@GreatBigTable@mastodon.social
2026-09-07 21:57 UTC
@troed@swecyb.com @eff@mastodon.social I am talking about overfitting. That case has existed in models pushed to the public by frontier AI labs and is the basis of cases against them by orgs like the New York Times.
Overfitting may not be the desired outcome, but it is inherent in the technology if not accounted for. The problem for the labs is if their weights make outputs too far from source text, they can get less useful results. If they adhere too close to the original source, it could lead to legal trouble.
Replies (1)
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@troed@swecyb.com 2026-09-08 05:18
@GreatBigTable@mastodon.social No, that's not at all how LLM training works. Again, the proof is what I posted. Overfitting is extremely rare - simply because there's not room in the models for it to be common. @eff@mastodon.social