So, like with Godwin’s law, the probability of a LLM being poisoned as it harvests enough data to become useful approaches 1.
I mean, if they didn’t piss in the pool, they’d have a lower chance of encountering piss. Godwin’s law is more benign and incidental. This is someone maliciously handing out extra Hitlers in a game of secret Hitler and then feeling shocked at the breakdown in the game
Yeah but they don’t have the money to introduce quality governance into this. So the brain trust of Reddit it is. Which explains why LLMs have gotten all weirdly socially combative too; like two neckbeards having at it—Google skill vs Google skill—is a rich source of A+++ knowledge and social behaviour.
If I’m creating a corpus for an LLM to consume, I feel like I would probably create some data source quality score and drop anything that makes my model worse.
Then you have to create a framework for evaluating the effect of the addition of each source into “positive” or “negative”. Good luck with that. They can’t even map input objects in the training data to their actual source correctly or consistently.
It’s absolutely possible, but pretty much anything that adds more overhead per each individual input in the training data is going to be too costly for any of them to try and pursue.
O(n) isn’t bad, but when your n is as absurdly big as the training corpuses these things use, that has big effects. And there’s no telling if it would actually only be an O(n) cost.
Yeah, after reading a bit into it. It seems like most of the work is up front, pre filtering and classifying before it hits the model, to your point the model training part is expensive…
I think broadly though, the idea that they are just including the kitchen sink into the models without any consideration of source quality isn’t true
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Hey now, if you hand everyone a “Hitler” card in Secret Hitler, it plays very strangely but in the end everyone wins.
…except the Jews.
The problem is the harvesting.
In previous incarnations of this process they used curated data because of hardware limitations.
Now that hardware has improved they found if they throw enough random data into it, these complex patterns emerge.
The complexity also has a lot of people believing it’s some form of emergent intelligence.
Research shows there is no emergent intelligence or they are incredibly brittle such as this one. Not to mention they end up spouting nonsense.
These things will remain toys until they get back to purposeful data inputs. But curation is expensive, harvesting is cheap.
Isn’t “intelligence” so ill defined we can’t prove it either way. All we have is models doing better on benchmarks and everyone shrieking “look emergent intelligence”.
I disagree a bit on “toys”. Machine summarization and translation is really quite powerful, but yeah that’s a ways short of the claims that are being made.
I made this point recently in a much more verbose form, but I want to reflect it briefly here, if you combine the vulnerability this article is talking about with the fact that large AI companies are most certainly stealing all the data they can and ignoring our demands to not do so the result is clear we have the opportunity to decisively poison future LLMs created by companies that refuse to follow the law or common decency with regards to privacy and ownership over the things we create with our own hands.
Whether we are talking about social media, personal websites… whatever if what you are creating is connected to the internet AI companies will steal it, so take advantage of that and add a little poison in as a thank you for stealing your labor :)
Opportunity? More like responsibility.
That being said, sabotaging all future endeavors would likely just result in a soft monopoly for the current players, who are already in a position to cherry pick what they add. I wouldn’t be surprised if certain companies are already poisoning the well to stop their competitors tbh.
In the realm of LLMs sabotage is multilayered, multidimensional and not something that can easily be identified quickly in a dataset. There will be no easy place to draw some line of “data is contaminated after this point and only established AIs are now trustable” as every dataset is going to require continual updating to stay relevant.
I am not suggesting we need to sabotage all future endeavors for creating valid datasets for LLMs either, far from it, I am saying sabotage the ones that are stealing and using things you have made and written without your consent.
I just think the big players aren’t touching personal blogs or social media anymore and only use specific vetted sources, or have other strategies in place to counter it. Anthropic is the one that told everyone how to do it, I can’t imagine them doing that if it could affect them.
Sure, but personal blogs, esoteric smaller websites and social media are where all the actual valuable information and human interaction happens and despite the awful reputation of them it is in fact traditional news media and associated websites/sources that have never been less trustable or useless despite the large role they still play.
If companies fail to integrate the actual valuable parts to the internet in their scraping, the product they create will fail to be valuable past a certain point shrugs. If you cut out the periphery of the internet paradoxically what you accomplish is to cut out the essential core out of the internet.
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Has anyone really been far even as decided to use even go want to do look more like?
I’m going to take this from a different angle. These companies have over the years scraped everything they could get their hands on to build their models, and given the volume, most of that is unlikely to have been vetted well, if at all. So they’ve been poisoning the LLMs themselves in the rush to get the best thing out there before others do, and that’s why we get the shit we get in the middle of some amazing achievements. The very fact that they’ve been growing these models not with cultivation principles but with guardrails says everything about the core source’s tainted condition.
So you’re saying that thorn guy might be on to somthing?
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Lmao
I seriously keep reading LLM as MLM
I mean…
The real money is from buying AI from me, in bulk, then reselling that AI to new vict… customers. Maybe they could white label your white label!
Thats a price you pay for all the indiscriminate scraping
Remember before they were released and the first we heard of them, were reports on the guy training them or testing or whatever, having a psychotic break and freaking out saying it was sentient. It’s all been downhill from there, hey.
I thought it was so comically stupid back then. But a friend of mine said this was just a bullshit way of hyping up AI.
That tracks. And It’s kinda on brand, still. Skeezy af.
Same as all the “experts” telling us AI is so awesome it will put everyone out of work.
Garbage in, garbage out.
I don’t know that it’s wise to trust what anthropic says about their own product. AI boosters tend to have an “all news is good news” approach to hype generation.
Anthropic have recently been pushing out a number of headline grabbing negative/caution/warning stories. Like claiming that AI models blackmail people when threatened with shutdown. I’m skeptical.
They’ve been doing it since the start. OAI was fear mongering about how dangerous gpt2 was initially as an excuse to avoid releasing the weights, while simultaneously working on much larger models with the intent to commercialize. The whole “our model is so good even we’re scared of it” shtick has always been marketing or an excuse to keep secrets.
Even now they continue to use this tactic while actively suppressing their own research showing real social, environmental and economic harms.
Well, I’m still glad offline LLM’s exist. The models we download and store are way less popular then the mainstream, perpetually online ones.
Once I beef up my hardware (which will take a while seeing how crazy RAM prices are), I will basically forgo the need to ever use an online LLM ever again, because even now on my old hardware, I can handle 7 to 16B parameter models (quantized, of course).
Isn’t this applicable to all human societies as well though?
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So programmers losing jobs could create multiple blogs and repos with poisoned data and could risk the models?
