Hallucinations are a mathematical necessity of powerful AI rather than just a bug that can be patched out.
Developers often assume that better data or more training will eventually stop AI from making things up. This paper proves a fundamental computability-theoretic limit that makes hallucinations inevitable in complex domains. You cannot have a system that is both highly expressive and guaranteed to be error-free. This means that as AI gets more capable of solving hard problems, the risk of plausible-sounding errors will always remain. We must build our infrastructure around the assumption that AI can never be one hundred percent reliable. Hallucination is the price we pay for intelligence.