too extreme.
I don't dispute that the algorithmic problem is interesting and important. I only claim that the empirical question is equally important.
Applying this standard to current research would stall progress in the directions I (and I think most serious AI researchers) currently believe are most important to actually reaching AI
What you're really saying is that you think a certain direction of research will be fruitful. That's fine. I disagree, but I doubt we can resolve the debate. Let's compare notes again in 2031.
I searched the posts but didn't find a great deal of relevant information. Has anyone taken a serious crack at it, preferably someone who would like to share their thoughts? Is the material worthwhile? Are there any dubious portions or any sections one might want to avoid reading (either due to bad ideas or for time saving reasons)? I'm considering investing a chunk of time into investigating Legg's work so any feedback would be much appreciated, and it seems likely that there might be others who would like some perspective on it as well.