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Demystifying Artificial Intelligence : Symbolic, Data-Driven, Statistical and Ethical AI

This book is intended for business professionals that want to understand the fundamental concepts of Artificial Intelligence, their applications and limitations. Built as a collaborative effort between academia and the industry, this book bridges the gap between theory and business application, demy...

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Autor principal: Emmanuel Gillain
Formato: Libro
Publicado: De Gruyter 2024
Acceso en línea:Ver este registro en EBSCOhost
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          Artificial intelligence
      ab: This book is intended for business professionals that want to understand the fundamental concepts of Artificial Intelligence, their applications and limitations. Built as a collaborative effort between academia and the industry, this book bridges the gap between theory and business application, demystifying AI through fundamental concepts and industry examples. The reader will find here an overview of the different AI techniques to search, plan, reason, learn, adapt, understand and interact. The book covers the two traditional paradigms in AI: the statistical and data-driven AI systems, which learn and perform by ingesting millions of data points into machine learning algorithms, and the consciously modelled AI systems, known as symbolic AI systems, which use explicit symbols to represent the world and make conclusions. Rather than opposing those two paradigms, the book will also show how those different fields can complement each other. All royalties go to a charity. “Demystifying AI reveals its true power: not as a mysterious force, but as a tool for human progress, accessible to all who seek to understand it.” Dr. Barak Chizi, Chief Data & Analytics Officer, KBC Group
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