Even if LLMs never get any more reliable than your average human, they're still valuable because they know much more than any single human ever could, run faster, only eat electricity, and can be scaled up without all kinds of nasty social and political problems. That's huge on its own.
Or, put another way, LLMs are kind of an concentrated digital extract of human cognitive capacity, without consciousness or personhood.
Hopefully, for the former.
Be a bit terrifying if it turns out "attention is all you need" for that too.
I assure you, those still exist in AI. AI follows whatever political dogma it is trained on, regardless of if you point out how logically flawed it is.
If it is trained to say 1+1=3, then no matter what proofs you provide, it will not budge.
Generally, you want some external way of verifying that you have something useful. Sometimes that happens naturally. Ask a chatbot to recommend a paper to read and then search for it, and you’ll find out pretty quick if it doesn’t exist.
The common case we see publicized today is people poking around with prompts, but isn't it more likely, or at least a risk, that mass adoption will look more like AI running as longlived processes talked with managing done system on their own?
If by “AI” you mean “bare GPT-style LLMs”, no, they can’t do that.
If you mean “systems consisting of LLMs being called in a loop by software which uses a prompt structure carefully designed and tested for the operating domain, and which has other safeguards on behavior, sure, that’s more probable.
One way to think about it, though, is that many important processes have a non-zero error rate. Particular those involving people. If you can put bounds on the error rate and recover from most errors, maybe you can live with it?
An assumption that error rates will remain stable is often pretty dubious, though.
Think about it: 100 people ask Jeeves who won the space race. They would all get the same results.
100 people ask Google who won the space race. They'll all get the same results, but in different orders.
100 people ask ChatGPT who won the space race. All 100 get a different result.
The LLM itself just emulates the collective opinions of everyone in a bar, so it's not a credible source (and cannot be cited anyway). Any two of these people arguing their respective GPT-sourced opinions at trivia night are going to be forced to go to a more authoritative source to settle the dispute. This is no different than the status quo...
The purpose is to serve as a component of a system which also includes features, such as the prompt structure upthread, that mitigates the undesired behavior while keeping the useful behaviors.