> I am reminded how thankful I am that AI is around now, because it understood what you clearly don't.
We understand what you're saying just fine but what you're saying is simply wrong as a matter of technical fact. All of that context still exists and still degrades the output even if the model has fooled you into thinking that it doesn't. Therefore recommending it as an alternative to actually clearing the context is bad advice.
It's similar to how a model can be given a secret password and instructed not to reveal it to anyone under any circumstances. It's going to reject naive attempts at first, but it's always going to reveal it eventually.
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What I'm saying is.. I tell the AI to "forget everything" and it understands what I mean... and you're arguing that it cannot do... what you INCORRECTLY think is being said
I get that you're not very intelligent, but do you have to show it repeatedly?
Again, we understand your argument and I don't doubt that the model "understands" your request and agrees to do it (insofar that LLMs are able to "understand" anything).
But just because the model is agreeing to "forget everything" doesn't mean that it's actually clearing its own context, and because it's not actually clearing its own context it means that all the output quality problems associated with an overfilled context continue to apply, even if the model is convincingly pretending to have forgotten everything. Therefore your original interjection of "instead of clearing the context you can just ask it to forget" was mistaken and misleading.
These conversations would be way easier if you didn't go around labeling everyone an idiot, believing that we're all incapable of understanding your rather trivial point while ignoring everything we say. In an alternative universe this could've been:
> You can ask it to forget.
> Models don't work like that.
> Oh, I didn't know that, thanks!
Just because it's not mechanically actually forgetting everything doesn't mean the phrase isn't having a non trivial effect (that isn't 'pretend'). Mechanically, based on all current context, Transformers choose how much attention/weight to give to each preceding token. Very likely, the phrase makes the model pay much less attention to those tokens, alleviating the issues of context rot in most (or a non negligible amount of) scenarios.
You should probably stop resorting to personal attacks as it's against hn rules.