This is what I think is the next evolution of these models. Our brains are made up of many different types of neurones all interspersed with local regions made up of specific types. From my understanding most approaches to tensors don't integrate these different neuronal models at the node level; it's usually by feeding several disparate models data and combining an end result. Being able to reshape the underlying model and have varying tensor types that can migrate or have a lifetime seems exciting to me.