Edge Computing and its Role in Enhancing Artificial Intelligence and Machine Learning Applications in the Cloud

Abstract

As the number of connected devices continues to expand at a dizzying rate, a new paradigm known as "edge computing" has emerged to meet the rising need for low-latency, real-time data processing. Faster and more efficient processing is made possible by bringing computation and data storage closer to the sources of data through edge computing. The function of edge computing in improving cloud-based AI and ML applications is investigated in this article. We discuss the benefits and challenges of integrating edge computing with AI/ML, and present use cases demonstrating the potential of this synergistic combination. We also examine the architectural considerations, resource management strategies, and security aspects of edge-based AI/ML systems. Through this comprehensive review, we highlight the transformative impact of edge computing on enabling intelligent, responsive, and scalable AI/ML applications in various domains.