It seems to be slowing down actually. Last year was wild until around llama 3. The latest improvements are relatively small. Even the reasoning models are a small improvement over explicit planning with agents that we could already do before - it's just nicely wrapped and slightly tuned for that purpose. Deepseek did some serious efficiency improvements, but not so much user-visible things.
So I'd say that the AI race is starting to plateau a bit recently.
While I agree, you have to remember the dimensionality of the labor-skill space is. The was I see it is that you can imagine the capability of AI as a radius, and the amount of tasks it can cover is a sphere. Linear imporovements in performance causes cubic (or whatever the labor-skill dimensionality is) imporvement in task coverage.
I‘m not sure that’s true with the latest models. o3-mini is good at analytical tasks and coding, and it really sucks at prose. Sonnet 3.7 is good at thinking but lost some ability in creating diffs.
So I'd say that the AI race is starting to plateau a bit recently.