AI-Enabled Global Education Networks on the Cloud

Abstract

The rapid advancement of Artificial Intelligence (AI) and Quantum Computing (QC) technologies presents transformative opportunities for optimizing global education and 6G wireless networks. This paper explores the convergence of AI and Quantum Cloud Computing (QCC) and its implications for enhancing network performance and educational systems. We propose an AIdriven Quantum Cloud Computing framework designed to leverage quantum algorithms and AI models for optimizing 6G network configurations and improving educational experiences globally. The framework integrates quantum computing’s capabilities to solve complex optimization problems and AI’s proficiency in predictive analytics and data-driven decisionmaking. We evaluate the framework’s performance across key metrics, including latency reduction, bandwidth utilization, energy efficiency, and throughput improvement. The results indicate significant advancements in network performance, including up to a 25% increase in throughput efficiency and a 52% reduction in packet loss rates. Additionally, the framework enhances global education by optimizing network infrastructure to support high-speed, reliable access for educational content and interactive learning environments. This paper demonstrates the potential of AI-driven QCC in addressing the challenges of next-generation networks and education systems, offering insights into its practical applications and future research directions.