One model I have is that when things are exponentials (or S-curves), it’s pretty hard to tell when you’re about to leave the “early” game, because exponentials look the same when scaled. If every year has 2x as much activity as the previous year, then every year feels like the one that was the big transition.
For example, it’s easy to think that AI has “gone mainstream” now. Which is true according to some order of magnitude. But even though a lot of politicians are talking about AI stuff more often, it’s nowhere near the top of the list for most of them. It’s more like just one more special interest to sometimes give lip service too, nowhere near issues like US polarization, China, healthcare and climate change.
Of course, AI isn’t necessarily well-modelled by an S-curve. Depending on what you’re measuring, it could be non-monotonic (with winters and summers). It could also be a hyperbola. And if we all dropped dead in the same minute from nanobots, then there wouldn’t really be a mid- or end-game at all. But I currently hold a decent amount of humility around ideas like “we’re in midgame now”.
You get more discrete transitions when one s-curve process takes the lead from another s-curve process, e.g. deep learning taking over from other AI methods.
One model I have is that when things are exponentials (or S-curves), it’s pretty hard to tell when you’re about to leave the “early” game, because exponentials look the same when scaled. If every year has 2x as much activity as the previous year, then every year feels like the one that was the big transition.
For example, it’s easy to think that AI has “gone mainstream” now. Which is true according to some order of magnitude. But even though a lot of politicians are talking about AI stuff more often, it’s nowhere near the top of the list for most of them. It’s more like just one more special interest to sometimes give lip service too, nowhere near issues like US polarization, China, healthcare and climate change.
Of course, AI isn’t necessarily well-modelled by an S-curve. Depending on what you’re measuring, it could be non-monotonic (with winters and summers). It could also be a hyperbola. And if we all dropped dead in the same minute from nanobots, then there wouldn’t really be a mid- or end-game at all. But I currently hold a decent amount of humility around ideas like “we’re in midgame now”.
You get more discrete transitions when one s-curve process takes the lead from another s-curve process, e.g. deep learning taking over from other AI methods.