Year: 2025
Type: article
Abstract: In the context of AI, where optimization and rapid processing are paramount, Vedic Mathematics presents a valuable set of tools that can enhance algorithmic performance. The methods inherent to Vedic Mathematics—such as pattern recognition, digit manipulation, and modular arithmetic—align with the principles of algorithmic efficiency and computational optimization critical to AI systems. This paper investigates how Vedic techniques can be integrated into modern computational frameworks to improve algorithmic processes, reduce computational overhead, and accelerate problem-solving. We analyze the core Sutras and their applications in comparison with contemporary computational techniques, highlighting how these ancient methods can be adapted to optimize data processing, enhance numerical accuracy, and contribute to algorithmic innovation. By drawing parallels between Vedic Mathematics and current AI methodologies, this study elucidates the potential synergies and practical applications of these historical techniques in advancing the field of artificial intelligence.
Author: Babita Trivedi
Institution: Amity University
Language: English
Subfield: Theoretical Computer Science
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411322921