FWF - SMALL - Spiking Memristive Architectures for Learning to Learn

Project: Research project

Project Details


Contemporary AI applications often rely on deep learning, which implies heavy computational loads with current technology. However, there is a growing demand for low-power autonomously learning AI systems that are employed “in the field”. We investigate in this project options for learning in low-power unconventional hardware that is based on spiking neural networks (SNNs) implemented in analog neuromorphic hardware combined with nano-scale memristive synaptic devices.
Effective start/end date1/02/2031/01/23