Stream Processing

Stream processing focuses on efficiently analyzing continuous data flows, aiming to extract real-time insights and support timely decision-making. Current research emphasizes optimizing stream processing across diverse hardware (edge devices, cloud), employing machine learning (including neural networks like X3D) for tasks like operator placement and adaptive resource management, and integrating transactional stream processing for robust handling of large language model updates. This field is crucial for applications ranging from IoT analytics and autonomous driving to real-time AI model training, impacting both the efficiency of data-intensive systems and the development of novel AI applications.