Archive link: https://archive.ph/GtA4Q

The complete destruction of Google Search via forced AI adoption and the carnage it is wreaking on the internet is deeply depressing, but there are bright spots. For example, as the prophecy foretold, we are learning exactly what Google is paying Reddit $60 million annually for. And that is to confidently serve its customers ideas like, to make cheese stick on a pizza, “you can also add about 1/8 cup of non-toxic glue” to pizza sauce, which comes directly from the mind of a Reddit user who calls themselves “Fucksmith” and posted about putting glue on pizza 11 years ago.

A joke that people made when Google and Reddit announced their data sharing agreement was that Google’s AI would become dumber and/or “poisoned” by scraping various Reddit shitposts and would eventually regurgitate them to the internet. (This is the same joke people made about AI scraping Tumblr). Giving people the verbatim wisdom of Fucksmith as a legitimate answer to a basic cooking question shows that Google’s AI is actually being poisoned by random shit people say on the internet.

Because Google is one of the largest companies on Earth and operates with near impunity and because its stock continues to skyrocket behind the exciting news that AI will continue to be shoved into every aspect of all of its products until morale improves, it is looking like the user experience for the foreseeable future will be one where searches are random mishmashes of Reddit shitposts, actual information, and hallucinations. Sundar Pichai will continue to use his own product and say “this is good.”

  • Margot Robbie@lemmy.world
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    1 month ago

    Reddit, and by extension, Lemmy, offers the ideal format for LLM datasets: human generated conversational comments, which, unlike traditional forums, are organized in a branched nested format and scored with votes in the same way that LLM reward models are built.

    There is really no way of knowing, much less prevent public facing data from being scraped and used to build LLMs, but, let’s do an thought experiment: what if, hypothetically speaking, there is some particularly individual who wanted to poison that dataset with shitposts in a way that is hard to detect or remove with any easily automate method, by camouflaging their own online presence within common human generated text data created during this time period, let’s say, the internet marketing campaign of a major Hollywood blockbuster.

    Since scrapers do not understand context, by creating shitposts in similar format to, let’s say, the social media account of an A-list celebrity starring in this hypothetical film being promoted(ideally, it would be someone who no longer has a major social media presence to avoid shitpost data dilution), whenever an LLM aligned on a reward model built on said dataset is prompted for an impression of this celebrity, it’s likely that shitposts in the same format would be generated instead, with no one being the wiser.

    That would be pretty funny.

    Again, this is entirely hypothetical, of course.