On the discovery progress, we can't look at all 200M papers with the LLM, so we prioritize some of them (the first 100 most promising) for deep analysis. Within those, we find a few that are relevant. But the rate at which we discover these tells us roughly what will happen if we read the next 100 (if we're discovering new relevant papers all the time, we will likely continue). We need a better explanation on the website, but we can statistically model this to quantitatively predict how many papers we would find if we exhaustively searched the whole database.
More info here: https://www.undermind.ai/static/Undermind_whitepaper.pdf