This book offers a timely and comprehensive contribution to the discourse surrounding Generative AI and Large Language Models. Through rigorously developed chapters, the authors present profound scholarly questions, analyze current practical applications, and articulate the evolving state of the field across diverse, domain-reshaping applications. We anticipate that this work serves as a valuable resource and catalyst for further research

Covers a wide range of topics, including generative AI, large language models and intelligent systems Combines theoretical foundations with practical implementations Targeted towards a broad range of readers interested in AI, including students, professionals,and technology enthusiasts

Inhalt

From Access to Agency: Rethinking the Democratization of Generative AI.- E-Health Data Protection in the Generative AI World: A Comparative Analysis of Legal Frameworks and Breaches.- Understanding Generative Models: Manifold Hypothesis and Approximation Capabilities.- Advancing Explainability in LLM-based Generative AI via Paraconsistent Annotated Evidential Logic E.- Leveraging Generative Artificial Intelligence for Enhanced Data Augmentation in Emotion Intensity Classification: A Comprehensive Framework for Cross-Dataset Transfer Learning.