alt Hacker NewsThat's not what I meant at all. I understand no one would want 1:1 text search, and part of the reason why Google won in the 90s was because of PageRank. All I was saying was that basing a 'search engine' on a CoT LLM is very inefficient.
>LLMs designed and deployed properly are infinitely better at this than keyword search engines are, despite being less predictable.
In what way? How are LLMs more efficient and 'infinitely' better at this than what Google had before AI overviews? If anything, I find that search results have gotten worse.
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That’s not what they’re doing either though. If I’m correctly informed, they are still running bog-standard Google searches under the hood and letting the LLM find the relevant stuff in them. It’s a bit of a godsend not having to do it yourself since the original results’ quality tanked so much. And kinda elegant from an algorithmic perspective actually.
It’s still not as good as actually searching the web semantically as I used to often find myself wanting to get rid of results that sounded vaguely like my search term but actually completely missed the point, but it makes it somewhat bearable again.
Something like: An LLM can encode a query into a vector to match against a vector database of indexed pages.
You have to actually engineer that though, you can't just throw random stuff into ChatGPT and expect good results.