THE STAGES OF MODERN HANDBALL MANAGEMENT AND ITS PLACE IN GLOBAL SPORTS

Abstract

In the digital age, the rapid growth of data traffic and the demand for high-speed, low-latency communication systems have made optical communication networks a fundamental infrastructure for global connectivity. These networks offer exceptional bandwidth and reliability but face increasing challenges due to rising traffic complexity, latency sensitivity, and performance demands. This paper explores the integration of Artificial Intelligence (AI) technologies into optical communication networks as a solution to optimize performance, manage traffic efficiently, and enhance real-time decision-making. The study presents an overview of optical network architecture and its challenges, analyzes the limitations of traditional optimization methods, and demonstrates how AI—through machine learning, deep learning, and reinforcement learning—can be leveraged to address issues like congestion, packet loss, and inefficient routing. Real-world implementations by major technology firms are reviewed to highlight the transformative impact of AI on network reliability, scalability, and automation. The findings underscore AI’s critical role in enabling adaptive, intelligent, and future-ready optical communication systems.