That's a non-sequitur, they would be stupid to run ab expensive _L_LM for every ...

michaelt · 2025-03-25T21:00:12 1742936412

Yes, putting an expensive LLM response atop each search query would be quite stupid.

You know what would be even stupider? Putting a cheap, wrong LLM response atop each search query.

canucker2016 · 2025-03-25T19:22:17 1742930537

Google placed its "AI overview" answer at the top of the page.

The second result is this reddit.com answer, https://www.reddit.com/r/math/comments/32m611/logic_question..., where at least the numbers make sense. I haven't examined the logic portion of the answer.

Bing doesn't list any reddit posts (that Google-exclusive deal) so I'll assume no stackexchange-related sites have an appropriate answer (or bing is only looking for hat-related answers for some reason).

moritzwarhier · 2025-03-25T19:39:24 1742931564

I might have been phrasing poorly. With _L_ (or L as intended), I meant their state-of-the-art model, which I presume Gemini 2.5 is (didn't come around to TFA yet). Not sure if this question is just about model size.

I'm eagerly awaiting an article about RAG caching strategies though!