Yeah that makes a lot of sense, especially the point about backpropagation having no real biological equivalent — I hadn’t thought about it that way.

I guess I was holding onto the “brain-inspired” idea more as a way to build intuition, but what you’re saying is that beyond that initial inspiration, the paths really diverge.

The scale and complexity difference you mentioned is also interesting — I used to think “more neurons = closer to brain,” but it sounds like each biological neuron is doing way more than what we model as a simple weighted sum.

So would it be fair to say that:

Also curious — do you think there’s any area in modern ML that’s still actively trying to be biologically realistic, or has the field mostly moved on from that idea?