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It used to be garbage in, garbage out (GIGO). But now, sometimes you put valid data in and get garbage out. I just can't go all-in on LLMs with the error / ha
by jgalt212 3y ago
It used to be garbage in, garbage out (GIGO). But now, sometimes you put valid data in and get garbage out. I just can't go all-in on LLMs with the error / hallucinate rate where it currently is. And people say it's getting better. But I guess I'll just do things the slower, and more accurate way until such time arrives.
- yau8edq12i 3y ago"Garbage in, garbage out" means that if you feed garbage to your algorithm, then you're going to get garbage in return. It's always been a one-way implication. It doesn't mean that if you feed valid data, you're not going to get garbage.
- andersa 3y agoThe fun part is that with LLMs we can now sometimes put absolute garbage in and still get good results.