The field of Artificial Intelligence (AI) and Machine Learning (ML) stands at the forefront of a new era—an era marked by rapid technological transformation and profound societal implications. Once the subject of speculative fiction, AI and ML are now integral to everyday life, powering everything from personal assistants and healthcare diagnostics to autonomous vehicles and smart infrastructures. With this growing integration comes an urgent need to explore not only the technical aspects of these systems but also their ethical, social, and economic dimensions.
This edited volume, Artificial Intelligence and Machine Learning: Advances, Challenges and Visions, was conceived with a clear purpose: to provide a comprehensive and multidisciplinary perspective on the current state, emerging trends, and future directions of AI and ML. The book brings together contributions from scholars, practitioners, and thought leaders across diverse fields, each addressing key topics such as algorithmic innovation, responsible design, industry applications, policy implications, and the human-AI relationship.
We have structured the book into thematic sections to guide readers through foundational concepts, technical developments, practical applications, and visionary frameworks. While the content is varied, a unifying theme persists throughout: the belief that AI and ML must be developed and deployed in ways that reflect and respect human values.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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