Oh interesting, you think the timeframe between proto-AGI and AGI is shorter than AGI to ASI?

I think by your definition we nearly have that with 2020 language models. We certainly could do it right now. I think 2023 is when we will do that, but it will require a few steps that need to be solved, at least so far as us in the general public assume it needs solved. They're working on it and I would be surprised if our next gen models in 2023 haven't at least been able to solve things like memory. Reinforcement Learning in the pretraining phase has massive potential to bridge the gap between a current narrow scope general AI and full blown generally capable AI that I'd define as proto-AGI.

But I think "strapping" together multiple models would fit the bill too. They aren't narrow AI, they're just not broadly general or capable enough to cover enough bases. We will see how it unfolds though.