International Journal of Science, Engineering and TechnologyAuthors: Shyamala Vimala
Abstract: Mathematics is the backbone of Artificial Intelligence (AI) and modern computer applications. AI systems use mathematical concepts such as linear algebra, calculus, probability, statistics, discrete mathematics, and optimization to process data, recognize patterns, and make intelligent decisions. These concepts support technologies including machine learning, neural networks, robotics, computer vision, cyber security, and data science. Linear algebra is used for vectors and matrices in neural networks, while calculus supports optimization and model training. Probability and statistics help systems make predictions under uncertainty. Discrete mathematics forms the basis of algorithms, logic, and cryptography. Optimization techniques improve the accuracy and efficiency of intelligent systems. The integration of mathematics with AI and computer science has transformed sectors such as healthcare, education, banking, agriculture, and transportation. Although challenges such as computational complexity, privacy concerns, and ethical issues remain, mathematics continues to drive innovation and technological advancement in AI and computer applications.
DOI: http://doi.org/10.5281/zenodo.20584270
