Would you consider an argumentative LLM system that sticks to it's guns (and research) be useful? I'm removing sycophancy in an multitude of ways, even during generation I have system to align the LLMs output to the original idea, so even if it was prompt injected it pivots (It uses non llm models for this). I'm just wondering what is people want out of their LLM locally, like how far is too far? An example is that an LLM has the advantage over most of us in how to code, so why would such a system need to listen to us on how to code something, when its algorithms have surfaced the most likely answer? Same mostly applies to math etc. Though I know most of us probably don't argue with the LLM on how to code or calculate something... What would you argue about?   submitted by   /u/GodComplecs [link]   [comments]