Abstract

The advent of big data has ushered in an era of unprecedented data volumes, necessitating efficient and scalable sorting algorithms. Traditional sorting algorithms, while effective for smaller datasets, struggle to handle the massive data loads generated by modern applications. To address this challenge, AI-driven sorting algorithms have emerged as a promising solution, leveraging the power of machine learning and artificial intelligence to optimize sorting processes. This research paper provides a comprehensive overview of AI-driven sorting algorithms, exploring their underlying principles, methodologies, and applications in big data scenarios. I delve into the key techniques, including machine learning-based approaches. Additionally, I discuss the potential benefits and challenges associated with AI-driven sorting algorithms, highlighting their potential to significantly improve sorting efficiency, accuracy, and scalability in big data contexts.