• Admiral Patrick@dubvee.org
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    1 day ago

    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.

    • azl@lemmy.sdf.org
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      1 day ago

      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.

      • Admiral Patrick@dubvee.org
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        1 day ago

        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.

      • Snowclone@lemmy.world
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        21 hours ago

        Well it means they need some ability to reject some content, which means they need a level of transparency they would never want otherwise.

    • FaceDeer@fedia.io
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      1 day ago

      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.

      • TheHarpyEagle@pawb.social
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        22 minutes ago

        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

      • Wrench@lemmy.world
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        22 hours ago

        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.

        • FaceDeer@fedia.io
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          20 hours ago

          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.