A New Brain-Inspired Learning Method for AI Saves Memory and Energy | Artificial Intelligence - Singularity Hub

Edd Gent, freelance science and technology writer based in Bangalore observes, Despite the frequent analogies, today’s AI operates on very different principles to the human brain. 
 

Photo: Gerd Altmann from Pixabay

Now researchers have proposed a new learning method more closely tied to biology, which they think could help us approach the brain’s unrivaled efficiency.

Modern deep learning is at the very least biologically-inspired, encoding information in the strength of connections between large networks of individual computing units known as neurons. Probably the biggest difference, though, is the way these neurons communicate with each other. 

Artificial neural networks are organized into layers, with each neuron typically connected to every neuron in the next layer. Information passes between layers in a highly synchronized fashion as numbers falling in a range that determines the strength of the connection between pairs of neurons...

In a paper in Nature Communications, the Austrian team describes how they created artificial analogues of these two features to create a new learning paradigm they call e-prop. While the approach learns slower than backpropagation-based methods, it achieves comparable performance.

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Source: Singularity Hub