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This book explores the rapidly advancing fields of Generative Artificial Intelligence (GAI) and Large Language Models (LLM), offering a comprehensive examination of their development, applications, and ethical implications. It delves into the historical evolution of these technologies, training methods, and challenges faced by GAI models. The book covers essential topics such as prompt engineering, fine-tuning, and reinforcement learning with human feedback. It also presents various case studies in finance and e-commerce, showcasing practical applications of GAI and LLM. The editors aim to provide readers with a deeper understanding of the transformative potential of these technologies and their impact on innovation and productivity. Targeted at researchers, practitioners, and students in the fields of artificial intelligence and machine learning, the book offers insights into future directions and open problems in GAI.
Artificial intelligence. --- Machine learning. --- Artificial intelligence --- Machine learning
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Striking a balance between the technical characteristics of the subject and the practical aspects of decision making, spanning from fraud analytics in claims management, to customer analytics, to risk analytics in solvency, the comprehensive coverage presented makes Big Data an invaluable resource for any insurance professional.
Big data. --- Insurance --- Insurance. --- Data processing. --- Insurance companies --- E-books
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