In my view, all results should be expressible in the form: because the real world data exhibits empirical structure X, algorithm Y succeeds in describing/predicting it.
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.
In fact, this algorithmic difficulty is an issue that many researchers are currently grappling with, so in practice you really shouldn't expect all results to be making a novel statement about how the world works. 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, especially human-comprehensible AI which might possibly be friendly.
Maybe we are wrong, but the argument you gave, and your implications about how NFL should be applied, are not really relevant to that question.
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 ...
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.