This book provides an up-to-date and easy-to-read introduction to Generative AI and its revolutionary contribution to building Industry 5.0. Written for both practitioners and interested readers, it is a clear and compelling overview of the technologies at the heart of the next industrial revolution.
The book introduces the conceptual notions behind generative models, large language models (LLMs), and the neural networks that drive them. It delves into the mathematical and conceptual foundations of Generative AI, transformer architecture, and the practical applications of language and vision models. Further, the book links the innovations to Industry 5.0, discussing digital twins, predictive maintenance, DevOps, and cybersecurity in intelligent systems. It encompasses real-world applications of AI in areas such as finance, manufacturing, and smart infrastructure. Case studies, like the application of generative models in FinTech and blockchain adoption, underscore how AI is already transforming business and society around the world.
The book is perfect for students, researchers, and practitioners of AI, data science, and industrial systems interested in comprehending the theory and practical applications of Generative AI. It also benefits educators and policymakers who wish to lead in cutting-edge technological advancements, with emphasis on responsible, secure, and human-oriented AI applications for a brighter future.
Table of Contents:
1. Generative and Open AI. 2. Decoding the Generative Transformer: Core of Gen AI. 3. Evolution of Language Understanding and Large Language Models. 4. Generative AI for Industry 5.0: The Role of Diffusion Models in Next-Generation Landscapes. 5. Software Engineering Reimagined and Development. 6. The Evolution of Industry: From 1.0 to 5.0. 7. System and Design Perspective for Industry 5.0. 8. Security Paradigm for Industry 5.0. 9. Generative AI for FinTech. 10. Mirror Reality: Exploring the Realm of Digital Twin Systems. 11. Cloud-Powered Intelligence: Integrating Generative AI for Scalable Innovation in Industry 5.0. 12. Ethical and Regulatory Aspects of AI in Industry 5.0. 13. The Trust Fabric: AI, Agents, and Cybersecurity in Industry 5.0. 14. AI-Assisted Smart Energy Infrastructure for a Sustainable Industry 5.0 to Support Virtual Power Plant. 15. Self-Evolving Twins: Shaping Ethical, Resilient, and Human-Centered Industry 5.0. 16. Graph Neural Networks in Industry 5.0: Smart Connectivity and Predictive Intelligence. 17. Automated Documentation Using Generative AI in Version-Controlled Projects.
About the Author :
Sangeeta Sharma is an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology Hamirpur, Himachal Pradesh, India. She earned a PhD in computer science at the Maulana Azad National Institute of Technology Bhopal in 2017. Her research interests include virtualization technologies, cloud computing, artificial intelligence/machine learning, federated learning, and distributed systems, with a focus on efficient and scalable resource management.
Robin Singh Bhadoria is an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology Hamirpur, Himachal Pradesh, India. He specializes in big data analytics, IoT, machine learning, and wireless networks. He earned a PhD at the Indian Institute of Technology Indore and an MTech (Gold Medalist) at Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, in computer science engineering.
Mukesh Kumar Giluka is an assistant professor in the School of Engineering, Jawaharlal Nehru University, New Delhi, India. He earned a PhD at the Indian Institute of Technology Hyderabad. His research interests include 5G/6G networks, Wi-Fi networks, V2X communication, ISAC, and Open RAN.
Review :
‘The editors have assembled a stellar line-up of contributors, who together explore every aspect of this cutting-edge topic. Combining research and practice, this will be an indispensable text for all readers.’
Brian A. Martin, University of East London, UK; Past President, UCAP
