A large language model predicts and generates text from patterns learned at scale — the engine behind many AI assistants.
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[ EXPLORE AI ]An LLM is a model trained on large text corpora to generate and transform language — answers, summaries, code, and dialogue. It is useful as a flexible interface over knowledge and tasks when paired with clear inputs and, where needed, retrieved sources.
Whilst LLMs sound like they “know” your business, in practice they only know training data plus what you put in the prompt. For example, asking for last quarter’s policy without retrieval invents a plausible answer. We often recommend treating the LLM as the reasoning layer — and grounding it with retrieval or tools when facts must be current.
The instruction or question you give a model — the input that shapes what it generates next.
A small chunk of text models read and write; length limits and cost are usually counted in tokens.
When a model produces fluent, plausible output that is not grounded in facts or provided sources.
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