Comment by jcranmer
2 hours ago
The first casualty of LLMs was the slush pile--the unsolicited submission pile for publishers. We've since seen bug bounty programs and open source repositories buckle under the load of AI-generated contributions. And all of these have the same underlying issue: the LLM makes it easy to do things that don't immediately look like garbage, which makes the volume of submission skyrocket while the time-to-reject also goes up slightly because it passes the first (but only the first) absolute garbage filter.
I run a small print-on-demand platform and this is exactly what we're seeing. The submissions used to be easy to filter with basic heuristics or cheap classifiers, but now the grammar and structure are technically perfect. The problem is that running a stronger model to detect the semantic drift or hallucinations costs more than the potential margin on the book. We're pretty much back to manual review which destroys the unit economics.