AI on the Edge: Hardware-Software Co-Design for Graph Analytics and Neural Networks - Session 3

Explore cutting-edge research in hardware-software co-design for AI at the edge in this 50-minute session from the USC AI Futures Symposium. Delve into four compelling presentations by leading researchers: Murali Annavaram discusses out-of-core graph analytics through multi-log memory updates, Viktor Prasanna explores accelerating Graph Neural Networks, Ajey Jacob presents Processing-in-Pixel-in-Memory-based object detection and tracking, and Jose Luis Ambite examines federated progressive sparsification. Gain valuable insights into the latest advancements in AI edge computing and their potential impact on future technologies.

USC AI Futures Symposium: AI on the Edge | Session III