There was a lot of press ~2 years ago about this paper, and the term “model collapse”:
Training on generated data makes models forget
There was concern that the AI models had slurped up the Whole Internet and needed more data to get any smarter. Generated “synthetic data” was mooted as a possible solution. And there’s the fact that the Internet increasingly contains AI-generated content.
As so often happens (and happens fast in AI), research and industry move on, but the flashy news item remains in peoples’ minds. To this day I see posts from people who misguidedly think this is still a problem (and a such one more reason the whole AI house of cards is about to fall)
In fact, the big frontier models today (GPT, Gemini, Llama, Phi, etc) are all trained on synthetic data
As it turns out, quality of data is what really matters, not whether it’s synthetic or not; see " Textbooks Are All You Need "
And then some folks figured out how to use an AI Verifier to automatically curate that quality data: " Escaping Model Collapse via Synthetic Data Verification "
And people used clever math to make the synthetic data really high quality: " How to Synthesize Text Data without Model Collapse? "
Summary:
“Model collapse” from AI-generated content is largely a Solved Problem.
There may be reasons the whole AI thing will collapse, but this is not one.


To put it more generally: we can assume that the problems we see with AI are well known to the professionals working on it and that they are some of the smartest people around. Just because you and I can’t think of a solution doesn’t mean they won’t, eventually.