>Also the 3.5 / 4.0 arguments are trash, made by the marketing department.
All these words to tell us you didn't use 4.
>The underlying math for language modeling it uses is presenatational. This means that it is purpose trained to present correct looking answers. Alas, correct looking answers aren't the same Venn Diagram circle as Correct Answers (even if they often appear to be close).
Completely wrong. LLMs are trained to make right predictions not "correct looking" predictions. If it's not right then there's a penalty and the model learns from that. The end goal is to make predictions that don't err from the distribution of the training data. There is quite literally no room for "correct looking" in the limit of training.
All these words to tell us you didn't use 4.
>The underlying math for language modeling it uses is presenatational. This means that it is purpose trained to present correct looking answers. Alas, correct looking answers aren't the same Venn Diagram circle as Correct Answers (even if they often appear to be close).
Completely wrong. LLMs are trained to make right predictions not "correct looking" predictions. If it's not right then there's a penalty and the model learns from that. The end goal is to make predictions that don't err from the distribution of the training data. There is quite literally no room for "correct looking" in the limit of training.