Introduction to Generative AI

Theoretical Foundations, Analysis and Practical Use Cases
1. Auflage 2026
ISBN: 978-1-032-98848-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 376 Seiten, Format (B × H): 156 mm x 234 mm

Introduction to Generative AI: Theoretical Foundations, Analysis and Practical Use Cases

Generative Artificial Intelligence is reshaping how we create, learn, and imagine.
This book offers a clear and complete journey through the science and art behind this revolution — from how machines learn to produce text, images, and music, to how they are being built, tested, and applied in the real world.

The first part of the book lays out the ideas that make generative AI possible — neural networks, transformers, diffusion models, and the mysterious “latent spaces” where creativity meets computation. The middle chapters explore how today’s AI systems reason, plan, and use tools, drawing on powerful frameworks such as LangChain, LangGraph, and AutoGen. The final section moves beyond algorithms, discussing how to build safe, fair, and energy-conscious AI that serves human goals rather than replacing them.

Throughout, real-world examples bring the technology to life — from language models that write poetry, to multimodal systems that can paint or compose music, to intelligent agents that collaborate with humans in research, education, and design. Written in accessible language and supported by visual explanations, this book bridges deep technical ideas with human-centered understanding.

Highlights

- Explains the core principles of how generative models think and create

- Shows how AI systems combine text, vision, and sound in unified ways

- Connects theory with hands-on applications and real-world use cases

- Discusses ethics, creativity, and sustainability in the age of intelligent machines

- Written for learners, researchers, and professionals who want both clarity and depth

Introduction to Generative AI: Theoretical Foundations, Analysis and Practical Use Cases is an essential guide for anyone curious about how artificial intelligence is shaping the next chapter of human innovation.

Zielgruppe

Undergraduate Advanced and Undergraduate Core

Autoren/Hrsg.

Murthy, Jamuna S

G M, Siddesh

Inhaltsverzeichnis

SECTION I Theoretical Foundations of Generative AI, Chapter 1 Introduction to Generative AI, Chapter 2 Deep Learning Foundations of Generative Models, Chapter 3 Building Generative AI with TensorFlow and Keras, Chapter 4 GANs, VAEs, and Transformers, SECTION II Analysis and Advanced Techniques in Generative AI, Chapter 5 Advanced Techniques and Emerging Architectures in Generative AI, Chapter 6 Training and Evaluation of Generative Models, Chapter 7 LLMs, Agents, and Workflow Orchestration, Chapter 8 Real-World Applications and Deployment of Generative AI, Chapter 9 Multimodal, Interactive, and Embodied Generative AI, Chapter 10 Research Methodology and Open Problems in Generative AI

Über Autor(innen)

Jamuna S. Murthy is currently working as an Assistant Professor in the Department of Computer Science and Engineering at Ramaiah Institute of Technology, Bengaluru. An academic topper throughout her education, she received the Best Master's Thesis Award (2017) for her M.Tech dissertation on real-time sentiment analysis. She also secured funding from the Department of Science and Technology (DST), India (2021-2022) for FitQua: Smart Water Bottle, an AI-powered health monitoring product. She has authored and edited multiple scholarly works, including serving as editor of the book Cloud Security: Concepts, Applications and Practices (CRC Press, 2024). Her research contributions appear in SCI-indexed journals, Springer conferences, and international collaborations with institutions in the USA, China, and Europe. In recognition of her contributions to emerging fields in AI, she was honoured with the Best Young Researcher Award (2024) by the STEM Research Society. Jamuna is actively engaged in the global research community as a reviewer and program committee member for leading A*-ranked conferences, including AAAI, AISTATS, ACM Multimedia, and AVSS. Her primary expertise lies in Generative Artificial Intelligence, focusing on multimodal generation, diffusion models, affective computing, and computer vision. She is committed to advancing human centered AI through both theoretical innovation and impactful applications.

Siddesh G. M. is currently working as Professor and Head in the Department of CSE( AI&ML) and CSE(Cyber Security), M. S. Ramaiah Institute of Technology, Bangalore. He has published a good number of research papers in reputed International Conferences and Journals. He has authored books on Network Data Analytics, Statistical Programming in R, Internet of Things with Springer, Oxford University Press, and Cengage publishers, respectively. He has edited research monographs in the area of Cyber Physical Systems, Fog Computing and Energy Aware Computing, and Bioinformatics with CRC Press, IGI Global, and Springer publishers, respectively. His main areas of research interests include the Internet of Things, Distributed Computing and Data Analytics. He is a member of ISTE, IETE, etc.