Mathematics: The Core Engine Behind AI Systems

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Authors: Mr. Rushikesh Kalhale, Mr. Venkatesh Bansode, Mr. Utkarsh Maske, Prof.Deepa Shivshimpi
Cited by: 0

Abstract

Mathematics is at the base of all Artificial Intelligence (AI) systems. Throughout the AI lifecycle, mathematics is the pillar for representing data at the start, learning, reasoning on behalf of the human user and adapting in the mid-section, and finally optimizing any algorithm or data driven model at the end. This paper will discuss how the main mathematics will start to emerge as critical constructs for AI - linear algebra, calculus, probability and statistics, and optimization. We will demonstrate the pertinence of mathematical models as a pathway for the development of neural networks, machine learning algorithms, and data driven decision systems. In demonstrating examples of how mathematics has evolved as part of the responsive development of Artificial Intelligence, we can clearly delineate the ongoing, sometimes inescapable, role mathematics will have in defining intelligent systems in the future.

Fields of Study & Subjects

Artificial Intelligence Applications Neural Networks and Applications Machine Learning and Algorithms

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 January 2026
Language
EN