This took a weird turn in an article that I thought would explore the basic scientific challenges of nanotech and why we don’t have it yet. I do think that the erosion of religion has some negative externalities in modern society (ie. lack of easy meaning and direction in life and downfall of local community kinship), but no I don’t think that is the main reason why we don’t have nanotech specifically. I don’t even think that’s the primary reason we are more polarized politically now (my current thoughts lean towards changes in information consumption, communication, and trust in institutions).
But specifically nano-printers? Of course people want that, as much as people want quantum computing, fusion energy, brain-computer interfaces, and life-extension. The benefits are obvious, from the money-making opportunities alone. Maybe reality is just disapointing: it’s a harder problem than people originally expected without any economically viable intermediate steps (the kind that bolster AI reasearch now) so progress is stuck in a quagmire.
I agree that most of the recent large model gains have been due to the surplus of compute and data, and theory and technique will have to catch up eventually … what I’m not convinced on is why that would necessarily be slow.
I would argue there’s a theory and technique overhang with self-supervised learning being just one area of popular research. We haven’t needed to dip very deeply yet since training bigger transformers with more data “just works.”
There’s very weak evidence that we’re hitting the limits of deep learning itself or even just the transformer architecture. Ultimately, that is the real limiter … certainly data and compute are the conceptually easier problems to solve. Maybe in the short-term that’s enough.