Our wetware neutral networks probably aren’t supposed to engage with synthetic content like this either. In a few years we’re gonna learn that overexposure to AI generated content creates some sort of neurological problem in people, like a real-world “nerve attenuation syndrome” (Johnny Mnemonic).
I’ve read some snippets of AI written books and it really does feel like my brain is short circuiting
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What would make me think that they haven’t “thoroughly dissected” it yet is that I’m a skeptic, and since I’m a skeptic I don’t immediately and without evidence believe that every industry is capable of identifying, dissecting, and solving every problem with its products.
Ironically given their skillset, training an ML model on known and properly tagged AI generated and non-AI-generated stuff might actually work.
More like degenerative AIs
Good riddance.
The solution for this is usually counter training. Granted my experience is on the opposite end training ai vision systems to id real objects.
So you train up your detector ai on hand tagged images. When it gets good you use it to train a generator ai until the generator is good at fooling the detector.
Then you train the detector on new tagged real data and the new ai generated data. Once it’s good at detection again you train the generator ai on the new detector.
Repeate several times and you usually get a solid detector and a good generator as a side effect.
The thing is you need new real human tagged data for each new generation. None of the companies want to generate new human tagged data sets as it’s expensive.
Old news? Seems to be a subject of several papers for some time now. Synthetic data has been used successfully already for very specific domains.
Yup, old news and wrong news. Also so many people who hate AI but don’t understand how it works. Pretty disappointing for a technology community.
…………………. Good?
I was very interested in the thumbnail of this post so I did a little digging and found this: The PDF to the Paper where the whole picture is
Wow, it’s amazing that just 3.3% of the training set coming from the same model can already start to mess it up.
I’ve been assuming this was going to happen since it’s been haphazardly implemented across the web. Are people just now realizing it?
People are just now acknowledging it. Execs tend to have a disdain for the minutiae. They’re like kids that only want to do the exciting bits. As a result things get fucked because they don’t really understand what they’re doing. As Muskrat would say “move fast and break things.” It’s a terrible mindset.
“Move Fast and Break Things” is Zuckerberg/Facebook motto, not Musk, just to note.
Oh, I stand corrected
It is very much the motto this idiot lives by. He just wasn’t the first to coin that phrase.
No, researchers in the field knew about this potential problem ages ago. It’s easy enough to work around and prevent.
People who are just on the lookout for the latest “aha, AI bad!” Headline, on the other hand, discover this every couple of months.
This sounds like AI is literally biting its own tail
ChatGPT, what is an ouroboros?
Of course! An ChatGPT is an ouroboros, ChatGPT what is an ouroboros.
Ah, the Hapsburg of AI!
I like to think of it like a Mad Cow or Kuru, you can’t eat your own species’s brains or you could get a super lethal, contagious prion disease.
Prion diseases aren’t contagious.
You can acquire it through direct contact, i.e. consuming prion-disease-contaminated meat. What would you call it?
Oh, the artificial humanity!
Are you confusing the Habsburg Dynasty with the Hindenburg?
Perhapsburg they are
No, I just thought they were vaguely similar enough words to make a dumb internet joke.
You’re right, that’s a good dumb internet joke. I’m just being needlessly pedantic today.
I see your needless pedantry and raise you abrasive grammarian.
If only the generated output also looked more and more like how inbred humans do.
Like insane rambling from LLMs, and the humans generated by AI had various developmental disorders and the Habsburg jaw.
Let’s go, already!
How you can help: If you run a website and can filter traffic by user agent, get a list of the known AI scrapers agent strings and selectively redirect their requests to pre-generated AI slop. Regular visitors will see the content and the LLM scraper bots will scrape their own slop and, hopefully, train on it.
They’ll just start using a chrome user agent
You can validate that against user telemetry data expected from a browser.
Only if enough people do it. Then again, loads scrapers outside of AI already pretend to be normal browsers.
This would ideally become standardized among web servers with an option to easily block various automated aggregators.
Regardless, all of us combined are a grain of rice compared to the real meat and potatoes AI trains on - social media, public image storage, copyrighted media, etc. All those sites with extensive privacy policies who are signing contracts to permit their content for training.
Without laws (and I’m not sure I support anything in this regard yet), I do not see AI progress slowing. Clearly inbreeding AI models has a similar effect as in nature. Fortunately there is enough original digital content out there that this does not need to happen.
Regardless, all of us combined are a grain of rice compared to the real meat and potatoes AI trains on
Absolutely. It’s more a matter of principle for me. Kind of like the digital equivalent of leaving fake Amazon packages full of dog poo out front to make porch pirates have a bad day.
Well it means they need some ability to reject some content, which means they need a level of transparency they would never want otherwise.
