[frannyg]

I wasn't able to elaborate on what I mean with "better" when I asked the question but the idea can indeed be summarized with "will an LLM increase quantity and quality of parameters if you give it more processing power and time". Now I know that language models don't do that at all and that the weights of the user request stored in the "frozen" training data is what assembles the return after generating possible output strings, which are selected by pre-prompts like asking for chain of thought and reasoning paths and so on, which in the end, are nothing more than more weights pulling in more specific context. (I'm just thinking out loud here)