The premise of using an LLM to interpret data assumes that LLMs can reliably reason over data, which is not always the case. Essentially, you're trusting a blac

The premise of using an LLM to interpret data assumes that LLMs can reliably reason over data, which is not always the case. Essentially, you're trusting a black box to analyze health data and blindly trusting the output. This doesn't seem like the best use of LLMs, but I guess the risks might not be that high in your context, and users may not even notice. It's important to remember that LLMs are not yet thinking machines; they process patterns rather than truly understand or reason: https://www.lycee.ai/blog/why-no-agi-openai https://www.lycee.ai/blog/why-no-agi-openai