Scientists from Western Sydney University are preparing to boot up the world’s first-ever supercomputer that simulates the design and phenomenal power of a human brain.
The technology could cast off bottlenecks that restrain traditional computers – including their enormous energy demands – and supercharge artificial intelligence, potentially giving rise to new forms of AI that aren’t algorithms but rather physical, genuinely intelligent decision-making devices.
An artist’s impression of the DeepSouth supercomputer, capable of replicating the power of a human brain.Credit: Western Sydney University
“This is not the biggest number-crunching supercomputer. But what’s special about this one is that it’s really geared towards simulating how our neural system and brains compute,” Professor Andre van Schaik, director of the university’s International Centre for Neuromorphic Systems, said.
The firing up of the computer, called DeepSouth, in April 2024 near Penrith, will represent a major global milestone in neuromorphic computing, which refers to technology based on the architecture of the brain. It can be thought of as biology’s answer to quantum computing.
Our brains can perform an exaflop (a billion squared) calculations in a second with only 20 watts – less power than a lightbulb. That’s an estimated million times more efficient than the computers we build, which are kneecapped because data must be shuttled between devices’ memory and processors, slamming the brakes on power and speed.
International Centre for Neuromorphic Systems Director, Professor André van Schaik, is leading the DeepSouth project, which will accelerate research into brain disease and smarter versions of AI.Credit: Western Sydney University
Neuromorphic computing skirts this problem by replicating the ability of neurons and synapses to bring processing and memory together.
Van Schaik said it took millions of dollars worth of energy to train AI models such as ChatGPT, which still make “stupid mistakes”.
“We have really good AI at the moment with the large language models that’re really capturing people’s imaginations and fears. But they don’t compute at all like a brain,” van Schaik said. “They’re more number crunching machines and they are very energy hungry. Once we understand how brains do what they do so efficiently, that will lead to different forms of AI and smarter systems.”