Also known as: confabulation · AI hallucination
A hallucination is output from an AI model that is fluent and confident but factually incorrect or entirely fabricated, such as an invented citation, a non-existent API method, or a plausible-sounding but false statistic.
Hallucination follows from the training objective. A model optimised to produce plausible continuations has no separate mechanism distinguishing 'plausible and true' from 'plausible and false', and no internal representation of its own uncertainty that reliably surfaces in its output.
This makes hallucinations especially hazardous in technical contexts, because fabricated content is generated with exactly the same confident register as accurate content. Retrieval grounding, citation requirements, and verification against authoritative sources reduce the rate but do not eliminate it.
A model asked for research supporting a claim may produce a citation with a realistic author list, journal name, and DOI format — none of which correspond to a real paper.
Large Language Model
A large language model (LLM) is a neural network trained on vast quantities of text to predict likely continuations of a sequence, producing systems capable of generating coherent language, answering questions, and writing code.
Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) is a technique in which relevant documents are retrieved from an external knowledge source and supplied to a language model as context, so that its response is grounded in specific retrieved material rather than parametric memory alone.
Grounding
Grounding is the practice of tying a model's output to specific verifiable source material, so that claims can be traced to documents rather than resting on the model's parametric memory.
AI Evaluation
AI evaluation is the practice of systematically measuring model performance against defined tasks and criteria, using benchmarks, human review, or automated graders to quantify capability and detect regressions.
Prompt Injection
Prompt injection is an attack in which malicious instructions are embedded in content an AI system processes — a web page, document, or email — causing the model to follow the attacker's instructions instead of the application's.