I interpreted it as a roundabout way of increasing quality. Take any given subreddit. You have posts and comments, and scores, but what if the data quality is

I interpreted it as a roundabout way of increasing quality. Take any given subreddit. You have posts and comments, and scores, but what if the data quality isn't very good overall? What if instead of using it as is, you instead had an AI evaluate and reason about all the posts, and classify them itself based on how useful the posts and comments are, how well they work out in practice (if easily simulated), etc? Essentially you're using the AI to provide a moderated and carefully curated set of information about the information that was already present. If you then ingest this information, does that increase the quality of the data? Probably(?), since you're throwing compute and AI reasoning at the problem ahead of time reducing compute and lowering the low quality data by adding additional high quality data.