LLM (Large Language Model)
An LLM (large language model) is a deep neural network—almost always a Transformer—trained on large amounts of text (and sometimes multimodal data) to model the probability of the next token given prior context. Its objective at training time is to minimize prediction error over billions of tokens, producing weights that encode grammar, facts (with limitations), reasoning patterns, and task-following behavior after alignment or instruction tuning. At inference time the same model generates completions, answers questions, summarizes documents, or drives agents; production systems expose it through APIs (often OpenAI-compatible) backed by engines such as vLLM or NIM. LLMs power chatbots, code assistants, RAG pipelines, and enterprise copilots.