It's worth keeping in mind the model doesn't keep a running memory. Each time its instantiated, it begins from its release state - so from its perspective (if it had one) the current task would be the first stop after posttraining. Perhaps the only stop.
Though of course you're talking about data centers, and romanticizing them rather than the AI itself.
No, llm providers will start providing a service that looks a lot like rumination or (day)dreaming. Like thats the prompt "you're daydreaming about this work you recently did" then add in whatever is in the current session.
Why do they do it this way? Because dogfooding is harmful to the model? Is this implying there's no benefit in having the model train on itself?
> Is this implying there's no benefit in having the model train on itself?
There are various theories around model collapse when you train on too much AI generated data (that's not for distillation).