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Does it strike any one that this is an extremely stupid way to add a restriction on how many images you can generate? (edit NOT) Giving hard limits to a system

• codingdave 2y ago
  On the contrary, that makes a ton of sense - if you have a fuzzy system with a potential for people to trigger massive resource usage, it would be silly not to put a hard restriction on the tasks that are resource-intensive.
  • pixiemaster 2y ago
    yeah, but that is not a hard restriction, since prompts are fuzzy
    • 1f60c 2y ago
      It's possible that OpenAI have implemented both soft and hard limits, and repeating it in the prompt just prevents it from hitting the user with a scary error.
  • utensil4778 2y ago
    A hard restriction would prevent a malicious prompt from being passed to the model. Instead, it seems they've simply asked the model nicely to pretty please not answer malicious prompts. A hard restriction would be a regex or a simpler model checking your prompt for known or suspected bad prompts and refusing outright.
    • ben_w 2y ago
      You seem to be suggesting implementing natural language processing as a series of regexes. If NLP was that easy, we wouldn't have needed to invent transformer models, and we'd have had things as capable as ChatGPT about the same time that Microsoft was selling Encarta on CD. The reality is, this soft fuzzy thing is the only practical way to minimise the Scunthorpe problem (and its equivalents for false negatives): https://en.wikipedia.org/wiki/Scunthorpe_problem https://en.wikipedia.org/wiki/Scunthorpe_problem
• Ozzie_osman 2y ago
  It's probably both. There is probably a hard restriction that will stop it if it tries to output more than one image in the generation, but the prompt mechanism probably drastically reduces the probability that it starts off by saying "Here are a few images..." and then getting stopped after the first.
• CGamesPlay 2y ago
  No, you have to tell the model about the restrictions that are in place on it. If the model wanted to generate 3 images, but the chat interface only supports returning a single one, the model would say "here are your images" and the chat interface would only show one.
  • CharlieDigital 2y ago
    Presumably, there is a step between the NLP and the actual image generation. Could be function calling, could be some other mechanism. It seems rather trivial to restrict the system at that interface point where the NLP gets translated into image generation instructions and simply cut it off at a limit.
    • CGamesPlay 2y ago
      But the model has to write a natural language response, which will be based on what it expects the result to be..
      • CharlieDigital 2y ago
        I don't see the disconnect. Since there is an interface point where the NLP is translated into some image generation call path, presumably, the response generation can see that it only got 1 image back instead of n. Even a system prompt could be added to normalize the output text portion of the response.
        • CGamesPlay 2y ago
          The image generation API returns a URL to the image, which ChatGPT isn't going to fetch and look at. If ChatGPT asked the service to generate 500 images, it seems reasonable to assume that the returned URL would be some sort of zip file or gallery or even single image grid containing those 500 images. Alternatively, if ChatGPT does think it is suspicous that it only got one URL, it might end up responding with "the system seems to be not working right now, I'm only getting partial results for your query", because it doesn't know that the system is only going to return a single image. This is getting into speculative territory, so I guess the true answer could also be "OpenAI are amateurs are prompting ChatGPT", but it seems less likely.
• deleted 2y ago
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