>The algorithm tokenizes the input into a sequence of tokens and then generates the next token(s) in the sequence based on the probabilities learned during trai

>The algorithm tokenizes the input into a sequence of tokens and then generates the next token(s) in the sequence based on the probabilities learned during training. This is just a description of the input/output boundary of the system. The question is what goes on in-between and how to best characterize it? My input/output is also "tokens" of a sort: word units, sound patterns, color patches, etc. >Your ideas cohere from network connections between the neurons in your brain, and then you come up with words to match your idea, not your previous words or the frequency that the words appear in your brain. At some high level of description, yes. At a low level it's just integrating action potentials. What's to say there isn't a similar high level of description that characterizes the process by which ChatGPT decides on its continuation?