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11.9 MB
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April 22, 2026, 2:26 p.m.
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(Last updated: April 22, 2026, 2:26 p.m.)
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| ['Raza K. Generative AI. Current Trends and Applications 2024.pdf'] | 0 bytes |
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| Uploaded by andryold1 | Size 11.9 MB | Health [ 24 /27 ] | Added 2026-04-22 |
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SOURCE: Raza K. Generative AI. Current Trends and Applications 2024
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COVER
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MEDIAINFO
Textbook in PDF format This comprehensive volume focuses on the latest advancements in Generative AI, including state-of-the-art techniques and models that are pushing the boundaries of what is possible. It covers recent developments in areas such as Generative AI models, transfer learning and Natural Language Processing (NLP) highlighting their potential to revolutionize content generation and creative applications including OpenAI, LangChain, NLTK and their practical implementations across diverse domains. The volume provides insights into emerging research areas, novel architectures, and innovative approaches in Generative AI, giving searchers a glimpse into the exciting future of the field. The aim is to offer readers a deep understanding of Generative AI and how it can be harnessed to tackle complex real-world challenges. Artificial Intelligence (AI) has seen unprecedented growth and development over the past decade. Among its many branches, generative AI (GenAI) stands out for its remarkable ability to create new and original content, whether it be in the form of text, images, music, or even complex simulations. The potential applications of generative AI (GenAI) are vast and varied, impacting industries as diverse as healthcare, entertainment, education, and finance. In recent years, GenAI has demonstrated its transformative potential across numerous domains. From generating realistic images and text to advancing drug discovery and enhancing creative processes, the applications of GenAI are as varied as they are impactful. The methodological development of GenAI has progressed from early statistical methods to sophisticated neural networks and deep learning models. Breakthroughs like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Transformers, and Large Language Models (LLMs) have significantly advanced the field, enabling the generation of highly realistic and diverse content across various domains. The field continues to evolve with innovations in model architectures, training techniques, and applications. Techniques like diffusion models, energy-based models, and hybrid approaches combining different generative methods are being explored. As GenAI becomes more powerful, there is a growing focus on addressing ethical issues, such as bias, misinformation, and the societal impact of AI-generated content. Researchers and policymakers are working on frameworks to ensure responsible development and deployment of generative AI. The book Generative AI: Current Trends and Applications aims to provide a comprehensive overview of the latest advancements and practical applications of GenAI. This book is designed to be a valuable resource for researchers, practitioners, students, and anyone with an interest in the transformative power of AI technologies. The inspiration for this book stemmed from our collective experiences as researchers and educators in the field of computer science. We have witnessed the rapid evolution of AI technologies and their increasing impact on various aspects of our lives. Our goal with this book is to encapsulate the current state of GenAI, highlight cutting-edge research, and explore real-world applications that demonstrate the profound capabilities of these technologies. Fundamentals and Evolution of Generative AI Generative Artificial Intelligence: Fundamentals and Evolution Fundamentals of Encoders and Decoders in Generative AI Applications and Solutions in Generative AI Ethical and Social Considerations in Generative AI Advanced Techniques and Models Transformative Applications of Generative AI
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