Large language model

A large language model (LLM) is a computational model capable of language generation or other natural language processing tasks. As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process.^[1]

The largest and most capable LLMs, as of August 2024^[update], are artificial neural networks built with a decoder-only transformer-based architecture, which enables efficient processing and generation of large-scale text data. Modern models can be fine-tuned for specific tasks or can be guided by prompt engineering.^[2] These models acquire predictive power regarding syntax, semantics, and ontologies^[3] inherent in human language corpora, but they also inherit inaccuracies and biases present in the data they are trained on.^[4]