Generative Artificial Intelligence
A. Dinesh Kumar (Hrsg.), R. Nidhya (Hrsg.), D. Pavithra (Hrsg.), S. Balamurugan (Hrsg.), Manish Kumar (Hrsg.)
Naturwissenschaften, Medizin, Informatik, Technik / Informatik
Beschreibung
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.
Kundenbewertungen
Computational Intelligence, Natural Language Processing, Soft Computing, Content Intelligence, Neuro Computing Algorithms, Diseases Prediction, Algorithmic Approach for Industrialization, Supervised Learning, Decision Support Systems, Image Processing, Artificial Intelligence, Generative AI, Brain Tumor Detection, Conversational Intelligence, Generative Adversarial Network