Do our brains use the same kind of deep-learning algorithms used in AI?

Deep-learning researchers have found that certain neurons in the brain have shape and electrical properties that appear to be well-suited for "deep learning" -- the kind of machine-intelligence used in beating humans at Go and Chess. Canadian Institute For Advanced Research (CIFAR) Fellow Blake Richards and his colleagues -- Jordan Guerguiev at the University of Toronto, Scarborough, and Timothy Lillicrap at Google DeepMind -- developed an algorithm that simulates how a deep-learning network could work in our brains. It represents a biologically realistic way by which real brains could do deep learning.* The finding is detailed in a study published December 5th in the open-access journal eLife. Seeing the trees and the forest "Most of these neurons are shaped like trees, with'roots' deep in the brain and'branches' close to the surface," says Richards.