LLM (Large Language Model)

A large language model (LLM) is the core technology behind modern AI assistants. It’s a system trained on enormous amounts of text — books, articles, code, conversations — until it learns the patterns of language well enough to understand what you ask and generate a fluent, relevant response.

What an LLM actually does

At its heart, an LLM predicts the most likely next piece of text given everything before it. That sounds simple, but scaled up across billions of examples, it produces something remarkably capable: models that can draft emails, summarise documents, answer questions, write and debug code, and hold a coherent conversation.

Tools like ChatGPT, Claude, and Gemini are all built on large language models. They differ in size, training, speed, and cost, but they share this same underlying idea.

What LLMs are good and bad at

LLMs excel at language tasks — writing, summarising, explaining, translating, and reasoning through problems step by step. Their main weakness is that they only know what they were trained on, and they can occasionally state wrong information confidently (often called “hallucination”). Techniques like RAG exist specifically to ground them in real, current data.

LLM in one sentence

A large language model is an AI trained on huge amounts of text so it can understand your questions and generate human-like answers.