4 ms·
>https://github.com/wgryc/phasellm/blob/main/demos-and-products/researchgpt/researchgpt.py#L52 https://github.com/wgryc/phasellm/blob/main/demos-and-produc...
by Imnimo 3y ago
>https://github.com/wgryc/phasellm/blob/main/demos-and-products/researchgpt/researchgpt.py#L52 https://github.com/wgryc/phasellm/blob/main/demos-and-produc...
Asking the LLM if it "understands" and only proceeding if it says yes feels very weird to me. Do we really expect the LLM to be able to introspect in that way and give a meaningful answer?
- cl42 3y agoNope! I'm not trying to suggest the LLM legitimately understands my query from a conceptual perspective via that question. What I am doing in that prompt is ensuring the LLM can follow the instructions. I specifically ask it to write "yes" if it does. If it can't do that part, then I don't want it to even generate code or try to analyze my data. Hence why I treat it as an assertion failure if it can't follow that instruction, and thus exit the app. Thanks for reading the code + for the very thoughtful question.
- r-zip 3y agoDeep nets are notoriously overconfident in their predictions. So why do you expect this approach to succeed?
- cl42 3y agoThe broader package I’m working on (PhaseLLM) is specifically focused on devtools for observability and robustness of LLM-powered products. I agree with you that there are lots issues with LLMs and taking them to production. I’m hoping products like this + making them robust will help improve the research as well as the UX.
- nullsense 3y ago>Deep nets are notoriously overconfident in their predictions Sounds a lot like humans