Dutch physicists have just taken the first steps towards making a “quantum brain” by building a material that stores and processes information in a similar way to the human brain.
In many ways, the incredible capabilities of the human brain make it more powerful than supercomputers. Scientists have long been trying to replicate its functions to apply to computing, creating artificial neural networks that are inspired by biological neural networks – using nodes that act like artificial neurons, transmitting signals through synapse-like connections.
But instead of just creating software to process information in a similar way to a brain, what if we built hardware that actually mimics neurons?
Researchers from Radboud University in the Netherlands have been working on this kind of hardware, called neuromorphic architecture. Specifically, they’ve been building an intelligent and dynamic material that can learn by physically adapting itself – so it has brain-like plasticity.
To do this, they first learned how to store information in single atoms: the ultimate in high-density information storage.
In 2017, this was achieved by a US-led team for the first time, and shortly after the Radboud team also showed that they could do so with a single cobalt atom. By applying a voltage to the atom, they caused it to randomly shift between values of 0 and 1, mimicking a neuron “firing”.
Now their new study, published in the journal Nature Nanotechnology, describes how they constructed a network of these cobalt atoms on black phosphorous. They were able to pattern and connect the atoms, including mimicking the autonomous behaviour of neurons and synapses.
These ensembles of atoms were even observed to have an inherent adaptive property – the synapses changed behaviour based on their surroundings.
“When stimulating the material over a longer period of time with a certain voltage, we were very surprised to see that the synapses actually changed,” says lead scientist Alexander Khajetoorians. “The material adapted its reaction based on the external stimuli that it received. It learned by itself.”
This could lead to a much more energy-efficient way to store and process information. The growing global demand for computing capacity has a planetary cost: as data centres multiply, so too does their energy footprint.
“It is clear that we have to find new strategies to store and process information in an energy-efficient way,” says Khajetoorians.
“This requires not only improvements to technology, but also fundamental research in game-changing approaches. Our new idea of building a ‘quantum brain’ based on the quantum properties of materials could be the basis for a future solution for applications in artificial intelligence.”
Next, the Radboud team will scale the system up even further – and attempt to understand why the system actually displays these interesting behaviours.
“If we could eventually construct a real machine from this material, we would be able to build self-learning computing devices that are more energy-efficient and smaller than today’s computers,” says Khajetoorians. “Yet, only when we understand how it works – and that is still a mystery – will we be able to tune its behaviour and start developing it into a technology.”
Lauren Fuge is a science journalist at The Royal Institution of Australia.
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