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This simply isn’t true. It’s true that they’re not great at doing this, but they can and do do it and easily demonstrated by chat gpt actively telling you about
by jncfhnb 3y ago
This simply isn’t true. It’s true that they’re not great at doing this, but they can and do do it and easily demonstrated by chat gpt actively telling you about things it does not know.
It does not have cognition. And yet it can do this. Ergo it does not need cognition to do this.
LLMs have easily demonstrated reasoning capabilities. The encoded meaning is very clearly explored by the model through its tuned framework and I think it’s ridiculous to pretend otherwise.
It’s not stepping through reflection steps in a way that is familiar to humans, but it absolutely is running through semantically defined pattern processing steps. And “known” vs “not known” is one such pattern.
- jijijijij 3y agoYes, I am sure they have implemented an heuristic for this. It can't do this in all cases, so ergo it does need cognition for the category of problem. At least by your reasoning. There is a difference between convincing you in interaction and proving theoretical capabilities. You also don't know, if your experience is down to inherent capabilities of the LLM, or manually implemented algorithms, when you use ChatGPT. We're arguing about different things, or about different levels of abstraction. Have fun with ChatGPT.
- jncfhnb 3y agoI run mixtral on my own hardware so I know pretty well what’s the output of the LLM. I’m not sure why you felt compelled to add that jab in there either way. Your argument seems to be that cognition is required to do this perfectly even though things with cognition frequently get this wrong and the bar of the conversation was whether it could be done at all. So I think it seems to be a pretty bad argument.