Название: Generative Artificial Intelligence: Concepts and Applications
Автор: R. Nidhya, D. Pavithra, Manish Kumar, A. Dinesh Kumar, S. Balamurugan
Издательство: Wiley-Scrivener
Год: 2025
Страниц: 292
Язык: английский
Формат: pdf (true)
Размер: 62.5 MB

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.

Generative AI is redefining the capabilities of machines to create and innovate. Unlike traditional AI, which analyzes existing data, Generative AI produces new and original content across images, text, music, and more by leveraging neural networks and deep learning techniques to learn patterns and relationships from vast datasets.

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 (NLP). 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.

This book provides an understanding of generative models, neural networks, and data generation algorithms. It caters to students, developers, data scientists, and AI practitioners, exploring practical applications across domains such as art, music, text generation, and image synthesis. It also examines real-world examples of Generative AI’s impact in industries like entertainment, healthcare, and design.

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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