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ameliustoday at 1:11 PM4 repliesview on HN

Can anyone explain why LLMs are so bad at finding products (their webpages) with given specifications?

You'd think they would have solved it by now.


Replies

simonwtoday at 1:51 PM

LLMs aren't architected to handle filter-style comprehensive search without setting them up with additional tools.

Asking an LLM for a list of every county in the USA for example, or every county with a population of more than 100,000 people.

Even if those county names and their populations are mixed up in their weights, the nature of next-token-prediction does not lend them to effectively answering comprehensive, detailed questions like that.

An agent system build on top of an LLM can do it, if it has access to tools which can help access eg a table of counties and then filter them with SQL or Pandas or similar.

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braiamptoday at 1:17 PM

Because that's structured data and structured data is usually hidden away from users _and_ machines. Product rarely want to be honest, unless it's B2B in a very competitive market (and even then!). So, yeah, it's not that they are bad, it's that there are few good sources of information.

(Lets ignore for now that no one seems to agree to what should be the spec sheets)

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_fluxtoday at 1:29 PM

Amazon Rufus has been mildly successful for me. I think the failures I've experienced with it are mostly because the product I'm looking for doesn't exist in the catalog.

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wslhtoday at 1:26 PM

Because the data, in general, is not included in the LLM model and it needs to search/browse for external information. It cannot look indefinitely so it get the top results from lists, not "evrything".