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An Introduction to Generative AI: Crafting Worlds From Code
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Author(s): Arokiaraj David (Al Tareeqah Management Studies, Swiss Business School, UAE), Jeganathan Gomathi Sankar (BSSS Institute of Advanced Studies, India), C. Ganeshkumar (Indian Institute Foreign Trade, India)and Mohammad Kashif (Graphic Era University (Deemed), India)
Copyright: 2024
Pages: 16
Source title:
Generative AI and Implications for Ethics, Security, and Data Management
Source Author(s)/Editor(s): Jeganathan Gomathi Sankar (BSSS Institute of Advanced Studies, India)and Arokiaraj David (Al Tareeqah Management Studies, Swiss Business School, UAE)
DOI: 10.4018/979-8-3693-8557-9.ch001
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Abstract
The chapter serves as an intricate exploration into the domain of Generative AI, offering a comprehensive understanding of its fundamental principles, diverse methodologies, and wide-ranging applications. Beginning with a clear definition and overview, it progresses to clarify key concepts such as probability distributions and sampling while providing an overview of various generative models, including autoregressive models, variational autoencoders, and generative adversarial networks. Architectural components, training methods, and optimization techniques are thoroughly examined, alongside an in-depth analysis of challenges and considerations in model design and selection. Through real-world examples, the chapter showcases the transformative potential of Generative AI across domains such as image generation, text processing, music composition, creative arts, etc. Addressing current limitations and outlining future directions offers valuable insights into the growing landscape of Generative AI, positioning it as a catalyst for innovation and creative expression.
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