Thanks for putting these sources together. It’s impressive that they got to this level of accuracy.

And is your argument now that an LLM can capture arbitrary state of the wider world as a general rule, eg pretending to be a Swift compiler (or LSP), without overfitting to that one task, making all other usages impossible?

> is your argument now that an LLM can capture arbitrary state of the wider world as a general rule, eg pretending to be a Swift compiler (or LSP), without overfitting to that one task, making all other usages impossible?

Overfitting happens, even in humans. Have you ever met a scientist?

My points have been only that 1: language encodes a symbolic model of the world, and 2: training on enough of it results in a representation of that model within the LLM.

Exhaustiveness and accuracy of that internal world model exist on a spectrum with many variables like model size, training corpus and regimen, etc. As is also the case with humans.