I think I should make this my new personal hype cycle. Lots of (time-consuming) wonders on the way. For pre-configured LLMs like ChatGPT one needs to know abou

I think I should make this my new personal hype cycle. Lots of (time-consuming) wonders on the way. For pre-configured LLMs like ChatGPT one needs to know about any automatic prompt extension and pre-biases, though, as in its current form e.g. chatGPT tries to please its user and would use any mentioned analogous problem more as a hint towards their goal than as an extension, perspective or aspect. The results usually are nicely formulated expressions of the thoughts you already had in mind anyway. At least this were my experiences when providing these kind of detour descriptions and examples to guide the model around its overly straight path. It would still only pick up what I hinted at. The solution them seemed based on wider paths and therefor seemed more consistent or complete but still wouldn't get particularly creative or new. Of course those personal chat explorations weren't scientific in any way. Still, one could imagine this priming becoming really large and basically containing all kinds of known philosophical standard solutions, so that the system would act like a philosohical engineer that knows all the transforms. This then would match the best trained philosopher (not too shabby) but might still not go that non-linear step, use that unprobable assumption etc, all what makes new ideas new when injected at the right point. So, I'd guess for creative reasoning you'd need to actually apply the idea to your model of the world and then judge what that would mean for that world. I guess, despite wanting to, I can't see this being done by a text-based model (might be the reason why there's that prejudice against well-educated person without much experience). Still, I think that LLMs can be much more than complex lookup machines due to all the implicit rules and knowlede contained in the model and its text-based base and that these can be re-formulated (or made explicit despite being hidden) with such an approach. Also the wanted explanatory reasoning might be improved in its output. Now, for a creative model, I'd say it would need stateful representation of the world that it could tinker with. And yes, we all know that we are the current implementation of such a model, right? (And yes, there might be a faster and more random but still cheaper way.) Edit: I'd really like to see a more theoretical (mathematical) discussion/theory on this topic.