Scientists have created a new type of nanoelectronic device that could significantly reduce how much energy artificial intelligence systems consume. The innovation works by copying how the human brain processes information, offering a more efficient alternative to today's power-hungry AI hardware.

The research team, led by the University of Cambridge, developed a modified version of hafnium oxide that functions as a highly stable, low-energy 'memristor' -- a component designed to replicate how neurons connect and communicate in the brain. Their findings were published in the journal Science Advances .

Why Current AI Systems Use So Much Energy

Modern AI relies on traditional computer chips that constantly move data between memory and processing units. This back-and-forth transfer requires large amounts of electricity, and demand continues to rise as AI becomes more widely used across industries.

Neuromorphic computing offers a different approach.…