language model built with very large amounts of texts
A large language model is a computer system trained on vast amounts of text data to understand and generate human language. It matters because it can perform a wide range of language tasks—like answering questions, writing, and translation—which makes it useful for many practical applications.
AI-generated from the Wikipedia summary — may contain errors.
A large language model (LLM) is a neural network trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate and analyze text in many contexts, and are a foundational technology behind modern chatbots. Biased or inaccurate training data can make an LLM's output less reliable.
As of 2026, the most capable LLMs are based on transformer architectures, which, according to the 2017 paper "Attention Is All You Need", can be more efficient and parallelizable than earlier statistical and recurrent neural network models.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).