An AGI that can do all that would also necessarily be able to do all white collar work. That latter definition I'd consider a "soft threshold" that would be hit before recursive self-improvement, which I imagine would happen soon after.
The current estimation on the time between this is fairly small, bottlenecked most likely by compute constraints, risk aversion, and need to implement safeguards. Metaculus puts it at about 32 months
https://www.metaculus.com/questions/4123/time-between-weak-a...
Sure, but that’s like saying we’re close att infinite life because we’ve expanded our life expectancy.
I don’t really buy into the ”one part equals another”, we are very quick to make those assumptions but they are usually far from the science fiction promised. Batteries and self driving cars comes to mind, and organic or otherwise crazy storage technologies, all ”very soon” for multiple decades.
It’s very possible that white collar jobs get automated to a large degree and we’ll be nowhere closer to AGI than we were in the 70’s, I would actually bet on that outcome being far more likely.
I think AGI by that definition (ability to self-improve) is closer than many people think largely because current models are very close to human intelligence in many domains. They can answer questions, derive theorems, write code, navigate websites, etc. All the work that current AI research scientists do is no more than these general information processing tasks, scaled up in terms of creativity, long-term coherence, sensitivity to bad/good ideas over the span of a larger context window, etc.
The leap between Opus 4.7/GPT 5.5 and what would be sufficient for AGI seems smaller than the leap between The invention of the Transformer model (2017) and today, thus by a very conservative estimate I think it will take no more time between then and now as it will between now and an AI model as smart as any human in all respects (so by 2035). I think it will be shorter though because the amount of money being put into improving and scaling AI models and systems is 100000x greater than it was in 2017.