Good reading: https://en.wikipedia.org/wiki/Post-scarcity https://en.wikipedia.org/wiki/Kardashev_scale then follow it up with a bit of 1993, https://edoras.sdsu.edu/~vinge/misc/singularity.html and https://web.pa.msu.edu/people/yang/RFeynman_plentySpace.pdf
(oh, huh, I just noticed that There's Plenty of Room at the Bottom starts with a reference to the discovery of superconduction)
AI today is a glorified search algorithm.
You can argue all language is a form of search, but that is missing completely what transformer models are bringing to the table, and not just within language.
Your comment says nothing about whether we are “near AGI”, only that we find images within Rorschach blobs (as a metaphor for GPT4 generated text).
> AI today is a glorified search algorithm.
and not the comment about AGI, given as that is a pedantic argument I have no wish engaging in.
> only that we find images within Rorschach blobs
I'm sorry, I'm not sure you understand what GPT-4 offers. Things like generating novel code to solve a novel problem are not finding "images within Rorschach blobs". I think you should sit down with the technology and explore with a more open mind.
My understanding is that there are still some others that need to be figured out, like "The physical structure holding the thing getting the everloving shit bombarded out of it by high energy neutrons and causing it to degrade and fail over time"
We need to design better geometries for reactors so that we can channel the plasma flow to better improve containment while quickly removing wastes from the highly compressed energetic region where fusion mostly occurs. If we could do that, then that mostly solves the issues from reactor degradation and significantly improves efficiency.
The trouble is that at such high energy levels the plasma flow is relatively chaotic so high fidelity models are required to predict the behavior accurately.