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LLMs can get "brain rot"

llm-brain-rot.github.io

171–180 of 310 posts

Re: LLMs can get "brain rot"

#171

Earlier quoted context omitted.

The em dash usage conundrum is likely temporary. If I were you, I’d continue using them however you previously used them and someday soon, you’ll be ignored the same way everybody else is once AI mimics innumerable punctuation and grammatical patterns.

They didn't always em-dash. I expect it's intentional as a watermark. Other buzzwords you can spot are "wild" and "vibes".

So if the vibes are wild, I’m not a hippie but an AI ? Cool. Is that an upgrade or &endash; or not ?

Re: LLMs can get "brain rot"

#173

Earlier quoted context omitted.

I think this article has already made the rounds here, but I still think about it. I love using em dashes! It really makes me sad that I need to avoid them now to sound human https://bassi.li/articles/i-miss-using-em-dashes

> I love using em dashes Keep using them. If someone is deducing from the use of an emdash that it's LLM produced, we've either lost the battle or they're an idiot. More pointedly, LLMs use emdashes in particular ways. Varying spacing around the em dash and using a double dash (--) could signal human writing.

it's a shibboleth. In the same way we stopped using Pepe the frog when it became associated with the far right, we may eschew em dashes when associated with compuslop

Re: LLMs can get "brain rot"

#175

Earlier quoted context omitted.

If they wanted to watermark (I always felt it is irresponsible not to, if someone wants to circumvent it that's on them) - they could use strategically placed whitespace characters like zero-width spaces, maybe spelling something out in Morse code the way genius.com did to catch google crawling lyric (I believe in that case it was left and right handed aposterofes)

Which could be removed with a simple filter. em dashes require at least a little bit of code to replace with their correct grammar equivalents.

The replacement doesn't have to be "correct" -- does it?

Re: LLMs can get "brain rot"

#176

Earlier quoted context omitted.

Same here. I recently learned it was an LLM thing, and I've been using them forever. Also relevant: https://news.ycombinator.com/item?id=45226150

> I’ve been using them forever. Many other HN contributors have, too. Here’s the pre-ChatGPT em dash leaderboard: https://www.gally.net/miscellaneous/hn-em-dash-user-leaderbo...

This would be a pretty hilarious board for anyone who likes the em-dash and who has had many fairly active accounts (one at a time) on here due to periodically scrambling their passwords to avoid getting attached to high karma or to take occasional breaks from the site. Should there be such people.

Re: LLMs can get "brain rot"

#177
post #66

Earlier quoted context omitted.

What you are obsessing with is about the writer's style, not its substance. How sure are you if they outsourced the thinking to LLMs? Do you assume LLMs produce junk-level contents, which contributes human brain rot? What if their contents are of higher quality like the game of Go? Wouldn't you rather study their writing?

Writing is thinking, so they necessarily outsourced their thinking to an LLM. As far as the quality of the writing goes, that’s a separate question, but we are nowhere close to LLMs being better, more creative, and more interesting writers than even just decent human writers. But if we were, it wouldn’t change the perversion inherent in using an LLM here.

Have you considered a case where English might not be the authors' first language? They may have written a draft in their mother tongue and merely translated it using LLMs. Its style may not be many people's liking, but this is a technical manuscript, and I would think the novelty of the ideas is what matters here, more than the novelty of proses.

Re: LLMs can get "brain rot"

#180
post #47

“Studying “Brain Rot” for LLMs isn’t just a catchy metaphor—it reframes data curation as cognitive hygiene for AI, guiding how we source, filter, and maintain training corpora so deployed systems stay sharp, reliable, and aligned over time.” An LLM-written line if I’ve ever seen one. Looks like the authors have their own brainrot to contend with.

I think using large language models really accelerates mental atrophy. It's like when you use an input method for a long time, it automatically completes words for you, and then one day when you pick up a pen to write, you find you can't remember how to spell the words. However, the main point in the article is that we need to feed high-quality data to large language models. This view is actually a consensus, isn't it? Many agent startups are striving to feed high-quality domain-specific knowledge and workflows to large models.
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