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Facebook, Microsoft target faster services with new A. I. server designs

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Facebook on Wednesday rolled out some staggering statistics related to its social networks. Each day, users watch 100 million hours of video, 400 million people use Messenger and more than 95 million photos and videos are posted on Instagram.
Facebook on Wednesday rolled out some staggering statistics related to its social networks. Each day, users watch 100 million hours of video, 400 million people use Messenger, and more than 95 million photos and videos are posted on Instagram.
That puts a heavy load on Facebook’s servers in data centers, which help orchestrate all these services to ensure timely responses. In addition, Facebook’s servers use machine learning technologies to improve services, with one visible example being image recognition.
The story is similar for Microsoft, which is continually looking to balance the load on its servers. For example, Microsoft’s data centers apply machine learning for natural language services like Cortana.
Both companies introduced new open-source hardware designs to ensure faster responses to such artificial intelligence services, and the designs will allow the companies to offer more services via their networks and software. The server designs were introduced at the Open Compute Project (OCP) U. S. Summit on Wednesday.
These server designs can be used by other companies as a reference to design their own servers in-house and then send for mass manufacturing in Asia, something Facebook and Google have been doing for years. Financial organizations have also been experimenting with OCP designs to make servers for their organizations.
Facebook’s Big Basin is an unorthodox server box that the company has termed “JBOG” — for Just a Bunch Of GPUs — that can deliver unprecedented power for machine learning. The system does not have a CPU and operates as an independent box that needs to be connected to discrete server and storage boxes.
Big Basin delivers on the promise of decoupling processing, storage, and networking units in data centers. In independent pools, storage and processing can be scaled up much faster but are limited when stuffed in one server box like today.

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