> There's a direct relationship between the algorithms human brains used to produce the training data and the algorithms being approximated by these models. Eh

> There's a direct relationship between the algorithms human brains used to produce the training data and the algorithms being approximated by these models. Eh. That deep learning networks is like the brain is like saying that cars are like cheetahs. Sure, they go really fast by converting some kind of fuel into kinetic energy, and they move by exerting force on the ground, but that's about it. Brains don't have ReLU units. Brains have lots of different types of topology, not just an uniform network, and can handle some of that topology arbitrarily being shut off due to damage. Brains use global chemical changes for (otherwise) out-of-band signaling purposes. Brains don't use gradient descent. Etc...