Earlier quoted context omitted.
I have very limited understanding of chatGPTs architecture, and neural nets in general. From what I've read over the last few days, the "attention" mechanism used in chatGPT and similar LLMs does indeed dynamically change weights of a portion of the model.
the connection between weights are dynamic but the weights themselves aren't being changed i.e being updated in response to the text. when training a model, the forward pass would happen i.e the generation and then depending on how close to truth it was, the configuration settings (aka the weights/neurons) would be adjusted to incorporate whatever little insight was gained from the text. Weights are matrices. The val…
1: https://towardsdatascience.com/an-intuitive-explanation-of-s...