Event date:
Jul 11 2023 10:00 am

Accelerating AI on a budget: tinyML and beyond

Dr. Muhammad Bilal
EE Reading Room, 2nd Floor, SBASSE Building LUMS
The ever-growing number of live video feeds in modern establishments has made it necessary to move the processing closer to the imaging sensors. This so called “Edge Computing” enables low latency, privacy, security, and scalability for AI applications in various domains. However, computing at the edge faces many challenges, such as limited energy and computing resources. To this end, a variety of hardware solutions are being considered. At one end of this spectrum is the trivial low resolution object detection on the smallest microcontrollers e.g. FOMO on ESP32-CAM microcontroller. At the other end, NVIDIA Jetson Orin/Xavier embedded GPUs offer high performance in small form factor albeit at a higher cost. RISC-V microprocessors (e.g. Kendryte K210) with dedicated Neural Processing Units (NPUs) offer a middle ground albeit at the expense of lesser portability. This talk will cover a brief overview of these alternative solutions followed by a group discussion on the merits of each approach with respect to cost, learning curve and computational/energy efficiency.

Dr. Muhammad Bilal is an educator, researcher and a maker. His research interests include Digital Image/Signal Processing, Machine Learning/AI, Digital/Analog circuit design, Embedded systems and Robotics. He is an Associate Professor in the Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah, KSA. Prior to joining KAU in 2014, he worked as a post-doctoral researcher at KAIST, South Korea. He obtained his PhD in EE from LUMS SBASSE in 2013.