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Not actually true. There is good evidence (specific ML-research into this exact question) that it does have a notion of truth, although of course it doesn't care whether the words it's generating add up to a truthful sentence or not ... it'll simply generate something truthful if that appears the best continuation of the prompt, or something untruthful (even if just a fairy tale) when that is the best continuation. And, this is precisely why it does have a notion of truth and lying, because it was necessary to learn that concept/context in order to generate these appropriately truthy/untruthy responses. People refer to ChatGPT as an LLM, and it's not wrong, but it's probably a bit misleading nonetheless. I think most people, certainly up until this point, would imagine a language model as something that was basically at the level of generating something gramatically correct (quite a tall order!), and not much more. The thing is, we could apply the same "predict next word" goal to something much more powerful than a language model - e.g. to an expert system that has in-depth knowledge of the world and is applying that vast corpus of semantics (coded via rules) to this prediction task, as needed to "answer questions" such as "with the chess board set up as so ... what move might Gary Kasparov make next" ? So, given the transformer technology behind ChatGPT, and the sheer scale (100's of billions of parameters), does it seem more insightful/accurate to describe ChatGPT as being closer to the grammar-only language-model end of the spectrum, or the predict-what-Kasparov-would-say expert system end of the spectrum? I'd say it's certainly somewhere in the middle given the capabilities we've seen that it has. We don't really have a very good vocabulary for discussing systems like this since it's something that hasn't existed before. I'd say that "predictive intelligence" isn't totally off-base - something that uses a learnt world-model to make predictions (in this case just word predictions), but maybe "expert system" would be a less controversial description. It seems pretty apparent that those billions of parameters are encoding some type of set of rules/knowledge, with the major difference between ChatGPT and a GOFAI expert system like Cyc being that ChatGPT had to learn it's rules from raw text, vs Cyc which was laboriously fed human curated rules. Anyway, regardless of how best to describe ChatGPT, calling it an LLM just because it shares the training goal of an LLM doesn't seem very useful. |