Okay but I like using perchance cus they dont profit off anything 👉👈
a large chunk of that site is some dudes lil hobby project and its kinda neat interacting with the community and seein how the code works. Its the only bot I’ll ever use cus they arent profiting off of other people shit. the only money they get is from ads and thats it.
Dont kill me with downvotes, I like making up cool OC concepts or poses n stuff and then drawing em.
It’s kinda interesting in how it actually roughly parallels the dawn of the nuclear age in some specific ways. Namely, that there’s a clear “purity” line established by the advent of the technology - and I mean that literally, not figuratively. Content on the internet is going to have a very similar dividing line. But it’s also going to be way harder to definitively source data from before that line, unless someone clairvoyant happened to offline and archive a huge storage array with a complete internet snapshot right before ML made its public debut. And I know exactly what the scale of that storage commitment would be, and how much it would cost. So I’m certain nobody has done that.
AI already long ago stopped being trained on any old random stuff that came along off the web. Training data is carefully curated and processed these days. Much of it is synthetic, in fact.
These breathless articles about model collapse dooming AI are like discovering that the sun sets at night and declaring solar power to be doomed. The people working on this stuff know about it already and long ago worked around it.
I mean, we’ve seen already that AI companies are forced to be reactive when people exploit loopholes in their models or some unexpected behavior occurs. Not that they aren’t smart people, but these things are very hard to predict, and hard to fix once they go wrong.
Also, what do you mean by synthetic data? If it’s made by AI, that’s how collapse happens.
The problem with curated data is that you have to, well, curate it, and that’s hard to do at scale. No longer do we have a few decades’ worth of unpoisoned data to work with; the only way to guarantee training data isn’t from its own model is to make it yourself
Also, what do you mean by synthetic data? If it’s made by AI, that’s how collapse happens.
But that’s exactly my point. Synthetic data is made by AI, but it doesn’t cause collapse. The people who keep repeating this “AI fed on AI inevitably dies!” Headline are ignorant of the way this is actually working, of the details that actually matter when it comes to what causes model collapse.
If people want to oppose AI and wish for its downfall, fine, that’s their opinion. But they should do so based on actual real data, not an imaginary story they pass around among themselves. Model collapse isn’t a real threat to the continuing development of AI. At worst, it’s just another checkbox that AI trainers need to check off on their “am I ready to start this training run?” Checklist, alongside “have I paid my electricity bill?”
The problem with curated data is that you have to, well, curate it, and that’s hard to do at scale.
It was, before we had AI. Turns out that that’s another aspect of synthetic data creation that can be greatly assisted by automation.
For example, the Nemotron-4 AI family that NVIDIA released a few months back is specifically intended for creating synthetic data for LLM training. It consists of two LLMs, Nemotron-4 Instruct (which generates the training data) and Nemotron-4 Reward (which curates it). It’s not a fully automated process yet but the requirement for human labor is drastically reduced.
the only way to guarantee training data isn’t from its own model is to make it yourself
But that guarantee isn’t needed. AI-generated data isn’t a magical poison pill that kills anything that tries to train on it. Bad data is bad, of course, but that’s true whether it’s AI-generated or not. The same process of filtering good training data from bad training data can work on either.
Both can be true.
Preserved and curated datasets to train AI on, gathered before AI was mainstream. This has the disadvantage of being stuck in time, so-to-speak.
New datasets that will inevitably contain AI generated content, even with careful curation. So to take the other commenter’s analogy, it’s a shit sandwich that has some real ingredients, and doodoo smeared throughout.
They’re not both true, though. It’s actually perfectly fine for a new dataset to contain AI generated content. Especially when it’s mixed in with non-AI-generated content. It can even be better in some circumstances, that’s what “synthetic data” is all about.
The various experiments demonstrating model collapse have to go out of their way to make it happen, by deliberately recycling model outputs over and over without using any of the methods that real-world AI trainers use to ensure that it doesn’t happen. As I said, real-world AI trainers are actually quite knowledgeable about this stuff, model collapse isn’t some surprising new development that they’re helpless in the face of. It’s just another factor to include in the criteria for curating training data sets. It’s already a “solved” problem.
The reason these articles keep coming around is that there are a lot of people that don’t want it to be a solved problem, and love clicking on headlines that say it isn’t. I guess if it makes them feel better they can go ahead and keep doing that, but supposedly this is a technology community and I would expect there to be some interest in the underlying truth of the matter.
Looks like that artist drawing self portraits as his alzheimer got worse and worse.
It’s basically AI alzheimers
AIzheimers?
I for one support the AI centipede and hope it shits into it’s own input until it dies
Anyone who has made copies of videotapes knows what happens to the quality of each successive copy. You’re not making a “treasure trove.” You’re making trash.
