How Machine Learning is Changing the Face of the Data Center 7wData

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Machine learning and artificial intelligence have arrived in the data center, changing the face of the hyperscale server farm as racks begin to fill with ASICs, GPUs, FPGAs and supercomputers. These technologies provide more computing horsepower to train machine learning systems, a process that involved enormous amounts of data-crunching. The end goal is to create smarter applications, and improve the services you already use every day. "Artificial intelligence is now powering things like your Facebook Newsfeed," said Jay Parikh, Global Head of Engineering and Infrastructure for Facebook. "It is helping us serve better ads.


How Machine Learning is Changing the Face of the Data Center

#artificialintelligence

Machine learning and artificial intelligence have arrived in the data center, changing the face of the hyperscale server farm as racks begin to fill with ASICs, GPUs, FPGAs and supercomputers. These technologies provide more computing horsepower to train machine learning systems, a process that involved enormous amounts of data-crunching. The end goal is to create smarter applications, and improve the services you already use every day. "Artificial intelligence is now powering things like your Facebook Newsfeed," said Jay Parikh, Global Head of Engineering and Infrastructure for Facebook. "It is helping us serve better ads.


Google Builds Custom Processors for Machine Learning

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When AlphaGo, Google's artificial intelligence program, defeated champion Go player Lee Sedol earlier this year, everyone praised its advanced software brain. But the program, developed by Google's DeepMind research team, also had some serious hardware brawn standing behind it. The program was running on custom accelerators that Google's hardware engineers had spent years building in secret, the company said. With the new accelerators plugged into AlphaGo's servers, the program could recognize patterns in its vast library of game data faster than it could with standard processors. The increased speed helped AlphaGo make the kind of quick, intuitive judgments that have escaped other computers trying to conquer the game.


AI And Machine Learning To Power The Alphabet (NASDAQ:GOOG) Cloud

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Alphabet Inc-A (NASDAQ:GOOGL) unveiled new cloud computing services that allow any developer or business to use the Machine Learning (ML) technologies that power the company's most powerful services, Wired reports. The recent, spectacular victory of Alphabet's AlphaGo program over top Go player Lee Sedol has been hailed as a major Artificial Intelligence (AI) breakthrough and indicates how AI is rapidly becoming a mature technology with a potential for world-changing applications. In fact, AI is becoming adept at more and more high-level cognitive tasks that used to be considered as too complex for automation. "The victory is notable because the technologies at the heart of AlphaGo are the future," noted Wired. "They're already changing Google and Facebook and Microsoft and Twitter, and they're poised to reinvent everything from robotics to scientific research."


Google Builds Custom Processors for Machine Learning

#artificialintelligence

When AlphaGo, Google's artificial intelligence program, defeated champion Go player Lee Sedol earlier this year, everyone praised its advanced software brain. But the program, developed by Google's DeepMind research team, also had some serious hardware brawn standing behind it. The program was running on custom accelerators that Google's hardware engineers had spent years building in secret, the company said. With the new accelerators plugged into the AlphaGo servers, the program could recognize patterns in its vast library of game data faster than it could with standard processors. The increased speed helped AlphaGo make the kind of quick, intuitive judgments that define how humans approach the game.