A new computing approach could revolutionize the growing field of Artificial Intelligence by creating machines capable of thinking for themselves all while consuming less energy to boot.
As Inverse puts it:
“Computers have come a long way since Alan Turing postulated their limitations in his now-famous 1950 paper “Computing Machinery and Intelligence.”
They may not be falling in love (though, having someone fall in love with them is up for debate), or enjoying a bowl of strawberries and fresh cream, but the limitations of these machines are slowly crumbling. In the age of machine learning, another one has bitten the dust: The ability to learn from experience.
Typically, this kind of intelligence is achieved through a leap-frog-like system of multiple computers and machine-learning algorithms, but in a new paper published Monday in the journal Nature Nanotechnology, a team of physicists propose a different method. They designed a computer capable of embedding basic intelligence into its hardware — by taking advantage of atoms’ quantum spins.
WHY IT MATTERS — This so-called ‘quantum brain’ is an example of neuromorphic computing — computing systems designed to mimic the biological structures of the brain. Ultimately, this technology could enable robots embedded with a tiny piece of computing hardware in their ‘brains’ to make decisions on their own.
THE BIG IDEA — Googling your favorite restaurant’s hours may seem like an energy-free computation, but in the grand scheme these calculations add up to a substantial carbon footprint— and the magnitude of these computations is only growing.
Alexander Khajetoorians is first author of this new study and professor of scanning probe microscopy at Radboud University. He explains in a statement that, to meet computation’s growing requirements and lower its energy-footprint, scientists need to seriously rethink how machines store and process information.
‘This requires not only improvements to technology, but also fundamental research in game changing approaches,’ Khajetoorians says.
To tackle this, Khajetoorians and colleagues follow a streamlined approach to essentially embed a software “brain” into physical hardware instead.
‘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,’ Khajetoorians explains.'”
This new approach sounds both scary and exciting. On the one hand if machines really can think for themselves we may not like what they decide. But on the other hand we could stand to benefit tremendously from their insights. Time will tell how this plays out but I for one think that Quantum Brains are definitely worth pursuing despite the inherent risks involved.
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