AI Native Course
Glossary

Hallucination

Output that is fluent and plausible but factually wrong or invented.

Hallucination is not a bug that will be patched out; it is a consequence of models optimising for likely continuations. It becomes dangerous when it is automated and nobody reads the output.

Mitigations that work in practice: ground answers in retrieved sources, ask for citations, require the model to say when it does not know, and design a UI that makes verification cheap.

Where this shows up in the course

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