Large Language Model

A Large Language Model (LLM) is a foundation model trained on text to predict the next token, capable of generating, summarising, and reasoning over natural language.

What is Large Language Model?

LLMs are transformer neural networks with billions of parameters, trained on web-scale text. They generate output by sampling tokens conditioned on a prompt and prior context. Useful behaviours like instruction following, code generation, and tool use emerge through additional training stages such as supervised fine-tuning and reinforcement learning from human feedback. LLMs do not have memory across calls unless explicitly given one, and they can produce confident-sounding errors known as hallucinations.

How does Large Language Model apply to enterprise AI?

Enterprises use LLMs for drafting, classification, extraction, summarisation, and grounded question answering. Production systems pair the model with retrieval, validation, and citation steps to reduce hallucination risk and produce auditable outputs.