Research has long strived to develop computers to work as energy efficiently as our brains. A study, led by researchers at the University of Gothenburg, has succeeded for the first time in combining a memory function with a calculation function in the same component. The discovery opens the way for more efficient technologies, everything from mobile phones to self-driving cars.
From: The Faculty of Science
November 29, 2021 -- In recent years,
computers have been able to tackle advanced cognitive tasks, like language and
image recognition or displaying superhuman chess skills, thanks in large part
to artificial intelligence (AI). At the same time, the human brain is still
unmatched in its ability to perform tasks effectively and energy efficiently.
“Finding new ways of performing
calculations that resemble the brain’s energy-efficient processes has been a
major goal of research for decades. Cognitive tasks, like image and voice
recognition, require significant computer power, and mobile applications, in
particular, like mobile phones, drones and satellites, require energy efficient
solutions,” says Johan Åkerman, professor of applied spintronics at the
University of Gothenburg.
Important breakthrough
Working with a research team at Tohoko
University, Åkerman led a study that has now taken an important step forward in
achieving this goal. In the study, now published in the highly ranked journal
Nature Materials, the researchers succeeded for the first time in linking the
two main tools for advanced calculations: oscillator networks and memristors.
Åkerman describes oscillators as
oscillating circuits that can perform calculations and that are comparable to
human nerve cells. Memristors are programable resistors that can also perform
calculations and that have integrated memory. This makes them comparable to
memory cells. Integrating the two is a major advancement by the researchers.
“This is an important breakthrough
because we show that it is possible to combine a memory function with a
calculating function in the same component. These components work more like the
brain’s energy-efficient neural networks, allowing them to become important
building blocks in future, more brain-like computers.”
Enables energy-efficient technologies
According to Johan Åkerman, the
discovery will enable faster, easier to use and less energy consuming
technologies in many areas. He feels that it is a huge advantage that the
research team has successfully produced the components in an extremely small
footprint: hundreds of components fit into an area equivalent to a single
bacterium. This can be of particular importance in smaller applications like
mobile phones.
“More energy-efficient calculations
could lead to new functionality in mobile phones. An example is digital
assistants like Siri or Google. Today, all processing is done by servers since
the calculations require too much energy for the small size of a phone. If the
calculations could instead be performed locally, on the actual phone, they
could be done faster and easier without a need to connect to servers.”
He notes self-driving cars and drones as
other examples of where more energy-efficient calculations could drive
developments.
“The more energy-efficiently that
cognitive calculations can be performed, the more applications become possible.
That’s why our study really has the potential to advance the field.”
Text: Ulrika Ernström
https://www.gu.se/en/news/new-discovery-opens-the-way-for-brain-like-computers
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