I think there’s a possibility that there could be dangerous emergent dynamics from multiple interacting AIs but I’m not too worried about that problem because I don’t think you can increase the capabilities of an AI much simply by running multiple copies of it. You can do more work this way but I don’t think you can get qualitatively much better work.
OpenAI created GPT-4 by training a brand new model not by running multiple copies of GPT-3 together. Similarly, although human corporations can achieve more than a single person, I don’t consider them to be superintelligent. I’d say GPT-4 is more capable and dangerous than 10 copies of GPT-3.
I think there’s more evidence that emergent properties come from within the AI model itself and therefore I’m more worried about bigger models than problems that would occur from running many of them. If we could solve a task using multiple AIs rather than one highly capable AI, I think that would probably be safer and I think that’s part of the idea behind iterated amplification and distillation.
There’s value in running multiple AIs. For example, OpenAI used multiple AIs to summarize books recursively. But even if we don’t run multiple AI models, I think a single AI running at high speed would also be highly valuable. For example, you can paste a long text into GPT-4 today and it will summarize it in less than a minute.
Thanks for the comment.
I think there’s a possibility that there could be dangerous emergent dynamics from multiple interacting AIs but I’m not too worried about that problem because I don’t think you can increase the capabilities of an AI much simply by running multiple copies of it. You can do more work this way but I don’t think you can get qualitatively much better work.
OpenAI created GPT-4 by training a brand new model not by running multiple copies of GPT-3 together. Similarly, although human corporations can achieve more than a single person, I don’t consider them to be superintelligent. I’d say GPT-4 is more capable and dangerous than 10 copies of GPT-3.
I think there’s more evidence that emergent properties come from within the AI model itself and therefore I’m more worried about bigger models than problems that would occur from running many of them. If we could solve a task using multiple AIs rather than one highly capable AI, I think that would probably be safer and I think that’s part of the idea behind iterated amplification and distillation.
There’s value in running multiple AIs. For example, OpenAI used multiple AIs to summarize books recursively. But even if we don’t run multiple AI models, I think a single AI running at high speed would also be highly valuable. For example, you can paste a long text into GPT-4 today and it will summarize it in less than a minute.