Comment by rerdavies
5 days ago
I think you have an overly strict definition of what "learning" means. ChatGPT now has memory that lasts beyond the lifetime of it's context buffer, and now has at least medium term memory. (Actually I'm not entirely sure that they are not just using long persistent context buffers, but anyway).
Admittedly, you have to wrap LLMs to with stuff to get them to do that. If you want to rewrite the rules to excluded that then I will have to revise my statement that it is "mostly, but not completely true".
:-P
You also have to alter some neural pathways in your brain to follow commands. That doesn’t make it learning. Learned behavior is usually (but not always) reflected in long term changes to neural pathways outside of the language centers of the brain, and outside of the short-term memory. Ones you forget the command, and still apply the behavior, that is learning.
I think SSR schedulers are a good example of a Machine Learning algorithms that learns from it’s previous interactions. If you run the optimizer you will end up with a different weight matrix, and flashcards will be schedule differently. It has learned how well you retain these cards. But an LLM that is simply following orders has not learned anything, unless you feed the previous interaction back into the system to alter future outcomes, regardless of whether it “remembers” the original interactions. With the SSR, your review history is completely forgotten about. You could delete it, but the weight matrix keeps the optimized weights. If you delete your chat history with ChatGPT, it will not behave any differently based on the previous interaction.