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.
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.