LLMs will absolutely be like that. The speed this technology is moving at makes me certain, especially over a period of 10-20 years; 20 years ago I was bugging friends for a GMail invite and AI was a joke left to academics.
I think it will even be solved soon, like, within the next 18 to 36 months. Hallucinations are the biggest problem consumers have with LLMs and a solution to that would be instantly worth billions of dollars. I’m sure every company in this space is desperately trying to figure it out before everyone else.
A non-deterministic system will always make mistakes, but we’ll hit a target where LLMs make fewer mistakes than humans and that will be good enough for almost all applications.
I don't know if you can "fix" hallucinations without changing the fundamental architecture. The other factor in this article is that prior to the AI summary at the top, Google could simply state that it was an error on the part of the website owner. Now it is being held liable for whatever the summary states - even if it's more accurate, it can still be wrong enough times to be expensive.
This is disregarding the entire mechanism by which LLMs work. How close to this ideal are the current frontier level ai is now? If you do a cost/improvement analysis does it look like it can reach a usable threshold?
I don’t know the numbers but as user, it seems impossible for it to be useful without expert review. It is also debatable if it brings any value when you consider the cost of building and using LLMs and the time of expert. Also need to include the opportunity cost the expert is spending on reviewing slop instead of creating work themselves and the long term consequences of this on the expert himself