philip lelyveld The world of entertainment technology

‘Super-Turing AI’ uses less energy by mimicking the human brain

PhilNote: this is a general audience article, but the research it reports on could be of interest.

... Dr. Suin Yi, assistant professor of electrical and computer engineering at Texas A&M's College of Engineering, is on a team of researchers that developed "Super-Turing AI," which operates more like the human brain. This new AI integrates certain processes instead of separating them and then migrating huge amounts of data like current systems do. ...

In the brain, the functions of learning and memory are not separated, they are integrated. ...

"Traditional AI models rely heavily on backpropagation—a method used to adjust neural networks during training," Yi said. "While effective, backpropagation is not biologically plausible and is computationally intensive.

"What we did in that paper is troubleshoot the biological implausibility present in prevailing machine learning algorithms," he said. "Our team explores mechanisms like Hebbian learning and spike-timing-dependent plasticity—processes that help neurons strengthen connections in a way that mimics how real brains learn."

Hebbian learning principles are often summarized as "cells that fire together, wire together." This approach aligns more closely with how neurons in the brain strengthen their connections based on activity patterns. By integrating such biologically inspired mechanisms, the team aims to develop AI systems that require less computational power without compromising performance. ...

Read the full story here: https://techxplore.com/news/2025-03-super-turing-ai-energy-mimicking.html