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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.


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.


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.


Google Has Built Its Own Custom Chip for AI Servers Data Center Knowledge

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Last October, a computer system beat a professional human player at the ancient Chinese board game Go. The AI system, AlphaGo, was built by Google and trained using machine learning techniques. Google built the hardware that powered AlphaGo in-house, as it does with most of its infrastructure components. At the core of that hardware is the Tensor Processing Unit, or TPU, a chip Google designed specifically for its AI hardware, the company's CEO, Sundar Pichai, said from stage this morning during the opening Google I/O conference keynote next to Google headquarters in Mountain View, California. This is the first time Google has shared any information about the hardware backend that powers its AI, which will play a central role in the company's revamped cloud services strategy, announced earlier this year.


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.