Applications of Number Theory in Machine Learning and Artificial Intelligence
Umesh Bibhishan Jadhav · Zenodo (CERN European Organization for Nuclear Research) · 2026
AI (Artificial Intelligence) is now one of the most revolutionary technologies of the 21st century that touch upon such domains as healthcare, finances, cybersecurity, and robotics. Although AI is usually also linked to machine learning, neural networks, and big data, the importance of mathematical foundations cannot be underestimated. The number theory is another valuable but frequently neglected branch of mathematics that the AI uses. Number theory concerns properties and relations of integers, prime numbers, modular arithmetic and cryptographic constructions. These ideas are important in data security, hashing algorithms, random number generation and optimization methods in AI systems. This paper discusses the use of number theory in artificial intelligence: cryptography, hash functions, pseudorandom number generators, data encoding and optimization algorithms. The paper emphasizes the role of classical ideas in number theory in the architecture of modern AI systems and their role in building secure and efficient intelligent systems.