Earlier quoted context omitted.
I mean I can definitely remember lots of cases for myself, in school especially, when I made the same mistake again repeatedly despite being corrected every time. I'm sure today's language models pale in comparison to your flawless genius, but you seriously underestimate the average person's idiocy. Agreed that the lack of some mid tier memory is definitely a huge problem, and the current solutions that try to addres…
It lacks more than memory, it makes the mistake again later even when the previous prompt is in its current token limit.
For example, I have this setup where a model has some actions defined in its system prompt that it can output when appropriate to trigger actions, and the interesting bit is that initially I was using openhermes-mistral which is famous for its extreme attention to the system prompt, and it almost never made any mistakes when calling the definitions. Later I swapped it with llama-3 which is way smarter, but isn't tuned to be nearly as attentive and far more often likes to make up alternatives and don't get fuzzy matched properly. Someone anthropomorphizing it might say it lacks discipline.