Hopfield networks have been introduced to me multiple times as a "biologically plausible" (at least relatively speaking) neural network architecture. My read on this is that they are not necessarily useful for machine learning so much as they are a curiosity because they seem to simulate the brain. Do I have the right idea here, or are Hopfield networks actually the best option for some tasks?
I'm aware that Hopfield networks have some properties which can be important - like recurrence. I'm not asking about that, just these specific networks.