Chess bots (like Stockfish) are trained on game samples, with the goal of predicting what search path to keep looking at and which moves will result in a win. You get game samples by playing the game, so it made sense to have stockfish play itself, since the input was always still generated by the rules of chess.

If a classifier or predictive model creates it's own data without tying it to the rules and methods in reality, they're going to become increasingly divorced from reality. If I had to guess, that's what the guy in the article is referencing when talking about "sanitizing" the data. Some problems, like chess, are really easy. Mimicking human speech? Probably not

[–] CanadaPlus@lemmy.sdf.org 5 points 7 months ago* (last edited 7 months ago)

Yeah, because the human developers know the rules of chess, so it's easy to generate or verify perfect quality games at massive scale. Natural language can't be tackled like that; certainly not yet, probably not ever. Many have tried and failed to parse natural language algorithmically, but at the end of the day it seems to rely heavily on loose conventions and endless shared experiences. So, you need content from the wild, or you're basically letting the AI mark its own homework.