But it’s not just converting them into a different format. It’s not even storing that information at all. It can’t actually reproduce anything from the dataset unless it is really small or completely overfitted, neither of which apply to GPT with how massive it is.
Each neuron, which represents a word or a phrase, is a set of weights. One source makes a neuron go up by 0.000001% and then another source makes it go down by 0.000001%. And then you repeat that millions and millions of times. The model has absolutely zero knowledge of any specific source in its training data, it only knows how often different words and phrases occur next to each other. Or for images it only knows that certain pixels are weighted to be certain colors. Etc.