While some neural network architectures can be designed to better fit certain tasks they are at their core general-purpose learning algorithms which can approximate any target function.
> I feel like I have a decent conceptual grasp of what LLMs are doing with written text
Just think of it as input data. In theory it shouldn't matter what each token represents. They could be xbox controller buttons, image pixels, or text.
The model with enough training data will map those inputs to an expected output.
> I feel like I have a decent conceptual grasp of what LLMs are doing with written text
Just think of it as input data. In theory it shouldn't matter what each token represents. They could be xbox controller buttons, image pixels, or text.
The model with enough training data will map those inputs to an expected output.