Spiking Neural Networks (SNN) and Neuromorphic Computing

Biologically inspired models are growing in popularity as a mean to acheive better performance and more generalization with AI. Spiking Neural Networks (SNN) simulate the spikes used by biological neurons to communicate with each other.

Why are Spiking Neural Networks interesting?

1. They closely model the propagation of biological signal in neural networks.
2. They capture information from the time dimension, not only from the space dimension.
3. They can achieve great efficiency when implemented in Neuromorphic Hardware.

To gain an introductory overview on SNN, you can read A Review of Computing with Spiking Neural Networks. If you want to play around with code, you can follow the python snnTorch Tutorial. For an example of Neuromorphic Hardware implementing SNN, you can check out Intel's Loihi Processor.

If you find this topic interesting, please join us for the evening!

Here's the plan for the evening:

🍕 18:30: Pizza & drinks
👋 19:00 - 19:30: Getting to know each other
👨‍🏫 19:30 - 20:30: Formal introduction to Spiking Neural Networks and Neuromorphic Computing
💬 20:30 - 21:30: Casual round table discussion on SNN and Neuromorphic Computing in relation to AGI

Hope to see you there!