AI on the Edge - TinyML and Machine Learning for Edge Devices - Session 1

Explore cutting-edge research on TinyML and machine learning for edge devices in this symposium session from USC Information Sciences Institute. Delve into four compelling research presentations covering neural inertial navigation in ultra-resource-constrained devices, embedding deep learning models in tiny IoT devices, distributed transformer models in edge environments, and collaborative training of large models at the edge. Gain insights from experts Luis Garcia, Peter Beerel, John Paul Walters, and Salman Avestimehr as they discuss innovative approaches to implementing AI in resource-limited edge computing scenarios.

USC AI Futures Symposium: AI on the Edge | Welcome & Session I