This is probably the most important single piece of evidence about AGI timelines right now. Well done! I think the trend should be superexponential, e.g. each doubling takes 10% less calendar time on average. Eli Lifland and I did some calculations yesterday suggesting that this would get to AGI in 2028. Will do more serious investigation soon.

Why do I expect the trend to be superexponential? Well, it seems like it sorta has to go superexponential eventually. Imagine: We've got to AIs that can with ~100% reliability do tasks that take professional humans 10 years. But somehow they can't do tasks that take professional humans 160 years? And it's going to take 4 more doublings to get there? And these 4 doublings are going to take 2 more years to occur? No, at some point you "jump all the way" to AGI, i.e. AI systems that can do any length of task as well as professional humans -- 10 years, 100 years, 1000 years, etc.

Also, zooming in mechanistically on what's going on, insofar as an AI system can do tasks below length X but not above length X, it's gotta be for some reason -- some skill that the AI lacks, which isn't important for tasks below length X but which tends to be crucial for tasks above length X. But there are only a finite number of skills that humans have that AIs lack, and if we were to plot them on a horizon-length graph (where the x-axis is log of horizon length, and each skill is plotted on the x-axis where it starts being important, such that it's not important to have for tasks less than that length) the distribution of skills by horizon length would presumably taper off, with tons of skills necessary for pretty short tasks, a decent amount necessary for medium tasks (but not short), and a long thin tail of skills that are necessary for long tasks (but not medium), a tail that eventually goes to 0, probably around a few years on the x-axis. So assuming AIs learn skills at a constant rate, we should see acceleration rather than a constant exponential. There just aren't that many skills you need to operate for 10 days that you don't also need to operate for 1 day, compared to how many skills you need to operate for 1 hour that you don't also need to operate for 6 minutes.

There are two other factors worth mentioning which aren't part of the above: One, the projected slowdown in capability advances that'll come as compute and data scaling falters due to becoming too expensive. And two, pointing in the other direction, the projected speedup in capability advances that'll come as AI systems start substantially accelerating AI R&D.