Tech giant IBM has unveiled a prototype chip that mimics the human brain, aiming to enhance the energy efficiency of AI systems. The company’s recent announcement comes amid growing concerns over the carbon footprint of vast data centers that power advanced AI. 

According to IBM, the new model could revolutionize the world of smart devices by introducing more power-efficient AI chips, significantly reducing battery consumption in everyday gadgets such as smartphones.

A major factor contributing to the chip’s efficiency is its components that operate similar to human brain connections.  

In a report by the BBC, Thanos Vasilopoulos, a scientist at IBM’s Zurich research lab, stated that the human brain could achieve remarkable performance while consuming little power. 

He stated that this superior energy efficiency allows large and more complex workloads to be executed in low-power or battery-contained environments, mentioning cars, mobile phones and cameras as examples. Cloud providers can use these chips to reduce energy costs and carbon footprint. 

Unlike traditional chips, the new chips use components called memristors (memory resistors) that are analogue and can store a range of numbers. The difference between digital analogues is like the difference between a light switch and a dimmer switch. 

The human brain is an analogy, and the way memristors work is similar to the way synapses in the brain works. 

According to Prof Ferrante Neri, University of Surrey, memristors fall into the realm of what you might call nature-inspired computing that mimics brain function. They could remember this electric history in a similar way to synapses in a biological system. Memristors which are interconnected can form a network resembling a biological brain. 

He also warned that developing a memristor-based computer is not a simple task and that there would be several challenges ahead for widespread adoption, including the costs of materials and manufacturing difficulties. 

IBM hopes that, in the future, chips in phones and cars could be more efficient, promising longer battery life and new applications.