U of T neuroscientist on how advances in AI may help us better understand why neurons are shaped the way they are

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The shape of our neurons may indicate our brains actually employ a type of learning, dubbed “deep learning,” that was developed to drive artificial intelligence, or AI, applications, a University of Toronto researcher has found.

The shape of our neurons may indicate our brains actually employ a type of learning, dubbed “deep learning,” that was developed to drive artificial intelligence, or AI, applications, a University of Toronto researcher has found.

While AI has made major leaps in recent years thanks to a technique that attempts to mimic our brain with a simulated, layered network of neurons, the approach contradicts a number of known biological facts about the brain. For one, deep learning in AI uses knowledge of all the network connections when learning, while our own brains can only use whatever information is available to an individual cell.

The neurons in our brain are also complex: Most in the neocortex, for example, are shaped like trees with “roots” deep in the brain and “branches” close to the surface. By comparison, the simulated neurons used in AI are very simple with no shape, just a single point in space.

As a result, many neuroscientists are skeptical that our brains really use deep learning.

Read more at University of Toronto