A neuromorphic supercomputer called DeepSouth will be capable of 228 trillion synaptic operations per second, which is on par with the estimated number of operations in the human brain
Edit: updated link, no paywall
A better title would be “Supercomputer that could conceivably simulate entire human brain, based on a rough estimate of what it would take to do that if we had any idea how to do that, will switch on in 2024”.
For real. I’m reading the title all wondering how the fuck they mapped all the neuron connections and… nope, the real innovative part of the story is clickbait
That’s only counting connections. The brain learns by making new connections, through complex location and timing dependent inputs from other neurons. It’s way more complex than the number of connections, and if neuroscientists are still studying the building blocks we don’t have much hope of recreating it.
This also ignores that the brain is not wholly an electrical system. The are all kinds of chemical receptors within the brain that alter all kinds of neurological function. Kid of the reason why drugs are a thing. On small scales we have a pretty good idea how these work, at least for the receptors that we’re aware of. On larger scales it’s mostly guessing at this point. The brain has a knack of doing more than the sum of all parts on a pretty regular basis.
Why post an article link behind a paywall?
Why whine about paywalls instead of learning how to remove them?
A neuromorphic supercomputer called DeepSouth will be capable of 228 trillion synaptic operations per second, which is on par with the estimated number of operations in the human brain
By James Woodford
12 December 2023
An artist’s impression of the DeepSouth supercomputer
A supercomputer capable of simulating, at full scale, the synapses of a human brain is set to boot up in Australia next year, in the hopes of understanding how our brains process massive amounts of information while consuming relatively little power.
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The machine, known as DeepSouth, is being built by the International Centre for Neuromorphic Systems (ICNS) in Sydney, Australia, in partnership with two of the world’s biggest computer technology manufacturers, Intel and Dell. Unlike an ordinary computer, its hardware chips are designed to implement spiking neural networks, which model the way synapses process information in the brain.
Such neuromorphic computers, as they are known, have been built before, but DeepSouth will be the largest yet, capable of 228 trillion synaptic operations per second, which is on par with the estimated number of synaptic operations in a human brain.
“For the first time we will be able to simulate the activity of a spiking neural network the size of the human brain in real time,” says Andre van Schaik at ICNS, who is leading the project. While DeepSouth won’t be more powerful than existing supercomputers, it will help advance our understanding of neuromorphic computing and biological brains, he says. “We need this ability to better learn how brains work and how they do what they do so well.”
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Existing supercomputers are becoming one of the biggest consumers of energy on the planet, whereas a human brain uses barely more power than a light bulb. At least part of this difference is down to differing ways of processing data – traditional computers process information in fast sequence, constantly moving data between the processor and the memory, while a neuromorphic architecture performs many operations in parallel with significantly reduced movement of data. As the movement of data is one of the most power-hungry parts of the computation, the neuromorphic approach offers significant power savings.
In addition, spiking neural networks are event-driven, meaning the neuromorphic system responds to changes in input rather than continuous running in the background like a traditional computer, resulting in further power savings.
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As well as potentially helping to build new types of computers, Ralph Etienne-Cummings at Johns Hopkins University, Baltimore, who is not involved in the work, says DeepSouth will advance the study of neuroscience more quickly as he and other researchers will be able to repeatedly test models of the brain.
“If you are trying to understand the brain this will be the hardware to do it on,” he says. “At the end of the day there’s two types of researchers who will be interested in this – either those studying neuroscience or those who want to prototype new engineering solutions in the AI space.”
DeepSouth could pave the way for much higher energy efficiency in computing, says Etienne-Cummings, and if the technology can be miniaturised it will help make drones and robots more autonomous.
Skeptical. As of August 2023, there are scientists still struggling with simulating C. Elegans- a single celled organism.
Another artificial idiot for the pile.
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