
Why AI models invent things: the mechanism, in plain terms
Brandi ReedHallucination isn't a bug awaiting a patch — it's how next-word prediction behaves when knowledge runs out, and the documented mitigations reduce it without repealing it.
Model launches, version changes, price moves, deprecations, safety policy revisions and outages.

Hallucination isn't a bug awaiting a patch — it's how next-word prediction behaves when knowledge runs out, and the documented mitigations reduce it without repealing it.

"Multimodal" once meant a separate vision model bolted on; it now means one system that reads text, images, audio, and video together — and the difference shows up in what you can hand it in one prompt.

Chatbot, assistant, agent — the industry uses the words interchangeably and the difference is real: an agent takes multi-step actions in the world, which means its failure modes are errands gone wrong, not bad answers.

Everything in your current conversation, plus selected facts carried across sessions — the two mechanisms behind a chatbot's memory are different things with different failure modes, and vendors document both.

The scores in every model launch are real measurements of something — but contamination, saturation, and the gap between test performance and your Tuesday afternoon are why numbers alone never settle it.

Every serious AI release ships with a documentation page — and its benchmark table, limitations list, and safety section tell you more than any launch event, if you know which parts are load-bearing.