AI hallucinations are the central unsolved problem for deploying language models in regulated industries: medical devices, clinical decision support, drug discovery, and post-market surveillance. Standard LLMs hallucinate because of an architectural gap. They hold no internal state they must remain consistent with, so output is statistical pattern matching rather than a constrained read against a model of self, history, or relationship. This session walks through brain-aligned language models that mirror neurochemistry, with a live demonstration of an AI system whose hormone state, scar memory, and trust lattice are queryable in real time, plus regulatory implications for ALCOA+ audit trails, Predetermined Change Control Plans, and Class II 510(k) submissions.