How Large Language Models Work

Learn how large language models like GPT and Gemini work under the hood in plain English

How Large Language Models Work translates years of expert research on Large Language Models into a readable, focused introduction to working with these amazing systems. It explains clearly how LLMs function, introduces the optimization techniques to fine-tune them, and shows how to create pipelines and processes to ensure your AI applications are efficient and error-free.

In How Large Language Models Work you will learn how to
• Test and evaluate LLMs
• Use human feedback, supervised fine-tuning, and Retrieval augmented generation (RAG)
• Reducing the risk of bad outputs, high-stakes errors, and automation bias
• Human-computer interaction systems
• Combine LLMs with traditional ML

How Large Language Models Work is written by some of the best machine learning researchers at Booz Allen Hamilton, including researcher Stella Biderman, Director of AI/ML Research Drew Farris, and Director of Emerging AI Edward Raff. In clear and simple terms, these experts lay out the foundational concepts of LLMs, the technology’s opportunities and limitations, and best practices for incorporating AI into your organization.

About the book
How Large Language Models Work is an introduction to LLMs that explores OpenAI’s GPT models. The book takes you inside ChatGPT, showing how a prompt becomes text output. In clear, plain language, this illuminating book shows you when and why LLMs make errors, and how you can account for inaccuracies in your AI solutions. Once you know how LLMs work, you’ll be ready to start exploring the bigger questions of AI, such as how LLMs “think” differently that humans, how to best design LLM-powered systems that work well with human operators, and what ethical, legal, and security issues can—and will—arise from AI automation.