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Nothing says that these models will be part of AI systems that are incapable of learning once trained. For a simple example take GPT-4 powering a chat bot that

Nothing says that these models will be part of AI systems that are incapable of learning once trained. For a simple example take GPT-4 powering a chat bot that uses GPT-4 as a component of the whole system. The text from the user, along with the context window, is used first to bring up "memories" based on semantic similarity to items stored in a vector database. GPT-4 then synthesizes the memories and the prompt into some kind of derivative prompt - putting into context the things it already knows and with the things the user is saying to it. GPT-4 then proposes a response to the user and also produces some predictions about the user's subsequent reply. When the subsequent reply comes in GPT-4 compares predicted to actual and produces insights based on the interaction that are subsequently stored in the vector database. This system is completely capable of learning - not by adjusting model weights, but by using the model as a component of a system that can learn. And, of course, nothing stops the model from actually adjusting its weights either - reinforcement learning and fine tuning - perhaps with the benefit of other expert systems that can evaluate exchanges after they've happened.

YeGoblynQueenne 3y ago
Sorry but none of that is realistic. It's all very creative, for sure, but why don't you try and do it yourself and see what happens, instead of just using your imagination? Go and try implementing that vector-database learning system you are imagining and see for yourself how close or far it is from reality. All you need is ChatGPT and a vector database, yes?
- ALittleLight 3y ago
  It's all extremely realistic and I have working prototypes of this already. You can literally do all of this with the OpenAI API and a vector database. (My prototype uses a nearest neighbor descent graph instead - but basically the same thing). Split the text into paragraphs, vector encode the paragraphs, store with the vector as a key. On a new prompt encode paragraphs of the input and find nearest neighbors to the input. Add them to the derivative prompt. If you think it's not realistic - let's make a bet. I'll post a GitHub repo with this working as I described it within 24 hours of acknowledging you accepted the bet (i.e. you say "okay, bet" and I say "okay"). I'll include a video walking through how to run the repo and showing how it works. A thousand dollars?
  - YeGoblynQueenne 3y ago
    A thousand dollars? What, do you take me for a sucker? You have discovered the next big thing in AI and you want to get away with a thousand dollar bet? How about 100 million dollars? US only. All of them.
    - ALittleLight 3y ago
      I think this, meaning some better and more sophisticated version of this, is a possible route to developing AI that can learn without changing its weights. It uses GPT-4 as a component of a system. You can tell it something, it will commit it to memory, and on later interactions with a different context it will recall what you previously told it and use that to form a new response. I've never said what I have is worth a hundred million dollars. My contribution here is a few Python scripts and some prompts. I'm sure other people working on this have the same or better ideas.
      - YeGoblynQueenne 3y ago
        In other words, you wrote some Python scripts and you want me to give you a thousand dollars for them? You really do think I'm a sucker.
        ALittleLight 3y ago
        ??? I originally said that GPT-4 could be a component of a system that learns without updating model weights. You said that was unrealistic. I said I already had a prototype and offered to bet you that I do actually have this prototype. My reason for offering the bet is that I know you know that what I wrote is actually realistic, thus, you will refuse the bet. I believed refusing the bet would force you to acknowledge that you were wrong, what I wrote above is actually realistic. You know it's realistic which is why you won't bet (and you shouldn't bet, you will instantly lose). I don't want you to give me a thousand dollars, I want you to acknowledge what I said was realistic.
        3y ago

YeGoblynQueenne 3y ago

Sorry but none of that is realistic. It's all very creative, for sure, but why don't you try and do it yourself and see what happens, instead of just using your imagination? Go and try implementing that vector-database learning system you are imagining and see for yourself how close or far it is from reality. All you need is ChatGPT and a vector database, yes?

ALittleLight 3y ago
It's all extremely realistic and I have working prototypes of this already. You can literally do all of this with the OpenAI API and a vector database. (My prototype uses a nearest neighbor descent graph instead - but basically the same thing). Split the text into paragraphs, vector encode the paragraphs, store with the vector as a key. On a new prompt encode paragraphs of the input and find nearest neighbors to the input. Add them to the derivative prompt. If you think it's not realistic - let's make a bet. I'll post a GitHub repo with this working as I described it within 24 hours of acknowledging you accepted the bet (i.e. you say "okay, bet" and I say "okay"). I'll include a video walking through how to run the repo and showing how it works. A thousand dollars?
- YeGoblynQueenne 3y ago
  A thousand dollars? What, do you take me for a sucker? You have discovered the next big thing in AI and you want to get away with a thousand dollar bet? How about 100 million dollars? US only. All of them.
  - ALittleLight 3y ago
    I think this, meaning some better and more sophisticated version of this, is a possible route to developing AI that can learn without changing its weights. It uses GPT-4 as a component of a system. You can tell it something, it will commit it to memory, and on later interactions with a different context it will recall what you previously told it and use that to form a new response. I've never said what I have is worth a hundred million dollars. My contribution here is a few Python scripts and some prompts. I'm sure other people working on this have the same or better ideas.
    - YeGoblynQueenne 3y ago
      In other words, you wrote some Python scripts and you want me to give you a thousand dollars for them? You really do think I'm a sucker.
      - ALittleLight 3y ago
        ??? I originally said that GPT-4 could be a component of a system that learns without updating model weights. You said that was unrealistic. I said I already had a prototype and offered to bet you that I do actually have this prototype. My reason for offering the bet is that I know you know that what I wrote is actually realistic, thus, you will refuse the bet. I believed refusing the bet would force you to acknowledge that you were wrong, what I wrote above is actually realistic. You know it's realistic which is why you won't bet (and you shouldn't bet, you will instantly lose). I don't want you to give me a thousand dollars, I want you to acknowledge what I said was realistic.
        3y ago