What Are Large Language Models? A Plain-Language Guide to LLM Basics

Large language models (LLMs) like ChatGPT, Claude, and Gemini are neural network programs trained on trillions of words to predict the next word in a sequence, rather than to truly understand language. Models such as GPT-4 are built with an estimated 1.7 trillion parameters and trained on roughly 13 trillion tokens sourced from books, websites, and other internet text. After initial training, LLMs undergo additional fine-tuning to make them behave as helpful, instruction-following chatbots. While they excel at text generation, summarization, and code assistance, they struggle with accurate math, real-time information, and can confidently produce false statements — a phenomenon known as hallucination. Training a large model can cost between $50 million and $100 million, and ongoing inference costs mean API access typically comes with a price tag.