How are the languages of the world related? This is the central question in the discipline of historical linguistics. In his MSc thesis, Peter Dekker studied how neural networks can help to reconstruct the ancestry of languages.

In this post, we go through the main building blocks of transformers and capsule networks and try to draw a connection between different components of these two models. Our main goal here is to understand if these models are inherently different and if not, how they relate.

As we saw in the previous post, we can decode someone’s visual experience from their brain activity using machine learning with increasing accuracy. This is pretty impressive already, however this is not quite what we understand as mind reading, is it? So let’s go a step further!

Ever since we started investigating the brain, neuroscientists have dreamed about reading the human mind. Will we ever be able to look into the brain and tell what someone is thinking? How would this even work?