Algorithms Help Spiking Neural Networks Learn to Learn

In this episode of Brains and Machines, Professor Emre Neftci, director of the Neuromorphic Software Ecosystems group at the Peter Grünberg Institute (PGI), talks to Brains and Machines host, Dr. Sunny Bains. He and his PGI colleagues, part of the Jülich Research Centre in Germany, think about how neurons can be trained and organized to learn in an efficient and brain-inspired way. You’ll hear about his work in making backpropagation compatible with spiking neural networks, dealing with device variability, and one- and few-shot learning.

Discussion follows with Dr. Giulia D’Angelo from the Fortiss research institute in Munich, and Professor Ralph Etienne-Cummings of Johns Hopkins University.