I get what the optimism is about in theory. Parsing unstructured data is something we can now do that we couldn't before. It adds a whole new vector to the span of software, a big piece of capability that software now has whose emergent, unforeseen consequences we can't predict.
I'm just not quite sure I buy this. It feels to me like there's a light motte-and-bailey going on, where supposedly AI is going to be a paradigm shift that changes the very notion of what's possible, but the actual proposals are mostly about LLMs being a finite-multiplier enhancement for the existing ability of software to model and optimize processes.
In particular, a big fraction of the concrete proposals seem to be about making business processes more efficient. Are businesses generally constrained by this to begin with? Like businesses don't seem to be sprinting at the edge of software technology to get as much efficiency as they can, buying diminishing returns from existing tech and waiting eagerly for the next wave of improvements. Judging by revealed preferences, it just doesn't seem like a very high priority for them.
Taking your automated library example, that sounds very cool from a hacker/tinkerer perspective and I'm sure it would result in some efficiency improvements, but it just doesn't seem like, no offense to anyone, a problem that needs urgent attention. How does this significantly improve the situation for anyone involved?
Of course it's true that we don't know what we don't know, and I don't disagree that often technology changes the world in unpredictable ways or even that current AI could possibly lead to this. At risk of being the dropbox-is-just-rsync guy, I'm just skeptical about the following pattern:
(1) some new tech gets invented that's supposedly the next internet;
(2) no one can quite explain or plausibly hypothesize how; but
(3) in the meantime, a wave of companies start building "platforms" and selling shovels to people who will supposedly later build the actual useful thing.