Accelerating Inference and Training at the Edge

Join us for a talk by Maxence Ernoult, Research Scientist at Rain, on accelerating inference and training at the edge.

  • Maxence Ernoult
  • March 5, 2024

Maxence will present us Rain’s vision and technological roadmap to build hardware optimized for inference and training at the edge including both the hardware and algorithm aspects with an emphasis on why physical and mathematical principles matter more to him than biological inspiration.

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Accelerating Inference and Training at the Edge

About the Speaker

Maxence Ernoult graduated from Ecole Polytechnique and the University of Cambridge in 2016, specializing in applied mathematics and theoretical physics. His PhD research was conducted in neuromorphic computing at Sorbonne University, in collaboration with Mila. During this time, he specialized in developing hardware-friendly alternatives to backpropagation and played a significant role in scaling up several of these alternatives, including Equilibrium Propagation and Difference Target Propagation. This work was undertaken alongside notable figures such as Ben Scellier, Blake Richards, and Yoshua Bengio. In 2021, Maxence joined IBM Research, focusing on AI safety. Subsequently, in 2022, he began a new position at Rain.

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  • Federico Corradi
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Join Dr. Federico Corradi as he explores low-power spiking neural network processing systems, offering insights into energy-efficient computing for extreme-edge applications.