I seems to remember a distinct time during which Claude for example became incomprehensible and weird with its writing, whereas before it was reasonably OK, even if still not that good
I find Claude’s writing unbearable. That ChatGPT offers personalization options (Base style, warmth, enthusiasm) and Claude doesn’t suggests Anthropic doesn’t recognize this as a problem. Plus, people sharing ChatGPT writing won’t all have the same voice.
My answer is still yes - I've got this personal concept that AI is sorta the "opposite" of lossy compression... As the model iterates on a larger corpus of context, things are missed, misinterpreted, slightly changed. This all eventually contributes to the writing feeling disconnected. LLMs make decisions on what the most important facet of a prompt is, obviously we can 'guide' it...
Over time, I feel that as we let more AI generated content (no human edited / modified / improved the output) sit around on the internet, the training data will pick up more of this 'poisoned' data and impact future output.
> This is an interesting failure-mode to me, and I've been interested in how accurate it is since the inception of these models.
The term you want to look for more information on this is "model collapse".