The brain is considered an autonomous learning system. It can detect patterns and acquire new knowledge without external guidance. Until recently, this was not the case for AI — any data being fed to machine learning systems needed to be tagged first.
Some presumed that no such mechanism existed in biological neural networks. However, based on a combination of considerations from the current practice of A and computational neuroscience researchers came to a different conclusion.
In a recent scientific publication, the authors show that self-supervision and error backpropagation co-exists in the brain, and with a very specific area of the brain involved: the hippocampus.