@examachine Though, we can be pretty confident that single neural networks are capable of achieving equivalent functions for individual discovered tiny regions because tiny regions, such as layers of the visual neocortex, have very simple jobs. For example, it takes two of them to process nothing more than edge detection.
There aren’t 300 large brain regions; only less than 300 tiny discovered ones, so I find it hard to not think that, at maximum, 1000 neural networks wouldn’t be enough. I think there would have to be a convenient jeopardising factor to make me wrong about this.
There’s also the fact that the brain uses equivalent to, at most, about 10 ^ 15 FLOPS and it seems very unlikely that the brain is as effcient as neural networks (which use backpropagation), so it’s quite a stretch that it would take more processing power than that to achieve human-level intelligence; with neural networks, at least.
Maybe DLs don’t take up many FLOPS or are very ineffcient. I don’t know that much about DLs.
I’ll read your paper. It sounds interesting.
Thank you for the conversations. I’ve enjoyed them. I hope you have, too.