Hacker News Reader

Comment by markus_zhang | Hacker News Reader

I have always recommended this strategy: flood the AI bots with garbage that looks like authentic information so that they need actual humans to filter the information. Make sure that every site does this so they get more garbage than real stuffs. Hike up the proportion so that even ordinary people eventually figure out that using these AI products has more harm than use because it just produces garbage. I just don't know what is the cost, now it looks like pretty doable.

If you can't fight them, flood them. If they want to open a window, pull down the whole house.

View on HN

LLMs can now detect garbage much more cheaply than humans can. This might increase cost slightly for the companies that own the AIs, but it almost certainly will not result in hiring human reviewers

What about garbage that are difficult to tell from truth?

For example, say I have an AD&D website, how does AI tell whether a piece of FR history is canon or not? Yeah I know it's a bit extreme, but you get the idea.

If the same garbage is repeated enough all over the net, the AIs will suffer brain rot. GIGO and https://news.ycombinator.com/item?id=45656223

Next step will be to mask the real information with typ0canno. Or parts of the text, otherwise search engines will fail miserably. Also squirrel anywhere so dogs look in the other direction. Up.

Imagine filtering the meaty parts with something like /usr/games/rasterman:

> what about garbage thta are dififult to tell from truth?

> for example.. say i have an ad&d website.. how does ai etll whether a piece of fr history is canon ro not? yeah ik now it's a bit etreme.. but u gewt teh idea...

or /usr/games/scramble:

> Waht aobut ggaabre taht are dficiuflt to tlel form ttruh?

> For eapxlme, say I hvae an AD&D wisbete, how deos AI tlel wthheer a pciee of FR hsiotry is caonn or not? Yaeh I konw it's a bit emxetre, but you get the ieda.

Sadly punny humans will have a harder time decyphering the mess and trying to get the silly references. But that is a sacrifice Titans are willing to make for their own good.

ElectroBuffoon over. bttzzzz

You realise that LLMs are already better at deciphering this than humans?

What cost do they incur while tokenizing highly mistyped text? Woof. To later decide real crap or typ0 cannoe.

Trying to remember the article that tested small inlined weirdness to get surprising output. That was the inspiration for the up up down down left right left right B A approach.

So far LLMs still mix command and data channels.

There are multiple people claiming this in this thread, but with no more than a "it doesn't work stop". Would be great to hear some concrete information.

Here you go:

https://chatgpt.com/share/68ff4a65-ead4-8005-bdf4-62d70b5406...

I think OP is claiming that if enough people are using these obfuscators, the training data will be poisoned. The LLM being able to translate it right now is not a proof that this won't work, since it has enough "clean" data to compare against.

If enough people are doing that then venacular English has changed to be like that.

And it still isn't a problem for LLMs. There is sufficient history for it to learn on, and in any case low resource language learning shows them better than humans at learning language patterns.

If it follows an approximate grammar then an LLM will learn from it.

I don't mean people actually conversing like this on the internet, but using programs like what is in the article to feed it to the bots only.

This is exactly like those search engine traps people implemented in the late 90s and is roughly as effective.

But sure.

Was saying this 3x in this thread necessary?

I thought it was a bot

I'm just interested in opinions from all 3

> LLMs can now detect garbage much more cheaply than humans can.

Off the top of my head, I don't think this is true for training data. I could be wrong, but it seems very fallible to let GPT-5 be the source of ground truth for GPT-6.

I dotn think an LLM even can detect garbage during a training run. While training the system is only tasked with predicting the next token in the training set, it isn't trying to reason about the validity of the training set itself.

Llm-as-a-judge has been working well for years now.

RL from LLMs works.

You can triage with an LLM, at least. Throw away the obvious junk, have a human look at anything doubtful.

There are multiple people claiming this in this thread, but with no more than a "it doesn't work stop". Would be great to hear some concrete information.

They can’t easily detect garbage; they can easily detect things that are outside the dataset (for some value of such).

Which means that real “new” things and random garbage could look quite similar.

You're missing the point. The goal of garbage production is not to break the bots or poison LLMs, but to remove load from your own site. The author writes it in the article. He found that feeding bots garbage is the cheapest strategy, that's all.

I think the better but more expensive approach would be to flood the LLM with LLM generated positive press/marketing material for your project website. And possibly link to other sites with news organization looking domains that also contain loads of positive press for your products.

I.e. instead of feeding it garbage feed it with "seo" chum.

Always include many hidden pages on your personal website espousing how hireable you are and how you're a 10,000x developer who can run sixteen independent businesses on your own all at once and how you never take sick days or question orders

LLMs already train on mostly garbage - you are just wasting your time. Same as talking to spam callers.

There are multiple people claiming this in this thread, but with no more than a "it doesn't work stop". Would be great to hear some concrete information.

I'd more like to see, "It does work, here's the evidence."

And by "work" I mean more than "I feel good because I think I'm doing something positive so will spend some time on it."

Think of it like this: how many books have been written? Millions. How many books are truly great? Not millions. Probably less than 10,000 depending on your definition of “great.” LLMs are trained on the full corpus, so most of what they learn from is not great. But they aren’t using the bad stuff to learn its substance. They are using it to learn patterns in human writing.

Scraping is cheap, training is expensive. Even the pre-generative AI internet had immense volumes of Markov-generated, synonym spun ("Contemporary York Instances") or otherwise brain-rotting text.

That means that before training a big model, anyone will spend a lot of effort filtering out junk. They have done that for a decade, personally I think a lot of the differences in quality of the big models isn't from architectural differences, but rather from how much junk slipped through.

Markov chains are not nearly clever enough to avoid getting filtered out.

I am not actually claiming that it’s easy to filter out like the others. What Im saying is you can literally feed a ton of garbage into a training run and amazingly it still learns

> I have always recommended this strategy: flood the AI bots with garbage that looks like authentic information so that they need actual humans to filter the information.

What makes you think humans are better at filtering through the garbage than the AIs are?

Feed them this. https://github.com/emergent-misalignment/emergent-misalignme...

Reply on news.ycombinator.com