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It's useful because it allows you to refer to messages in the chat by message number, and to define functions to use on them. You can do a lot of really powerfu

It's useful because it allows you to refer to messages in the chat by message number, and to define functions to use on them. You can do a lot of really powerful things with it.

AndrewKemendo 3y ago
I think that’s precisely what is unclear What exactly is so powerful that you can do this way, that you can’t do by having a more specified prompt? I read the whole thing but didn’t see anything that stood out
- airesearcher 3y ago
  I often work on documents or content in ChatGPT and I needed a way to refer to previous messages and drafts, and to combine them or pull ideas from them into new drafts or iterations. My first goal was to simply implement message numbering so I could refer to messages by number in the chat. It took a LOT of tuning to make ChatGPT do that reliably. Once I got that working I started taking it further to enable more advanced editing commands on ranges of messages, and automation of tasks with simple command line functions. It saves me a ton of time and a lot of cutting and pasting. Also the ability to tag messages in a chat and then pull them by tag to use for a new draft is useful. Now that I have this working I have also added other features - only available in the GPT version - that are increasingly more powerful and productive for really using ChatGPT to develop content and ideas systematically. It's way better than constantly copying and pasting previous messages into new messages to ask ChatGPT to do stuff with them. Now I simply type "Make //5 longer and combine with //7" to make message 5 longer and merge it with message 7. Big time saver!
  - Zetobal 3y ago
    It's still a workaround for not using the right tools for the job... ie. Embeddings and RAG and it influences your output.
    - fnordpiglet 3y ago
      I’m not sure I understand how embedding or RAG help with the use case articulated. Those are techniques for either adjusting the semantic space or bringing context in via information retrieval. The use case here is iterative refinement of parts of the existing context without pasting it back into the context. Aside from time saving it’ll also help mitigate large context that contain lots of repetition issues. It’s hard to imagine a way embedding or RAG could help you with “take response 5 and 8, combine them and distill into a summary, but with a more emphatic style”
      - Zetobal 3y ago
        Because you are impedding the model performance by doing a task that can be handled by external libraries in the context window. It's just inefficient while also influencing the output of the model... There are literally no positives on doing it OPs way.
        mewpmewp2 3y ago
        So we should test out the performance, because with GPT funnily enough, it's possible that this type of prompt could bias it even better. Because e.g. if you need it to answer in a very specific way, it might be helpful for the ChatBot to see what the other potential ways are so it would know to contrast even more. Yes, it's influencing the output of the model, but it's unclear to me without extensive trying in which way, because it could be positive influence as well. As for efficiency. It doesn't add that much in terms of magnitude if you already have long conversations going on. Finally. Using external libraries and building out the things that you are mentioning will take time, trial and error. Just modifying the initial prompt is easy, and you can start to use it immediately. So the main positive is just that it's likely faster and easier to implement compared to building out those systems.
        Zetobal 3y ago
        You don't want your tooling to have any effect on your output...

It's useful because it allows you to refer to messages in the chat by message number, and to define functions to use on them. You can do a lot of really powerful things with it.

AndrewKemendo 3y ago

I think that’s precisely what is unclear What exactly is so powerful that you can do this way, that you can’t do by having a more specified prompt? I read the whole thing but didn’t see anything that stood out

airesearcher 3y ago
I often work on documents or content in ChatGPT and I needed a way to refer to previous messages and drafts, and to combine them or pull ideas from them into new drafts or iterations. My first goal was to simply implement message numbering so I could refer to messages by number in the chat. It took a LOT of tuning to make ChatGPT do that reliably. Once I got that working I started taking it further to enable more advanced editing commands on ranges of messages, and automation of tasks with simple command line functions. It saves me a ton of time and a lot of cutting and pasting. Also the ability to tag messages in a chat and then pull them by tag to use for a new draft is useful. Now that I have this working I have also added other features - only available in the GPT version - that are increasingly more powerful and productive for really using ChatGPT to develop content and ideas systematically. It's way better than constantly copying and pasting previous messages into new messages to ask ChatGPT to do stuff with them. Now I simply type "Make //5 longer and combine with //7" to make message 5 longer and merge it with message 7. Big time saver!
- Zetobal 3y ago
  It's still a workaround for not using the right tools for the job... ie. Embeddings and RAG and it influences your output.
  - fnordpiglet 3y ago
    I’m not sure I understand how embedding or RAG help with the use case articulated. Those are techniques for either adjusting the semantic space or bringing context in via information retrieval. The use case here is iterative refinement of parts of the existing context without pasting it back into the context. Aside from time saving it’ll also help mitigate large context that contain lots of repetition issues. It’s hard to imagine a way embedding or RAG could help you with “take response 5 and 8, combine them and distill into a summary, but with a more emphatic style”
    - Zetobal 3y ago
      Because you are impedding the model performance by doing a task that can be handled by external libraries in the context window. It's just inefficient while also influencing the output of the model... There are literally no positives on doing it OPs way.
      - mewpmewp2 3y ago
        So we should test out the performance, because with GPT funnily enough, it's possible that this type of prompt could bias it even better. Because e.g. if you need it to answer in a very specific way, it might be helpful for the ChatBot to see what the other potential ways are so it would know to contrast even more. Yes, it's influencing the output of the model, but it's unclear to me without extensive trying in which way, because it could be positive influence as well. As for efficiency. It doesn't add that much in terms of magnitude if you already have long conversations going on. Finally. Using external libraries and building out the things that you are mentioning will take time, trial and error. Just modifying the initial prompt is easy, and you can start to use it immediately. So the main positive is just that it's likely faster and easier to implement compared to building out those systems.
        Zetobal 3y ago
        You don't want your tooling to have any effect on your output...