Introduction to Generative AI
Theoretical Foundations, Analysis and Practical Use Cases
1st Edition
Will be published approx. on 1. July 2026
Book
Hardback
376 pages
978-1-032-98848-1 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Undergraduate Advanced and Undergraduate Core
Illustrations
16 s/w Tabellen, 45 s/w Photographien bzw. Rasterbilder, 45 s/w Abbildungen
16 Tables, black and white; 45 Halftones, black and white; 45 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-032-98848-1 (9781032988481)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Jamuna S. Murthy | Siddesh G M
Introduction to Generative AI
Theoretical Foundations, Analysis and Practical Use Cases
E-Book
approx. 07/2026
Chapman and Hall
€65.99
Not yet available
Jamuna S. Murthy | Siddesh G M
Introduction to Generative AI
Theoretical Foundations, Analysis and Practical Use Cases
E-Book
approx. 07/2026
Chapman and Hall
€65.99
Not yet available
Persons
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 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. His main areas of research interests include the Internet of Things, Distributed Computing and Data Analytics. He is a member of ISTE, IETE, etc.
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. His main areas of research interests include the Internet of Things, Distributed Computing and Data Analytics. He is a member of ISTE, IETE, etc.
Content
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