Machine Learning Based System

Machine learning (ML)-based systems are rapidly evolving, focusing on improving model performance, reliability, and safety, particularly in large-scale applications like recommendation systems and autonomous vehicles. Current research emphasizes automated optimization of training processes for massive models, rigorous testing methodologies to ensure system reliability and compliance with safety standards, and the development of explainable AI techniques to enhance transparency and trust. These advancements are crucial for deploying reliable and safe ML systems across diverse sectors, impacting everything from industrial automation to critical infrastructure.