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> You don’t need proper cognition to identify that the answer is not stored in source data That's the original argument. > Tuning creates the contextual frame
by jijijijij 3y ago
> You don’t need proper cognition to identify that the answer is not stored in source data
That's the original argument.
> Tuning creates the contextual framework on which test is mapped to a latent space that encodes the meaning and most likely next sequences of text rather than just raw most likely sequence of text as seen in training data
That's different than understanding, or knowing. The encoded meaning is not accessible to the LLM, but the human it's presented to. An LLM cannot know about things it has or has not stored in source data, because it is not actually informed by the information processed. You do need proper cognition to know if information is in source data, because reasoning about information strictly requires interpretation and understanding intent, otherwise it's just data.
- jncfhnb 3y agoThis 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.