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Comment by jrochkind1 | Hacker News Reader

More LLM-generated text about LLMs.

Is anyone else actually finding it harder and harder to read LLM generated text? I find it quite tiring, my brain just does not want to get through it.

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Your brain is incredibly adept at pattern recognition; it doesn't focus on LLM-generated text for the same reason it doesn't stare at wallpaper.

We've all learnt that it's not really communication, and so can be dispensed with.

It’s largely because LLMs are reaching for many different types of adjectives or verbs in the same sentence, in a jarring way. While embedding it in a confidently declarative sentence. Everything sounds like some profound insight, dialed to an 11, but written as poetry. Especially those headings. With the short sentences.

I have to agree with you. Yet it is tiring, people don't even try anymore.

the biggest giveway is actually not the writing style, but the content

"using GPT-4o-mini for query rewriting" -> model from 2024, when RAG was trendy, and all the langchain, llama-index, etc, docs mentioned this specific model

GPT-4o-mini is still very relevant. It is a very capable model and very very fast and dirt cheap. Excellent for this type of stuff

author here. at most companies I've worked for recently (F500) RAG is still quite trendy. this was what frustrated me a bit and motivated to write this article - along with other experiences that definitely relate with some of the folks in the comments above

But you actually had an LLM write this article, no?

to be fully transparent, I used LLM to review my draft yes. and interestingly enough, this article had tens of thousands of more views and estimulated significantly more discussions than my other, non-LLM written articles. so there's that.

Why pretend? You mean your draft was the meat of the article and you had an LLM make it an article (sentences rather than bullet points?)

This is absolutely not a small draft review or edit.

So maybe it works! They are of course models distilling the best click-baity eyeball trapping engagement processes.

what I implied is that in 2024 a lot was written about RAG, LLMs were trained on it, and that explains your gpt-4o-mini reference. the argument is that the article is ai slop, and that point is totally unrelated to name dropping fortune 500s references

sorry if it came across as name dropping - the point I wanted to make is actually that F500s are chasing RAG (as in pure semantic search without any care for chunking strategies, evals etc) instead of starting with the basics.

and for the record, my last employer was still using gpt-4o and gpt-4o mini last year. and they are an F500 (not that it means anything, just for context).

But it's "trendy"

"This is where the real trade-off lives – not cost, but speed."

That is where I stopped

Everything that is generate from a LLM is shit, I don't know why people continue using it. I'm waiting for this bubble to explode once for all so we can return doing things in the sane way.

In the same boat here.

The enshittification of the web, now powered by AI.

I'm Becoming AI-Blind: https://news.ycombinator.com/item?id=49386699

VERY interesting, thank you! So it's not just me.

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