This book presents a comprehensive and accessible guide to today’s most influential artificial intelligence (AI) models including GPT, LLaMA, Gemini, Claude, Falcon, DeepSeek, Qwen, Grok, and modern Retrieval-Augmented Generation (RAG) systems. Large language models (LLMs) are advanced computer programs that can understand and generate human language, and they power everyday tools such as chatbots, search engines, translation apps, and writing assistants. However, most people use these systems without knowing how they work or why different models behave differently. This book explains, in simple and clear terms, the inner machinery behind modern AI models—how they are built, trained, and improved, so that readers can better understand the technology shaping education, business, healthcare, and everyday communication. Through clear explanations, diagrams, and real-world examples, the authors demystify how these models are designed, trained, evaluated, and deployed across text, image, audio, and multimodal tasks. Ideal for students, educators, developers, and AI enthusiasts, this book bridges the gap between cutting-edge research and practical understanding, offering an essential roadmap to the rapidly evolving world of generative AI.

Deepshikha Bhati, P.D., is an Assistant Professor in the Department of Computer Science at Kent State University. She recently earned her Ph.D. with a dissertation titled Towards Enhanced AI Explanation and Interaction with Users. Her research interests include Explainable Artificial Intelligence (XAI), information visualization, generative AI, Large Language Models (LLMs), deep learning, machine learning, image processing, and human-centered AI systems. Dr. Bhati has authored and co-authored numerous journal articles, conference papers, and book chapters in the fields of AI, visualization, and intelligent systems. She is also a co-author of A Beginner’s Guide to Generative AI: An Introductory Path to Diffusion Models, ChatGPT, and LLMs, also published by Springer.  Dr. Bhati’s research broadly focuses on improving AI explainability, semantic interaction, and visualization systems for applications in education and interactive AI systems. She is a member of IEEE, the IEEE Computer Society, and ACM.

Fnu Neha, Ph.D. is an instructor in Artificial Intelligence and Database System Design at Kent State University. She received her Ph.D. in Computer Science from Kent State University, and she completed her Master’s degree in Computer Applications from Panjab University in 2017 and qualified the UGC-NET examination in 2018.  She is an active member of ACM and IEEE and is affiliated with an AI research laboratory at Kent State University. Dr. Neha’s teaching areas include AI, image processing, computational health informatics, big data analytics, and database system design, and her research interests focus on applications of deep learning and computer vision in healthcare.

Aloysius Bathi Kasturiarachi, Ph.D. is a Professor of Mathematics at Kent State University, where he has worked for over 30 years. He won the Distinguished Teaching Award in 2001 and was a finalist in 2022. He is the recipient of numerous grants, totaling well over 10 million dollars. He also served as the Associate Dean for Academic Affairs at Kent State University at Stark from August 2013 to January 2018. He teaches courses in mathematics and computer science, and his research interests include partial differential equations, non-integrable systems, numerical analysis, mathematics education, and number theory. He has published extensively in these areas and is a member of MAA and AMS.

Angela Guercio, Ph.D., is a Professor of Computer Science at Kent State University, where she has worked for over 20 years. Prior to joining Kent State University, she served as an assistant professor at Hiram College for three years and as a senior research associate at the University of Salerno, Italy, for 16 years. Her research interests include smart e-education and AI, big data, data mining, software engineering, visual languages, human-machine interaction, and multimedia computing. She has co-authored numerous papers published in scientific journals and refereed international conferences. Dr. Guercio has received multiple research awards and fellowships for her work and is a member of IEEE, the IEEE Computer Society, and ACM.