New discovery opens the way for brain-like computers

Date:
November 29, 2021
Source:
University of Gothenburg
Summary:
Research has long strived to develop computers to work as
energy efficiently as our brains. A study has now succeeded 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.



FULL STORY ========================================================================== 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.


==========================================================================
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 AAkerman, professor of applied spintronics at
the University of Gothenburg.

Important breakthrough Working with a research team at Tohoko University, AAkerman 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.

AAkerman 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 AAkerman, 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." About the research field
Neuromorphic computing is an AI-related field attempting to imitate the
brain's neural networks. The research uses new algorithmic approaches
that resemble how the human brain integrates with the surrounding world
to deliver capacity approaching human cognition.

========================================================================== Story Source: Materials provided by University_of_Gothenburg. Original
written by Ulrika Ernstro"m. Note: Content may be edited for style
and length.


========================================================================== Journal Reference:
1. Mohammad Zahedinejad, Himanshu Fulara, Roman Khymyn, Afshin
Houshang,
Mykola Dvornik, Shunsuke Fukami, Shun Kanai, Hideo Ohno, Johan
AAkerman.

Memristive control of mutual spin Hall nano-oscillator
synchronization for neuromorphic computing. Nature Materials,
2021; DOI: 10.1038/s41563- 021-01153-6 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/11/211129122758.htm

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