The interesting question to me at the moment is whether we are still at the bottom of an exponential takeoff or nearing the top of a sigmoid curve. You can find evidence for both. LLMs probably can't get another 10 times better. But then, almost literally at any minute, someone could come up with a new architecture that can be 10 times better with the same or fewer resources. LLMs strike me as still leaving a lot on the table.

If we're nearing the top of a sigmoid curve and are given 10-ish years at least to adapt, we probably can. Advancements in applying the AI will continue but we'll also grow a clearer understanding of what current AI can't do.

If we're still at the bottom of the curve and it doesn't slow down, then we're looking at the singularity. Which I would remind people in its original, and generally better, formulation is simply an observation that there comes a point where you can't predict past it at all. ("Rapture of the Nerds" is a very particular possible instance of the unpredictable future, it is not the concept of the "singularity" itself.) Who knows what will happen.