Autosorting, fuzzy search, document analysis, identifying posts with the same topic, and sentiment analysis all benefit from AI's soft input handling.
I do NOT want search to become any fuzzier than it already is.
See the great decline of Google's search results, which often don't even have all the words you're asking about and likely omits the one that's most important, for a great example.
It might be that it's worth it to bifurcate soon. Search indexes and AI engines, doing different roles. The index would have to be sorted with AI though - to focus on original and first-party material and to downrank ad-driving slop.
> I do NOT want search to become any fuzzier than it already is.
For a specialized shop site you may want it. Search term: "something 150", the client is looking for a 1.5m something, if you're doing an exact text search your search engine will give you a lot of noise. Or you'll have to fiddle with synonyms, dictionaries and how you index your products with a huge chance to break other types of search queries.
Gemini 2.5 pro is basically free.
Also watsonx, but that's b2b.
And depending on the client vertical they tend to not use the same vocabulary when looking for products.
But contrary to some other comments I know LLM are not magical tools and anything we use will require data to fine tune whatever base model we choose. And it will be used on top of standard text search not as a full replacement. I'm sure many companies are currently doing the exact same thing or will be soon enough.