This book is a comprehensive overview of AI fundamentals and applications to drive creativity, innovation, and industry transformation.
Generative AI stands at the forefront of artificial intelligence innovation, redefining the capabilities of machines to create, imagine, and innovate. GAI explores the domain of creative production with new and original content across various forms, including images, text, music, and more. In essence, generative AI stands as evidence of the boundless potential of artificial intelligence, transforming industries, sparking creativity, and challenging conventional paradigms. It represents not just a technological advancement but a catalyst for reimagining how machines and humans collaborate, innovate, and shape the future.
The book examines real-world examples of how generative AI is being used in a variety of industries. The first section explores the fundamental concepts and ethical considerations of generative AI. In addition, the section also introduces machine learning algorithms and natural language processing. The second section introduces novel neural network designs and convolutional neural networks, providing dependable and precise methods. The third section explores the latest learning-based methodologies to help researchers and farmers choose optimal algorithms for specific crop and hardware needs. Furthermore, this section evaluates significant advancements in revolutionizing online content analysis, offering real-time insights into content creation for more interactive processes.
Audience
The book will be read by researchers, engineers, and students working in artificial intelligence, computer science, and electronics and communication engineering as well as industry application areas.
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R. Nidhya, PhD, is an assistant professor in the Department of Computer Science & Engineering, Madanapalle Institute of Technology & Science, affiliated with Jawaharlal Nehru Technical University, Anantapuram, India. She has published many research papers in international journals and her research interests include wireless body area networks, network security, and data mining.
D. Pavithra, PhD, is an assistant professor at Dr. NGP Institute of Technology, Coimbatore, Tamil Nadu, India. Her current research interests include autism, machine learning, and deep learning.
Manish Kumar, PhD, is an assistant professor at The School of Computer Science & Engineering, VIT, Chennai, India. His research interests include soft computing applications for bioinformatics problems and computational intelligence.
A. Dinesh Kumar, PhD, is an associate professor at KL (Deemed to be University), Vijayawada, Andhra Pradesh, India. His current research interests include wireless body area networks, wireless sensor networks, network security, and artificial intelligence.
S. Balamurugan, PhD, is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamil Nadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman of the Renewable Energy Society of India (RESI), India. He has published 50+ books, 200+ international journals/conferences, and 35 patents.
This book is a comprehensive overview of AI fundamentals and applications to drive creativity, innovation, and industry transformation.
Generative AI stands at the forefront of artificial intelligence innovation, redefining the capabilities of machines to create, imagine, and innovate. GAI explores the domain of creative production with new and original content across various forms, including images, text, music, and more. In essence, generative AI stands as evidence of the boundless potential of artificial intelligence, transforming industries, sparking creativity, and challenging conventional paradigms. It represents not just a technological advancement but a catalyst for reimagining how machines and humans collaborate, innovate, and shape the future.
The book examines real-world examples of how generative AI is being used in a variety of industries. The first section explores the fundamental concepts and ethical considerations of generative AI. In addition, the section also introduces machine learning algorithms and natural language processing. The second section introduces novel neural network designs and convolutional neural networks, providing dependable and precise methods. The third section explores the latest learning-based methodologies to help researchers and farmers choose optimal algorithms for specific crop and hardware needs. Furthermore, this section evaluates significant advancements in revolutionizing online content analysis, offering real-time insights into content creation for more interactive processes.
Audience
The book will be read by researchers, engineers, and students working in artificial intelligence, computer science, and electronics and communication engineering as well as industry application areas.
"About this title" may belong to another edition of this title.
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