I liken it to VR. That was a big hype before AI and while I really love the tech (I have 5 headsets) I could have told anyone that the expectations were insane. The investors truly believed that in 2-3 years time everyone would be doing everything with a big headset on. It was dragged into lots of situations where it didn't belong.
Then of course the hype collapsed and now even the usecases where VR shines are deemed a flop. But no, it's exceptionally good at simulation (racing/flight) and visualising complex designs while 3D designing.
I see the same with generative AI and LLM. It's really good with programming. It's definitely good at making quick art drafts or even final ones for those who don't care too much about the specifics of the output. I use it a lot for inspiration.
But it's not good for everything that it's trying to be sold as. Just like the VR craze they're dragging it by the hairs into usecases where it has no business being. A lot of these products are begging to die.
For example an automation tool using real world language. For that it's a disaster, it's inconsistent and constantly confuses itself. It's the reason openclaw is a foot bazooka. It's also not very great at meeting summaries especially those where many speakers are in a room on the same microphone.
I don't think AI will disappear but a realignment to the usecases where it actually adds value, yes I hope that happens soon.
Ugh... a balanced take, this isn't appropriate for social media! /s
> It's also not very great at meeting summaries especially those where many speakers are in a room on the same microphone.
It is astonishingly poor at this. My intuition was that it should be good at this (it is basically a translation problem right? And LLMs are fundamentally translation systems) but the practical results are so poor. Not just mis-identifying speakers (frequently saying PersonX responded to PersonX) but managing complete opposite conclusions from what was actually said.
I'm genuinely intrigued as to what approaches have been taken in this space and what the "hard problem" is that is stopping it being good.