Brain-Inspired Hardware and Algorithm Co-Design with Melika Payvand

EPISODE 585
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About this Episode

Today we continue our ICML coverage joined by Melika Payvand, a research scientist at the Institute of Neuroinformatics at the University of Zurich and ETH Zurich. Melika spoke at the Hardware Aware Efficient Training (HAET) Workshop, delivering a keynote on Brain-inspired hardware and algorithm co-design for low power online training on the edge. In our conversation with Melika, we explore her work at the intersection of ML and neuroinformatics, what makes the proposed architecture “brain-inspired”, and how techniques like online learning fit into the picture. We also discuss the characteristics of the devices that are running the algorithms she’s creating, and the challenges of adapting online learning-style algorithms to this hardware.

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Thanks to our sponsor Qualcomm AI Research

Qualcomm AI Research is dedicated to advancing AI to make its core capabilities — perception, reasoning, and action — ubiquitous across devices. Their work makes it possible for billions of users around the world to have AI-enhanced experiences on devices powered by Qualcomm Technologies. To learn more about what Qualcomm Technologies is up to on the research front, visit stage.twimlai.net/qualcomm.

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