Oh no. Anyways...
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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.
Kind of like how true thoughts and opinions on complex topics are boiled down to digestible concepts for others to understand who then perpetuate those concepts without understanding them and the meaning degrades and we dont think anymore, just repeat stuff in social media comments.
Side note... this article sucks and seems like it was ai generated. Repetitive and no author credit? Just says it was originally posted elsewhere.
Generative AI isnt in danger of being killed as this clickbait titled suggests... just hindered.
Having now flooded the internet with bad AI content not surprisingly its now eating itself. Numerous projects that aren't AI are suffering too as the quality of text reduces.
Oh no
Anyway
is it not relatively trivial to pre-vet content before they train it? at least with aigen text it should be.
If mainstream blogs are writing about it, what would make someone think that AI companies haven't thoroughly dissected the problem and are already working on filtering out AI fingerprints from the training data set? If they can make a sophisticated LLM, chances are they can find methods to XOR out generated content.
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.
It's like a human centipede where only the first person is a human and everyone else is an AI. It's all shit, but it gets a bit worse every step.
Deep fired AI art sucks and is a decade late to the party
Good riddance.
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.
"Model collapse" is just a fancy way of saying "our stupid ideas are bad and nobody wants them."
Usually we get an AI winter, until somebody develops a model that can overcome that limitation of needing more and more data. In this case by having some basic understanding instead of just having a regurgitation engine for example. Of course that model runs into the limit of only having basic understanding, not advanced understanding and again there is an AI winter.
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).
Good
Sooner or later it is supposed to happen, but I don't think we are quite there....Yet.