Can Russia's 'giant' supercomputer predict war?
Russia possesses a “giant” supercomputer capable of predicting wars, Russian Defense Minister Sergei Shoigu revealed.
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A nuclear bomb test in the 1950s. |
“The powerful supercomputer is located at the military command center, helping the Russian armed forces prepare for threats,” RT quoted Russian Defense Minister Sergey Shoigu.
The supercomputer is a key component of Russia's IT infrastructure, so powerful that the military only uses half of its capacity, Shoigu told Rossiya 24 channel.
The channel is currently filming a documentary about the Russian National Defense Coordination Center (NDMC).
Mr. Shoigu emphasized that the supercomputer is an open structure, Russian experts can add components, helping to expand its operating capacity if necessary.
The supercomputer will rely on analysis from all wars and conflicts that took place in the past to predict what will happen in the future, Mr. Shoigu explained.
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Russian Defense Minister Sergey Shoigu. |
“For example, the Yugoslav war. This was a major NATO operation. All signs of naval mobilization, missiles, strategic positions were analyzed by supercomputers,” Shoigu said. “If the supercomputer announces the results of the current situation, or an event that is 90% similar to the past, then we know that war is imminent and take appropriate countermeasures.”
This “giant” supercomputer has 236 petabytes of memory, equivalent to 236,000,000 gigabytes, according to Rossiya 24. Mr. Shoigu asserted that this memory is 19 times larger than the US military's computer system.
The supercomputer can analyze the amount of data equivalent to “50 Russian State Libraries”. This is the largest library in Russia, currently storing 17 million books.
The supercomputer is just one part of Russia's secretive digital defense center, which works around the clock to analyze intelligence data.
In September 2016, Russia announced that it was developing a supercomputer that could control an army of armed robots at sea, in the air or on land.
According to VNN
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