Title: Networked AI: A Leap in Data and Intelligence Efficiency

Abstract:

Through an analysis of cutting-edge research in Networking Systems of AI (NSAI), we explore the evolving direction and key challenges of shifting from end-to-end large models to networked, distributed, and autonomous intelligence. The presentation highlights the benefits that Networked AI offers in data and intelligence efficiency compared to end-to-end models. It also discusses its applications in pioneering fields such as embodied intelligence, spatial intelligence, and industrial intelligence.

Biography:

Professor Liang Song has been a Distinguished Professor at Fudan University. He also concurrently serves as President of the International Institute on Networking Systems of AI, Chairman of the Shanghai 5G-VR Industry Alliance, Chief Scientist for multiple listed companies, among other services. Prof. Song’s work integrates artificial intelligence with communication networks within practical communication application systems to empower a wide range of industries. It enables online evolutive learning and real-time sensing and control in intelligent networking systems, serving as a vital pathway to constructing full-scenario, universal Networked AI.