3 ms·

We've replaced our rule-based health engine with LLM

• passwordoops 2y ago
  I look forward to upcoming the blog post explaining why they went back E.g, https://medcitynews.com/2024/08/ai-healthcare-llm/ https://medcitynews.com/2024/08/ai-healthcare-llm/ Which is a news article about: https://openreview.net/pdf?id=6eMIzKFOpJ https://openreview.net/pdf?id=6eMIzKFOpJ
  • guzik 2y ago
    The second link is broken: "no healthy upstream" Edit: it works now. Are you the author? I’d be happy to add a reference to it.
    • passwordoops 2y ago
      Thanks, but no I'm not the author
  • deleted 2y ago
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• fsndz 2y ago
  Good luck with the reliability issues: https://www.lycee.ai/blog/ai-reliability-challenge https://www.lycee.ai/blog/ai-reliability-challenge
  • guzik 2y ago
    Do you mean hallucinations? We know about them and thought about adding some post-checks to our pipeline. Can you share more?
    • fsndz 2y ago
      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
  • deleted 2y ago
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