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submitted 9 months ago by balderdash9@lemmy.zip to c/memes@lemmy.world
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[-] AllonzeeLV@lemmy.world 33 points 9 months ago

As humanity has found yet another way to pass the buck, it'll be interesting to see the diminishing returns of LLMs as they begin to feed more and more on derivative content made by LLMs.

[-] jacksilver@lemmy.world 25 points 9 months ago

It's interesting, because people say they can only get better, but I'm not sure that's true. What happens when most new text data is being generated by LLMs or we accidentally start labeling images created through diffusion as real. Seems like there is a potential for these models to implode.

[-] FierySpectre@lemmy.world 11 points 9 months ago

They actually tested that, trained a model using only the outputs of the previous generation of model. It takes less iterations of that to completely lose quality than you'd think.

[-] jacksilver@lemmy.world 4 points 9 months ago

Do you have any links on that, it was something I had wanted to explore, but never had the time or money.

[-] WarmSoda@lemm.ee 3 points 9 months ago

They go insane pretty quickly don't they? As in it all just become a jumble.

[-] Ilovethebomb@lemm.ee 5 points 9 months ago

Given that people quite frequently try and present AI generated content as real, I'd say this will be a huge problem in the future.

[-] danielbln@lemmy.world 1 points 9 months ago

Microsoft has shown with Phi-2 (https://www.microsoft.com/en-us/research/blog/phi-2-the-surprising-power-of-small-language-models/) that synthetic data generation can be a great source for training data.

[-] livus@kbin.social 13 points 9 months ago

Even before the LLMs, back when I was on reddit I would sometimes see conversations between bots that were 3 or 4 bots replying to each other with scraped content (usually in the personal advice subs) and getting upvotes.

I only noticed because I used to hunt bots as a hobby.

[-] Diplomjodler@feddit.de 6 points 9 months ago

It's cat farts all the way down.

this post was submitted on 15 Dec 2023
502 points (97.9% liked)

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