tinyML Asia 2021 Yunxin Liu: Efficient on-device deep learning

tinyML Asia 2021
“Efficient on-device deep learning”
Yunxin LIU , Guoqiang Professor at Institute for AI Industry Research (AIR), Tsinghua University

With the advances of hardware, software, and artificial intelligence (AI), there is a new computing paradigm shift from centralized intelligence in the cloud to distributed intelligence on the edge. In the era of edge computing, it is critical to infuse AI to empower diverse edge devices and applications. This talk overviews the challenges and opportunities of on-device deep learning and introduces our recent research work on making on-device deep-learning more efficient, focusing on how to build affordable AI models customized for diverse edge devices and how to maximize the performance of on-device model inference by fully utilizing the heterogeneous computing resources.

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