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.”
Yeah I’m not an AI expert, or even really someone who studies it as my primary role. But my understanding is that part of the “innovation” of modern LLMs is that they generate tokens, which are not necessarily full words, but simply small linguistic units. So basically with enough training the model can learn to predict the most likely next couple of characters and the words just generate themselves.
I haven’t looked too much into it either, but from that very brief description, it sounds like that would help to mostly make it sound more natural by abstracting a bit over word roots and considering grammar structures, without actually baking those into the model as logic.
AI text does read pretty naturally, so hopefully my interpretation is correct. But it’s also very verbose, and can repeat itself a lot.