[solid_fuel]

> I used that particular example because you said "You cannot separate data that was input by the user and data that is from the system once it is mixed together like that" and that simply is not true. LLMs can do what neural nets do because they contain them, neuralnets can perform functions. If there is any signal distinguishing two things then there is a function that can separate them.

Oh my, this is a serious misunderstanding on your part. That segmentation models can classify portions of an input into separate groups has no bearing on being able to unmix user and system intent within the confines of an LLM.

Just one of many issues with your reasoning here: a segmentation model works along boundaries in the data. E.g. in simple terms, a foreground segmentation model works because you can define a clear foreground and background for most images. There is no way to differentiate system and user intent in the same way, they aren’t segmentable in the same way as an image.