Hardware Podcasts

On-Chip Learning is Missing Neuromorphic Building Block

EE Times Current · 8 Sept 2023 · 44m

What this episode covers

Elisabetta Chicca, chair of the bio-inspired Circuits and Systems research group at the University of Groningen, discusses building neuromorphic chips using sub-threshold analog CMOS and emerging memristor technologies to model biological learning and sensing. She explains how these physical systems handle noise and variability through population coding, and details the challenges of on-chip learning algorithms compared to traditional AI. The episode also features Ralph Etienne-Cummings from Johns Hopkins University, who expands on the role of materials science, 3D integration, and the ethical considerations of combining living tissue with artificial systems.

Most relevant to

makers and hobbyists

Topics

Mentioned

Companies
University of Groningen, Johns Hopkins University, Italian Institute of Technology, Cognigron
Chips
memristors, CMOS
Also
Neurobench

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