@@ -2,9 +2,8 @@ We welcome **Emre Neftci**, new head of PGI-15, at FZJ and in the JULAIN communi
**Meta-Training Neuromorphic Hardware with Differentiable Programming**
on 15 November 2021, 11:30am
as a virtual meeting at: Virtual Meeting using [BigBlueButton](https://webconf.fz-juelich.de/b/wen-mym-pj7)
on 15 November 2021, 11:30am<br>
as a virtual meeting at: [BigBlueButton](https://webconf.fz-juelich.de/b/wen-mym-pj7)
**Abstract:**
Online “life-long” learning at the edge is an aspirational goal of AI technologies. Neuromorphic hardware is particularly attractive in this regard, thanks to its emphasis on local learning algorithms and its potential compatibility with future and emerging devices. With recent advances in training neuromorphic hardware using differentiable programming, it is now possible to achieve competitive accuracy and performance compared to Deep Neural Networks (DNNs). In practice, however, the data-intensive and iterative training procedure that powers DNNs is incompatible with the device non-idealities and real-time operation that characterize neuromorphic hardware. In this talk, I will argue that gradient-based meta-learning can play a critical role in closing this gap, enabling accurate, few-shot learning, even in the presence of certain severe device non-idealities. As a result, meta-learning has the potential to redefine the target metrics used in the design of emerging nanodevices for neuromorphic computing."
