Replicating the brain’s capabilities, an impossible task, may theoretically require thousands of H100, one of NVIDIA’s most powerful GPUs. At 700 watts per chip, we are looking at power consumption in the megawatt range. The brain runs on 20 watts. Scientists have taken inspiration from this remarkable organ to create chips that could cut conventional energy use by 70%.

Researchers at the University of Cambridge have developed a new brain-inspired nanoscale device that they say could dramatically reduce the enormous energy demands of artificial intelligence hardware. The team created an ultra-low-power “memristor”: a device that can both store and process information in the same location, much like synapses in the human brain.

In conventional computing architectures, memory and processing units are physically separated, requiring data to shuttle back and forth between these units for every task. This seemingly simple process consumes enormous amounts of electricity and is a significant contributor to AI’s exploding power demands.