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"I was able to prompt GPT-4 in a way that makes it give information that is probably reasonable but that I had to then still verify myself, using my own experti

"I was able to prompt GPT-4 in a way that makes it give information that is probably reasonable but that I had to then still verify myself, using my own expertise as baseline, because GPT-4 cannot be trusted to give true information, and it turns out that for this particular prompt the result made sense" is not something you should downplay.

davesque 4y ago
This is exactly what I came here to say. Yes, GPT-4 may happen to give a correct answer. But what happens when it's wrong? And how would you know it's wrong without a specific background in some topic?
- bdg 4y ago
  This is the major "magic wow factor" behind GPT. It has a basic level of knowledge in every topic which is enough to convince an average human that the AI produced a good result If-And-Only-If the human is unskilled in that topic.
  - warent 4y ago
    Except that GPT can and does produce good results even to experts, just not all the time. So your claim of "IFF" is unnecessary hyperbolic contrarianism
    - shagie 4y ago
      The interesting part here is "does it take longer for an expert to come up with the answer independently or verify that GPT is producing an accurate result?"
      - deleted 4y ago
        [deleted]
- jacobwilliamroy 4y ago
  The other day I was having ChatGPT write some code for me and it started referencing objects and properties that didnt exist. I wish I tried correcting it. That would have been interesting.
  - mckeed 4y ago
    When you correct it, it always seems to say "You are absolutely right! I apologize for the mistake," and then it gives another wrong answer with the same fully confident tone.
    - jacobwilliamroy 4y ago
      Lol. One probably has to work at OpenAI to try and fix their LLM thing. The one they let the public use probably doesnt learn from its users. Hopefully. I wouldn't let just any data in my LLM. When those things get garbage in they just put garbage out.
      - shagie 4y ago
        There's a "thumbs up" and "thumbs down" next to each generated response. While this model may not be getting updated in real time, I would be surprised if that feedback isn't used when looking at updating the model with good feedback being used for retraining the model.
        mclightning 4y ago
        I would love to hear opinions from LLM experts. But I have a feeling they may not be able to update the model, at a fundamental level, so easily by live feedback. Based on what I have been reading, training the core model is a work of statistical analysis on how often words follow each other. This produces a graph tree of words. Now how do you re-evaluate the entire graph based on a single additional feedback without actually retraining the entire model with the said feedback (because it is costly, and result wouldn't be immediate, unless you're thinking of injecting the input as an initial condition to the readily trained model)

davesque 4y ago

This is exactly what I came here to say. Yes, GPT-4 may happen to give a correct answer. But what happens when it's wrong? And how would you know it's wrong without a specific background in some topic?

bdg 4y ago
This is the major "magic wow factor" behind GPT. It has a basic level of knowledge in every topic which is enough to convince an average human that the AI produced a good result If-And-Only-If the human is unskilled in that topic.
- warent 4y ago
  Except that GPT can and does produce good results even to experts, just not all the time. So your claim of "IFF" is unnecessary hyperbolic contrarianism
  - shagie 4y ago
    The interesting part here is "does it take longer for an expert to come up with the answer independently or verify that GPT is producing an accurate result?"
    - deleted 4y ago
      [deleted]
jacobwilliamroy 4y ago
The other day I was having ChatGPT write some code for me and it started referencing objects and properties that didnt exist. I wish I tried correcting it. That would have been interesting.
- mckeed 4y ago
  When you correct it, it always seems to say "You are absolutely right! I apologize for the mistake," and then it gives another wrong answer with the same fully confident tone.
  - jacobwilliamroy 4y ago
    Lol. One probably has to work at OpenAI to try and fix their LLM thing. The one they let the public use probably doesnt learn from its users. Hopefully. I wouldn't let just any data in my LLM. When those things get garbage in they just put garbage out.
    - shagie 4y ago
      There's a "thumbs up" and "thumbs down" next to each generated response. While this model may not be getting updated in real time, I would be surprised if that feedback isn't used when looking at updating the model with good feedback being used for retraining the model.
      - mclightning 4y ago
        I would love to hear opinions from LLM experts. But I have a feeling they may not be able to update the model, at a fundamental level, so easily by live feedback. Based on what I have been reading, training the core model is a work of statistical analysis on how often words follow each other. This produces a graph tree of words. Now how do you re-evaluate the entire graph based on a single additional feedback without actually retraining the entire model with the said feedback (because it is costly, and result wouldn't be immediate, unless you're thinking of injecting the input as an initial condition to the readily trained model)