When you are like ‘clean this up’. I always wonder how much of that is “clean it up so it is in line with some context that actually lives in my mind but I forgot to tell you”
Yeah, there’s definitely a lot of that. If we had decent BCIs, that would plausibly indeed make strong cyborgism/centaurs work. Like, I think that may actually 10x even my cursed work.
That said, humans don’t have telepathy, yet human-to-human collaboration still works better than human-to-LLM. So I don’t think it’s the whole story, LLMs are genuinely dropping the ball in some ways that humans with just as much context (e. g., a remote-worker subcontractor, communicated-with via pretty sparse, mostly text-only, channels) wouldn’t.
I suspect a lot of context lives in the collective minds of humans that is not easily or obviously inferred in a one-to-one sense from all the training data. It’s not a one-to-one mapping or many-to-one from training to outcome, there’s many ways to interpret the training data that the AI is seeing during training and also tacit knowledge/wisdom.
The latter is how I imagine you can have superintelligence but it will still fail to build an EUV machine one-shot because so much context lives in the entire supply chain and it’s nowhere written down and it has to go and each and every one of those people and observe very closely what they do, and then try it out iterate and fail.
Yeah, there’s definitely a lot of that. If we had decent BCIs, that would plausibly indeed make strong cyborgism/centaurs work. Like, I think that may actually 10x even my cursed work.
That said, humans don’t have telepathy, yet human-to-human collaboration still works better than human-to-LLM. So I don’t think it’s the whole story, LLMs are genuinely dropping the ball in some ways that humans with just as much context (e. g., a remote-worker subcontractor, communicated-with via pretty sparse, mostly text-only, channels) wouldn’t.
I suspect a lot of context lives in the collective minds of humans that is not easily or obviously inferred in a one-to-one sense from all the training data. It’s not a one-to-one mapping or many-to-one from training to outcome, there’s many ways to interpret the training data that the AI is seeing during training and also tacit knowledge/wisdom.
The latter is how I imagine you can have superintelligence but it will still fail to build an EUV machine one-shot because so much context lives in the entire supply chain and it’s nowhere written down and it has to go and each and every one of those people and observe very closely what they do, and then try it out iterate and fail.