I’ve read this paper about how columns learn the structure of the world and there is a thing that I don’t understand:
The output layer’s activation is fixed while it is getting different feature-location signals. Also the layer can represent union of possible objects and over time it finds the right object. So the activation of the output layer does change. So how can these things happen at the same time?
Thank you for your help!
A post was merged into an existing topic: Why Does the Neocortex Have Layers and Columns, A Theory of Learning the 3D Structure of the World