Research has lengthy strived to develop computers to work as vitality effectively as our brains. A research, led by researchers at the University of Gothenburg, has succeeded for the first time in combining a reminiscence perform with a calculation perform in the identical element. The discovery opens the way for extra environment friendly applied sciences, the whole lot from cellphones to self-driving automobiles.
In latest years, computers have been in a position to deal with superior cognitive duties, like language and picture recognition or displaying superhuman chess expertise, thanks largely to synthetic intelligence (AI). At the identical time, the human mind remains to be unmatched in its potential to carry out duties successfully and vitality effectively.
“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 utilized spintronics at the University of Gothenburg.
Working with a analysis staff at Tohoko University, Åkerman led a research that has now taken an necessary step ahead in reaching this objective. In the research, now revealed in the journal Nature Materials, the researchers succeeded for the first time in linking the two major instruments for superior calculations: oscillator networks and memristors.
Åkerman describes oscillators as oscillating circuits that may carry out calculations and which can be akin to human nerve cells. Memristors are programable resistors that may additionally carry out calculations and which have built-in reminiscence. This makes them akin to reminiscence cells. Integrating the two is a significant development 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 applied sciences
According to Johan Åkerman, the discovery will allow sooner, simpler to make use of and fewer vitality consuming applied sciences in lots of areas. He feels that it’s a big benefit that the analysis staff has efficiently produced the elements in a particularly small footprint: a whole lot of elements match into an space equal to a single bacterium. This will be of explicit significance in smaller functions like cellphones.
“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 automobiles and drones as different examples of the place extra energy-efficient calculations might 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.”
Johan Åkerman, Memristive management of mutual spin Hall nano-oscillator synchronization for neuromorphic computing, Nature Materials (2021). DOI: 10.1038/s41563-021-01153-6. www.nature.com/articles/s41563-021-01153-6
University of Gothenburg
New discovery opens the way for brain-like computers (2021, November 29)
retrieved 29 November 2021
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