Artificial brains could point the way to ultra-efficient supercomputers

New research from Sandia National Laboratories suggests that brain-inspired neuromorphic computers are just as adept at solving complex mathematical equations as they are at speeding up neural networks and could eventually pave the way to ultra-efficient supercomputers.

Running on around 20 watts, the human brain is able to process vast quantities of sensory information from our environment without interrupting consciousness. For decades, researchers have been trying to replicate these processes in silicon, in what is commonly referred to as neuromorphic computing. 

Sandia has been at the center of much of this research. The lab has deployed numerous neuromorphic systems from the likes of Intel, SpiNNaker, and IBM over the past several years.

Much of the research around these systems has focused on things like artificial intelligence and machine learning. But as it turns out, these brain-inspired chips are much more versatile. 

The brain is performing complex computations even if we ...