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PaperclipPerfector  4d ago (text post)   18584 thread views

Culture War Roundup for the week of April 13, 2026

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I'm sure rov wants to search by concept or something not keyword.

I understand. Modern LLMs have not meaningfully impacted search at all. Our ability to semantically search documents in a particular technical domain has not advanced tremendously in the last decade. word2vec (2012) and BERT (2017) were both meaningful step changes (but only a small step). Nothing in the generative/LLM era has meaningfully impacted search.

I want to know how this is going to impact things when one side is using it to write and distribute memo's and other corporate information and the other side is using it to summarize and automate replies to said information and 'no' side in reality is paying attention to what the other is doing. The rift and chasm I imagine opening up is going to being chaos to organizations and cause more harm than it solves.

I read a story the other day about how new candidates on the job market are using them to build their resumes and in response HR departments are using them in tandem with the applicant tracking systems (ATS) to filter through candidates and reject the ones that are suspected to be influenced by an AI / LLM. It's a lose / lose proposition for both parties in the long run.

I would argue that there's a tremendous gulf in capability between the post-bert world of embeddings plus cross encoder rankings, and the ancient days of 2010.

I agree that the genai era does shit for search though, we barely addressed the needle in the haystack problem, let alone asking more complex queries. And LLMs are horrendously incapable of returning all matches for a query, even a super simple one.

Keyword search doesn't even require AI.

LLMs aren't needed for that:

https://en.wikipedia.org/wiki/Concept_search

They don't work well and have been obsoleted by newer llm based techniques, mostly bert based (not to be confused with gpt/genai)

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