I am reminded of Self Driving Cars. Back when that whole thing started executives were absolutely, iron clad certain that because a car drove itself through a desert for a good ways this meant cars that could drive themselves through cities were just around the corner. I think it was the CEO of General Motors that predicted that "hardware would be the hard part" and once that was solved cars would be driving themselves everywhere in no time! This was back in, oh, 2015 or so.
Over a decade later I can get into a car that drives itself in certain cities, if I want to hire one specifically. Maybe I can pay a ton of money to get a car that can mostly drive itself on the highway, in the right conditions, and as long as there isn't a 0.1% corner case wherein I have to take over immediately or I might die. So maybe it was harder than "just solving the hardware." And 2015 felt like where we're at with general AI now. It's brilliant at solving mathematics, because math has perfectly defined pass/not criteria entirely contained within itself. General AI is, good, at coding, because at least you can test code and see if it boots/throws errors, etc. and that's easy to brute force learn a billion times over running on your own nuclear plant. What exactly was is the test for "good" say... creativity? Because I was bored and asked Claude to pitch me a sequel to Alien as a test just 2 days ago, and I shit you not the title it came up with was "Alien: Lullaby" which is about as good as the rest of the pitch was.
My conclusion: check back over a decade from now to see where we are on this general AI thing, but everyone investing like general purpose AI is "just around the corner" sounds like the auto industry assuming self driving cars were just around the corner, and had managed to invest half the wealth of the entire planet on that assumption as fast as they could get hold of it.