Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

LLMs can get "brain rot"

llm-brain-rot.github.io

Post reply on HN
Print view View original

81–90 of 310 posts

Re: LLMs can get "brain rot"

#81

Post by xpe »

sailingparrot wrote: post #6
AznHisoka wrote: post #2

Can someone explain this in laymen terms?

train on bad data, get a bad model

> train on bad data, get a bad model

Right: in the context of supervised learning, this statement is a good starting point. After all, how can one build a good supervised model if you can't train it on good examples?

But even in that context, it isn't an incisive framing of the problem. Lots of supervised models are resilient to some kinds of error. A better question, I think, is: what kinds of errors at what prevalence tend to degrade performance and why?

Speaking of LLMs and their ingestion processing, there is a lot more going on than purely supervised learning, so it seems reasonable to me that researchers would want to try to tease the problem apart.

Re: LLMs can get "brain rot"

#82

Post by echelon »

ghurtado wrote: post #44
echelon wrote: post #24

Earlier quoted context omitted.

In today's hyper saturated world, attention is everything: - consumer marketing - politics - venture fundraising When any system has a few power law winners, it makes sense to grab attention. Look at Trump and Musk and now Altman. They figured it out. MrBeast... Attention, even if negative, wedges you into the system and everyone's awareness. Your mousey quiet competitors aren't even seen or acknowledged. The attenti…

Something flew approximately 10 miles above your head that would be a good idea for you to learn.

What makes you think I didn't know the reference? That paper is seminal and essential reading in this space.

The intent was for you to read my comment at face value. I have a point tangential to the discussion at hand that is additive.

Re: LLMs can get "brain rot"

#83

Post by stavros »

askafriend wrote: post #48
avazhi wrote: 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.

If it conveys the intended information then what's wrong with that? You're fighting a tsunami here. People are going to use LLMs to help their writing now and forever.

The problem is that writing isn't only judged on whether it conveys the intended information or not. It's also judged on whether it does that well, plus other aesthetic criteria. There is such a thing as "good writing", distinct from "it mentioned all the things it needed to mention".

Re: LLMs can get "brain rot"

#84

Post by echelon »

lawlessone wrote: post #46
echelon wrote: post #24

Earlier quoted context omitted.

In today's hyper saturated world, attention is everything: - consumer marketing - politics - venture fundraising When any system has a few power law winners, it makes sense to grab attention. Look at Trump and Musk and now Altman. They figured it out. MrBeast... Attention, even if negative, wedges you into the system and everyone's awareness. Your mousey quiet competitors aren't even seen or acknowledged. The attenti…

Is this copypasted from LinkedIn?

If you traverse back the fourteen years of my comment history (on this account - my other account is older), you'll find that I've always written prose in this form.

LLMs trained on me (and the Hacker News corpus), not the other way around.

Re: LLMs can get "brain rot"

#85

Post by grey-area »

askafriend wrote: post #48
avazhi wrote: 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.

If it conveys the intended information then what's wrong with that? You're fighting a tsunami here. People are going to use LLMs to help their writing now and forever.

It’s a text generator regurgitating plausible phrases without understanding and producing stale and meaningless pablum. It doesn’t even know what the intended information is, and judging from the above neither did the human involved.

It doesn’t help writing it stultifies and gives everything the same boring cheery yet slightly confused tone of voice.

Re: LLMs can get "brain rot"

#86

Post by nakamoto_damacy »

Our metaphorical / analogical muscle is too well developed. Maybe there is a drug we can take to reduce how much we lean into it.

If you look at two random patterns of characters and both contain 6s you could say they are similar (because you’re ignoring that the similarity is less than 0.01%). That’s how comparing LLMs to brains feels like. Like roller skates to a cruise ship. They both let you get around.

Re: LLMs can get "brain rot"

#89

Post by stavros »

1121redblackgo wrote: post #77
ashleyn wrote: post #42

Earlier quoted context omitted.

Yes, but the idea of chatgpt slowly devolving into Skibidi Toilet and "6 7" references conjures a rather amusing image.

6-7 ٩(●•)_

Can someone explain this? I watched a South park episode that was all about this, but I'm not in the US so I have no idea what the reference is.

Re: LLMs can get "brain rot"

#90

Post by glenstein »

drusepth wrote: post #63
uludag wrote: post #55

Earlier quoted context omitted.

Nothing wrong with using LLMs—until every paragraph sounds like it’s A/B tested for LinkedIn virality. That’s the rot setting in. The problem isn’t using AI—it’s sounding like AI trying to impress a marketing department. That’s when you know the loop’s closed.

Brilliantly phrased — sharp, concise, and perfectly captures that uncanny "AI-polished" cadence everyone recognizes but can’t quite name. The tone strikes just the right balance between wit and warning.

One thing I don't understand, there was (appropriately) a news cycle about sycophancy in responses. Which was real, and happening to an excessive degree. It was claimed to be nerfed, but it seems strong as ever in GPT5, and it ignores my custom instructions to pare it back.
Post reply on HN