Neurons are the exceptional cells that govern most part of animals' behaviors. These cells are highly interconnected in intricate networks which compose the central nervous system, aka the brain.

Research on neurons and their networks dates back to the beginning of 20th century, nonetheless there are more open problems than settled ones. On the other hand, the study of nervous tissue inspired several breakthroughs in computer science and it is commonly believed that neuromorphic computers will solve the energetic issues related to Von Neumann architectures.

In this brief workshop we will go through the basic elements of neurons biology and spiking networks, describe which algorithms can be implemented on this substrate and how big companies intend to use this knowledge to build next generation computers.

The workshop will be divided into three parts:

1. The dynamics of neurons, with a parallel to analogue electronics. We'll discuss together if we can implement one of this device analogically/digitally (because there are non linear variable conductances)

2. Describe the algorithm that can be implemented with this substrate and which are the pros and cons.

3. Which are the perspective of big companies in this regard and why these techs are important for large scale machine learning.