Part of my own reconciliation is to question the premise that they would already be capable of ushering in a new industrial revolution. I’ve become more skeptical over time as these basic reasoning issues persist. It’s hard for me to imagine an industrial revolution’s worth of progress and innovation powered by a mind so lacking in coherent world models across so many domains.
Well, steam engines have even less coherent world models.
I believe in their power from seeing just how much value they give me and how transformative they are for me. I’m a super early adopter, but if I extrapolate the rest of the world making as much use of the tech as I am, and doing all the things I could see doing, it’s still so much.
But aren’t a lot of your tasks the sort of thing where
there is in fact a ton of training-available data demonstrating good performance
it’s cheap to experiment
etc., other relevant peculiarities of your use cases
?
I think the claim might be true but I don’t see a super compelling reason to think so at the moment.
“Reasoning” helping with self-driving cars might be a compelling demo, but what it would be compelling about is “you can slap together robotics, big data for a specific domain, and some LLM reasoning stuff to duct tape some more of the decision-making, and get something that’s practically useful”. Generalizing to other robotics could kick off a revolution, but it would be slow-going I think?
There could be a fair amount of science overhang, where you just have to search hard enough to put X and needs-X together. E.g. people curing themselves by searching hard using LLMs. Exciting, but not an industrial revolution? In the grand scheme of science it’s not mostly that. A lot of the coolest stuff is really hard, which means there’s not that many people at the forefront, which means that people at the forefront are already familiar with a lot of what’s relevant.
If you can find domains where iteration can be done pretty automatedly, but it’s expensive enough that decision-making still matters, but decision-making is very cognitively costly, but getting kinda-okay-not-creative decision-making would still be quantitatively better, then you could unlock some sort of new paradigm of invention / discovery. E.g. automated labs running automated experiments designing proteins by gippity-tweaking, or similar. Like PACE. But that would also be hard to get started on.
What are other reasons to think this? Plausible I just haven’t seen the idea, haven’t tried too hard.
Huh, this seems like a very weird comparison to me. It is very clear that I can automate a huge amount of labor using LLMs at current capability levels. My guess is more than the majority of current work in the economy, and of course I will also be able to do a lot of new things that are now cheaper. My guess is this alone is enough to do something about as big as the industrial revolution.
Most work is just really quite boring and doesn’t require a coherent world models across many domains.
Part of my own reconciliation is to question the premise that they would already be capable of ushering in a new industrial revolution. I’ve become more skeptical over time as these basic reasoning issues persist. It’s hard for me to imagine an industrial revolution’s worth of progress and innovation powered by a mind so lacking in coherent world models across so many domains.
Well, steam engines have even less coherent world models.
I believe in their power from seeing just how much value they give me and how transformative they are for me. I’m a super early adopter, but if I extrapolate the rest of the world making as much use of the tech as I am, and doing all the things I could see doing, it’s still so much.
But aren’t a lot of your tasks the sort of thing where
there is in fact a ton of training-available data demonstrating good performance
it’s cheap to experiment
etc., other relevant peculiarities of your use cases
?
I think the claim might be true but I don’t see a super compelling reason to think so at the moment.
“Reasoning” helping with self-driving cars might be a compelling demo, but what it would be compelling about is “you can slap together robotics, big data for a specific domain, and some LLM reasoning stuff to duct tape some more of the decision-making, and get something that’s practically useful”. Generalizing to other robotics could kick off a revolution, but it would be slow-going I think?
There could be a fair amount of science overhang, where you just have to search hard enough to put X and needs-X together. E.g. people curing themselves by searching hard using LLMs. Exciting, but not an industrial revolution? In the grand scheme of science it’s not mostly that. A lot of the coolest stuff is really hard, which means there’s not that many people at the forefront, which means that people at the forefront are already familiar with a lot of what’s relevant.
If you can find domains where iteration can be done pretty automatedly, but it’s expensive enough that decision-making still matters, but decision-making is very cognitively costly, but getting kinda-okay-not-creative decision-making would still be quantitatively better, then you could unlock some sort of new paradigm of invention / discovery. E.g. automated labs running automated experiments designing proteins by gippity-tweaking, or similar. Like PACE. But that would also be hard to get started on.
What are other reasons to think this? Plausible I just haven’t seen the idea, haven’t tried too hard.
Huh, this seems like a very weird comparison to me. It is very clear that I can automate a huge amount of labor using LLMs at current capability levels. My guess is more than the majority of current work in the economy, and of course I will also be able to do a lot of new things that are now cheaper. My guess is this alone is enough to do something about as big as the industrial revolution.
Most work is just really quite boring and doesn’t require a coherent world models across many domains.