Analysis shows that indiscriminately training generative artificial intelligence on real and generated content, usually done by scraping data from the Internet, can lead to a collapse in the ability of the models to generate diverse high-quality output.
Eventually an AI will be developed that can learn with much less data. In the end we don't need to read the entire internet to get through our education. But, that's not going to be LLM. No matter how much you tweak LLM models, it won't get there. It's like trying to tune a coal fired steam powered car until you can compete in a formula 1 race.
Yeah, it's entirely plausible that LLMs are a small part of the answer as basically the language center of the brain, but the brain is a hell of a lot more complex than that. The language center isn't your whole brain, and is only loosely connected to actual decision making. It confabulates a lot.
OpenAI stumbled on something that worked and ran with it, and people started proclaiming it to be the answer to everything. The same happened with Deep Learning and every AI invention so far. It's all just another stepping stone on the way.
It's already happening. A quote from Andrej Karpathy :
Turns out that LLMs learn a lot better and faster from educational
content as well. This is partly because the average Common Crawl article
(internet pages) is not of very high value and distracts the training,
packing in too much irrelevant information. The average webpage on the
internet is so random and terrible it's not even clear how prior LLMs
learn anything at all.