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Machine Learning at the Extreme Edge - an Open Platform Approach

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Edge ML is a megatrend, as privacy concerns and networks bandwidth/latency bottlenecks prevent cloud offloading of sensor analytics functions in many application domains. The next revolution is that of “Extreme Edge AI” pushes aggressively towards sensors and actuators. In this talk I will describe an Extreme Edge AI platform based on open source parallel ultra-low power (PULP) Risc-V processors and accelerators, from its academic inception to the creation of an innovation ecosystem. I will then conclude looking into open challenges and opportunities in this exciting field.

Luca Benini holds the chair of digital Circuits and systems at ETHZ and is Full Professor at the Universita di Bologna. He received a PhD from Stanford University. He has been visiting professor at Stanford University, IMEC , EPFL. In 2009-2012 he served as chief architect in STmicroelectronics France. Dr. Benini’s research interests are in energy-efficient computing systems design, from embedded to high-performance. He is also active in the design ultra-low power VLSI Circuits and smart sensing micro-systems. He has published more than 1000 peer-reviewed papers and five books. He is an ERC -advanced grant winner, a Fellow of the IEEE , of the ACM and a member of the Academia Europaea. He is the recipient of the 2016 IEEE CAS Mac Van Valkenburg award and of the 2019 IEEE TCAD Donald O. Pederson Best Paper Award.

This talk is part of the Wednesday Seminars - Department of Computer Science and Technology series.

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