What are the tentative predictive features that Kagi has identified to-date in the StopSlop initiative, which differentiate search results that are "AI Slop" versus "Not AI Slop"?
Fxgn may be right: it could be more useful to think about the problem as "Slop" versus "Not Slop." Additionally, from a practical model development perspective, solving the "Slop"/"Not Slop" problem might be less challenging than solving the "AI Slop"/"Not AI Slop" problem, if "AI Slop" and "Human Slop" share common variance.