Introduction to Generative AI

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.

• 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