In 30 years we will not have an iPhone-sized device with the power of today's supercomputers. Transistor scaling is in its final stages. We'll be lucky to get 2-3 more process nodes and that'll be it.
Perhaps quantum computing will enable new kinds of inference, then we will need to scale superconductors like we did transistors in the past 75 years, that is possible (not in the next 10-15 years though; 30-40 years is more realistic). However I don’t think this will lead to anything more then amazing statistical inference. People theorized artificial neural networks way back in the 1940s and we already had algorithms for it in the 1970s. I’m not aware of any algorithms, not even theoretical ones that gives us AGI, on any computing device (not even quantum computers).
However this misses my point about AGI. It is not about computing capabilities but theory. AGI will have to evaluate situations that has never arisen before without having data that directly directs it. I don’t see how statistical inference can do that, and as such we will need an entirely new methods of training it. Like I said, we haven’t even conceived how an AGI technology works, there are no algorithms which will work in theory even with unlimited computing power. Contrast this, for example, with quantum computing, which has a bunch of algorithms demonstrating it’s capabilities. With AGI all we have is “perhaps our cars become better at driving them selves”. I’m not buying it.
All that's needed is someone to achieve GAI at a supercomputer level. From then on, it's just a matter of scaling it down. Your iPhone has more compute power than a supercomputer 30 years ago, after all.
And what's also a way to "cheat" is fusing computers and organic matter. Brain-in-a-vat style, or, for yet another Star Trek reference, Voyager's organic compute network (which IIRC even suffered a pathogen infection at one point). And that is definitely possible in the next 10-15 years. Give Musk's Neuralink enough apes to euthanize and it will get done.