[Technical foundations of large language models]

Large language models (LLMs) such as ChatGPT have rapidly revolutionized the way computers can analyze human language and the way we can interact with computers.

To give an overview of the emergence and basic principles of computational language models.

Narrative literature-based analysis of the history of the emergence of language models, the technical foundations, the training process and the limitations of LLMs.

Nowadays, LLMs are mostly based on transformer models that can capture context through their attention mechanism. Through a multistage training process with comprehensive pretraining, supervised fine-tuning and alignment with human preferences, LLMs have developed a general understanding of language. This enables them to flexibly analyze texts and produce outputs of high linguistic quality.

Their technical foundations and training process make large language models versatile general-purpose tools for text processing, with numerous applications in radiology. The main limitation is the tendency to postulate incorrect but plausible-sounding information with high confidence.