Generative AI Unleashed: Advancements, Transformative Applications and Future Frontiers

by Karthik Ramamurthy (Editor), Suganthi Kulanthaivelu (Editor), Shajina Anand (Editor), Thangavel Murugan (Editor)

Overview

Today's generative AI has been marked by the advent of neural networks, inspired by the human brain, which are trained to recognize patterns in a dataset. Once the network is trained, it can make decisions or predictions without being programmed to perform tasks. Generative AI learns from a set of data without explicit instructions and can create and generate new digital content such as text, audio and art. Recent models are beginning to overcome challenges such as computational power, data quality and training stability.

This edited book on generative AI presents novel perspectives, approaches and methodologies, as well as security, ethical and legal considerations, and future trends. Topics and technologies covered include generative transformers and text generation models, generative models for human-like speech synthesis, generative AI for image synthesis, data synthesis for privacy protection, and exploration of the impact of generative AI in fields including industry 4.0, astronomy, and brain tumour detection. Two chapters offer perspectives on ethics and legality.

Generative AI Unleashed: Advancements, transformative applications and future frontiers will serve as a valuable resource for researchers, engineers, advanced students and lecturers operating in the domains that are significantly impacted by generative AI.

Product Details

ISBN-13:	9781837240999
Publisher:	Institution of Engineering & Technology
Publication date:	07/01/2025
Series:	Computing and Networks
Pages:	324
Product dimensions:	6.14(w) x 9.21(h) x 0.75(d)

About the Author

Karthik Ramamurthy is an associate professor in the Research Centre for Cyber Physical Systems at the Vellore Institute of Technology, Chennai, India. His research interests include deep learning, computer vision, digital image processing, and medical image analysis. He has published 80+ papers in peer reviewed journals and conferences and is an active journal reviewer. He obtained his doctoral degree from the Vellore Institute of Technology and his master's degree from Anna University, India.

Suganthi Kulanthaivelu is an associate professor in the School of Electronics Engineering, Vellore Institute of Technology, Chennai, India. Her areas of research interest focus on artificial intelligence, wireless sensor networks, internet of things applications and industrial IoT, and image processing. She has published 20+ research papers in journals and at conferences. She holds a PhD degree in wireless sensor networks from Anna University, India.

Shajina Anand is an assistant professor and manager of the Cybersecurity Lab at Seton Hall University, NJ, USA. With over a decade of experience in both industry and academia, her research interests include artificial intelligence, data engineering, cloud computing security, and cybersecurity, including authentication, ethical hacking, cyberattacks, and cyber detection. She holds a PhD degree in cloud data security from Anna University, India.

Thangavel Murugan is an assistant professor in the Department of Information Systems and Security, College of Information Technology, United Arab Emirates University, UAE. He specializes in data science for cybersecurity, information security, ethical hacking, cyber forensics, blockchain, and high-performance computing (HPC). He has published in international journals and at conferences and authored 15+ book chapters. He is a senior member of the IEEE and a professional member of the ACM.

Table of Contents

• Chapter 1: Introduction to generative artificial intelligence
• Chapter 2: Unveiling the generative power: an introduction to generative AI algorithms and their evolution
• Chapter 3: Generative transformers and text generation models
• Chapter 4: Generative models for human-like speech synthesis: evolution, trends and the road ahead
• Chapter 5: Generative AI in image synthesis: review and recent advancements
• Chapter 6: Harnessing generative AI for enhanced brain tumor detection in clinical trials
• Chapter 7: A systematic review of GAN-based models in data synthesis for privacy protection
• Chapter 8: Impact of generative AI on Industry 4.0 and digital transformation
• Chapter 9: Navigating the ethics and legality of deepfake technology: advancements, implications and responsible deployment
• Chapter 10: Cosmic creativity: exploring generative AI in astronomy
• Chapter 11: Ethical and legal considerations of generative AI
• Chapter 12: Trending technologies and application of generative AI
• Chapter 13: Conclusion