Competitive learning, a form of Hebbian learning, has been around since the 80s. It’s been some time I’ve not followed Numenta’s work, but, from my understanding, the way the spatial pooler and the temporal memory learn is quite similar to e.g. self-organising maps (which learn in a competitive way).
I’m interested in a comparison between competitive learning and the way the SP and TM learn. What are the differences and similarities? They both learn in an unsupervised way, but I am interested in more details. (I will eventually answer to this question, if nobody is able to do it, but only once I have some more time.)