Science & technology | Backprop in the brain

AI scientists are producing new theories of how the brain learns

The challenge for neuroscientists is how to test them

A brain on a circle mirror. In the reflection is a colourful digital brain with learning nodes
Illustration: Daniel Liévano

Five DECADES of research into artificial neural networks have earned Geoffrey Hinton the moniker of the Godfather of artificial intelligence (AI). Work by his group at the University of Toronto laid the foundations for today’s headline-grabbing AI models, including ChatGPT and LaMDA. These can write coherent (if uninspiring) prose, diagnose illnesses from medical scans and navigate self-driving cars. But for Dr Hinton, creating better models was never the end goal. His hope was that by developing artificial neural networks that could learn to solve complex problems, light might be shed on how the brain’s neural networks do the same.

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This article appeared in the Science & technology section of the print edition under the headline “Great minds”

From the August 17th 2024 edition

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