Historical Evolution of Artificial Intelligence: From the Mathematics and Calculations of Ancient Civilizations to Modern Machine Learning

This book provides an overview of AI’s historical development, while understanding the cultural and scientific foundations that make AI possible. Through easy-to-understand explanations of complex ideas, and a focus on both technological advances and ethical considerations, it provides an understanding of AI’s past, present, and future.

Abbas Tcharkhtchi is a Full Professor at Arts et Métiers ParisTech (ENSAM), Paris, Fance. He was previously the head of the Polymers and Composites Group, the Head of the Processing, Mechanics, and Materials Department, and member of the institution’s research council. He was also the scientific manager of doctoral training at the Paris campus, where he was responsible for overseeing 70 PhD students. Currently, he is the president of the scientific and technical commission of the AFR association.

Sofiane Khelladi is a Full Professor at Arts et Métiers Institute of Technology in Paris, France. His research focuses on modeling and analyzing fluid flows for the design of complex fluid and energy systems. His preferred scientific approach is predominantly theoretical and numerical, often complemented by an experimental component for validation purposes. His research activities center around three main themes with strong interactions: advanced numerical methods for fluid and energy systems, multiphase flows and multiphysics coupling, and aero-hydrodynamics and acoustics of turbomachines.

Hamid Reza Vanaei is an Associate Professor at the Ecole Supérieure d’Ingénieurs Léonard de Vinci (ESILV), Léonard de Vinci University in Paris, France. He obtained his M.Sc. and Ph.D. in Mechanics of Materials from the Arts et Métiers Institute of Technology in Paris and works as an associate researcher at the same institute. With six years of experience in Material Science, Mechanical Engineering, and Advanced Manufacturing, his primary research focuses on a multidisciplinary approach to optimizing Advanced Manufacturing techniques.

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