THE ROLE OF MATHEMATICS IN ADVANCING ARTIFICIAL INTELLIGENCE: A THEORETICAL AND APPLIED PERSPECTIVE

Mathematics is the backbone of AI. It offers the foundation for algorithms, innovations, learning models, and restores efficient decision-making processes in creating intelligent systems. This paper discusses key mathematical areas that support AI, such as linear algebra, the theory of probability, calculus, graph theory, and optimization. It illustrates how basic mathematical principles enable machine learning, deep learning, and data-driven decision-making. Additionally, the paper investigates real-time AI applications in health, finance, and autonomous systems, pointing to the intractable requirement for a fusion of mathematic reasoning with novel AI progress. Finally, it addresses some modern mathematical questions regarding AI and the mathematical work that shall inform the development of intelligent systems with a view to the future.