This chapter provides an overview of the technology underpinning large language models (LLMs). It introduces the historical context of artificial intelligence (AI), from symbolic systems to statistical approaches and deep neural networks, highlighting milestones in natural language processing (NLP). It also addresses the limitations of LLMs, such as hallucinations, biases, and a lack of explainability, and the different types of LLMs according to their information-sharing approaches. The chapter aims to help readers understand LLMs and their underlying algorithms, setting the stage for a deeper exploration of ethical considerations and applications in subsequent sections of the book.