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IBM creates artificial neurons from phase change memory for cognitive computing

Lucas Mearian | Aug. 4, 2016
The artificial neurons can sustain billions of switching cycles, which means multiple years of operation

Exploiting this integrate-and-fire property, even a single neuron can be used to detect patterns and discover correlations in real-time streams of event-based data, the researchers said.

Phase change memory IBM research
IBM Research

The ability to analyze massive volumes of data in a split second

For example, in the Internet of Things, sensors can collect and analyze volumes of weather data collected at the edge for faster forecasts. The artificial neurons could also detect patterns in financial transactions to find discrepancies or use data from social media to discover new cultural trends in real time. Large populations of these high-speed, low-energy nano-scale neurons could also be used in neuromorphic coprocessors with co-located memory and processing units.

What also makes IBM's artificial neurons special is they can achieve a level of self-learning and could be used for power-hungry applications such as data analytics, which could detect random patterns in social networks such as Twitter or a stock market.

For example, if one stock is traded on an exchange, it could have an effect on others in ways not easily discernible.

Eleftheriou used "the diapers and beer" predictive analytics urban legend to explain how machine learning enabled by artificial neurons would work. The legend contends that a study performed by a grocery store found a correlation between men who bought diapers and beer sales. While not readily apparent, the study found men buying diapers felt compelled to balance their nurturing, feminine side with a manly beer purchase.

The study's findings, the legend contends, prompted the grocery store to move the beer closer to the diapers, which resulted in a 35% increase in sales of both. Other grocery stores followed suit.

"Using the artificial neurons, you can also find correlations between two stocks, which you and I may think, 'How are these two stocks connected?'" Eleftheriou said. "We don't know why it's happening, but the data says it is happening and the synapses can show that correlation."

 

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