Engineering Application of Artificial Intelligence

Abstract When engineering students graduate from university, large number of them will be working for engineering industries. Artificial Intelligence and Machine Learning have a game-changing contribution to industrial and engineering-related problems. This technology will completely change the future of many industries through a transformational increase of the efficiency and accuracy of the problem solving. The contributions of Artificial Intelligence and Machine Learning to many engineering industries can be summarized in two classes: Class One: Minimization or avoidance of assumptions, interpretations, and simplifications in order to build highly realistic models of the physical phenomena. Class Two: Minimization of computational footprint of the numerical models such that they can act in a realistic and practical manner. There are major differences between modeling and solving Engineering versus Non-engineering related problems using Artificial Intelligence and Machine Learning. Successful and realistic application of Artificial Intelligence and Machine Learning in engineering disciplines requires engineering domain expertise above and beyond expertise in AI & ML. This fact challenges the current state of hypes and marketing schemes of this technology in multiple engineering disciplines. Expertise in engineering application of Artificial Intelligence is not only about understanding the mathematical characteristics of the machine learning algorithms. It is very important for engineers to know about (a) Ethics of Artificial Intelligence in engineering, (b) Expertise of Artificial Intelligence, (c) Modeling Physics using Artificial Intelligence, and (d) Differences between Artificial Intelligence and Traditional Statistics.