I don't think any improvements in existing models changes the AGI landscape. Existing architectures perfected to 99.99% accuracy gets you a bunch of narrow/weak super intelligent models and not AGI. If you had millions of those for every economically useful task, that would pass for AGI.

R&D needs to max out on existing architectures before they will seriously branch out and search the possibility space for something that will get you a proper learning algorithm.

If you want AGI, you will need the R&D community to realize existing models won't get them what they want and they need to explore elseware.