August 7, 2025 – Large language models (LLMs) are a category of deep learning models trained on immense amounts of data, making them capable of understanding and generating natural language and other types of content to perform a wide range of tasks. LLMs are built on a type of neural network architecture called a transformer which excels at handling sequences of words and capturing patterns in text.

LLMs work as giant statistical prediction machines that repeatedly predict the next word in a sequence. They learn patterns in their text and generate language that follows those patterns.

LLMs represent a major leap in how humans interact with technology because they are the first AI system that can handle unstructured human language at scale, allowing for natural communication with machines. Where traditional search engines and and other programmed systems used algorithms to match keywords, LLMs capture deeper context, nuance and reasoning. LLMs, once trained, can adapt to many applications that involve interpreting text, like summarizing an article, debugging code or drafting a legal clause. When given agentic capabilities, LLMs can perform, with varying degrees of autonomy, various tasks that would otherwise be performed by humans.

Explore more of this topic with IBM's 2023 article "What are Large Language Models (LLM)”?