
What AI Can Do
Description
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Critically considering this issue from philosophical, interdisciplinary, and engineering perspectives, respectively, this book assesses the scope and pertinence of AI technology and explores how it could bring about both a better and more unpredictable future.
What AI Can Do highlights, at both the theoretical and practical levels, the cross-cutting relevance that AI is having on society, appealing to students of engineering, computer science, and philosophy, as well as all who hold a practical interest in the technology.
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Persons
Elvira G. Rincon-Flores holds a PhD in Education Sciences from the University of Salamanca, Cum Laude thesis. Actually, she is an Impact Measurement Research Scientist at the Institute for the Future of Education of the Tecnologico de Monterrey, and she is also a professor at the same institution. She belongs to the National System of Researchers of Mexico (SNI-Level 2), and the research groups: GRIAL and GIIE, the University of Salamanca, and Tecnologico de Monterrey, respectively. She is the leader of the following research projects: Adaptive Learning, Gamification in Higher Education, Student Mentoring, Wellbeing Students, and Educational Spaces. It also collaborates with the University of Lima in the development of a dynamic platform for Gamification called Gamit! Her lines of research are Educational Innovation Evaluation and Educational Gamification.
Gildardo Sanchez-Ante is a full-time professor and researcher at the Tecnologico de Monterrey School of Engineering and Sciences, Campus Guadalajara. Holds a PhD in Computer Science from Tecnologico de Monterrey in 2002. From 1999-2001 he was a Visiting Researcher at the Robotics Laboratory of Stanford University and from 2004-2005 he was a Research Fellow at the National University of Singapore. He is a Senior Member of the IEEE and the ACM. Member of the National System of Researchers (SNI). His research interests are in automatic learning and pattern recognition, as well as its application to robotics. He has recently worked in the computational modeling of nanomaterial properties to optimize their performance.
Content
massive therapy in the future. Classification Machine Learning applications for Energy Management Systems in Distribution Systems.
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