Large language models (LLMs) are advanced artificial intelligence (AI) systems trained on vast amounts of text data that can understand, generate, and manipulate human language. They use machine learning techniques, particularly deep learning with neural networks, to learn patterns, grammar, context, and meaning from the data, enabling them to perform a wide range of natural language processing (NLP) tasks such as text generation, language translation, summarization, question answering, and even code generation. LLMs are typically based on transformer architecture that allows processing of large sequences of text in parallel, resulting in efficient learning from massive datasets. Examples of LLMs include OpenAI's ChatGPT, Google's Bard, Meta's Llama, and others. They are widely used across industries for chatbots, virtual assistants, content creation, and more, although they also pose challenges like high computational needs and ethical concerns.