Timothy Lee: I wonder if “medium quality papers” have any value at the margin. There are already far more papers than anyone has time to read. The point of research is to try to produce results that will stand the test of time.
The theory with human researchers is that the process of doing medium quality research will enable some researchers to do high quality research later. But ai “researchers” might just produce slop until the end of time.
I think medium quality papers mostly have negative value. The point of creating medium quality papers is that it is vital to the process of creating high quality papers. In order to get good use out of this style of tool we will need excellent selection. Or we will need actually successful self-improvement.
I think this misunderstands how modern science, and especially how ML research, works. My impression from having been in / around the field for a decade now and following the literature relatively closely is that most of the gains have come from ‘piling on’ iterative, relatively small improvements. Lots of relatively ‘medium quality papers’ (in terms of novelty, at least; relatively good, robust empirical evaluation might be more important) are the tower on which systems like GPT-4 stand.
I think this misunderstands how modern science, and especially how ML research, works. My impression from having been in / around the field for a decade now and following the literature relatively closely is that most of the gains have come from ‘piling on’ iterative, relatively small improvements. Lots of relatively ‘medium quality papers’ (in terms of novelty, at least; relatively good, robust empirical evaluation might be more important) are the tower on which systems like GPT-4 stand.