MATHEMATICS AND ARTIFICIAL INTELLIGENCE

This article presents a comprehensive scientific analysis of the fundamental relationship between mathematics and artificial intelligence (AI). Artificial intelligence systems are deeply rooted in mathematical theory, relying on linear algebra, calculus, probability theory, statistics, optimization, and discrete mathematics. The effectiveness, scalability, and reliability of AI algorithms are determined by the robustness of their mathematical foundations. Particular attention is given to machine learning and deep learning, where mathematical modeling and numerical optimization techniques play a central role. The paper demonstrates that mathematics is not merely a supporting tool for AI, but its essential structural backbone, enabling intelligent systems to learn, generalize, and make decisions under uncertainty.

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