If we wanted to generalize this further, attention is 'just' an instance of graph convolution, encoder-only models like Bert are complete graphs, decoder-only models like GPT are still complete graphs but the information flow is not bi-directional as in Bert; instead a node provides information to all subsequent nodes only giving rise to the causal nature.

However, I don't think Hebbian learning will see a resurgence except maybe if it motivates some kind of pruning mechanism.

I think that Sutton was right in 'The bitter lesson', the problem seems to be that we are hitting the limits of what we can do with our compute.