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Attendees at the event included Taiwan Mobile Chairman Daniel Tsai, Asus Chairman and Chief Jonney Shih , and Quanta Founder and CEO Barry Lam, all of whom participated in a swearing in ceremony for the joint establishment of the AI cloud platform. At the ceremony it was announced that Taiwan’s first self-developed and self-established AI cloud platform would be completed in December 2018.
MOST stated that the AI cloud platform is the most important link in the five major strategies of the “Small National AI Challenge,” the goal of which is to create a national AI R&D and cloud services environment. In the future the AI cloud platform will be equipped with a calculation efficiency of up to 7 PFLOPS and have a consolidated mainframe with up to 50 PB of storage capacity. Furthermore, through the integration of a one-stop portal, it will provide AI training, big data analysis, and and storage management services.
The basic configuration of the AI room is scheduled to be completed in August, and the hosting computer hardware is expected to be built in September. Following that, the software deployment is planned to be completed in October while the overall system testing is anticipated to be carried out in December. In addition to having the capacity to provide rapid calculations, large abundant storage space, and secure networks, the AI platform will be Taiwan’s largest big data and AI learning markets and provide more immediate and convenient computing services in the industry, academia and research communities.
In addition, as a collaborative cross-industry and cross-group AI platform, this project is the first one of its kind in Taiwan, and will be supervised by the National Center for High-Performance Computing (NCHC). Meanwhile, Taiwan Mobile will be responsible for the construction of the high-specification computer room and telecommunication-grade logistics, while Quanta will cover the AI computing and data storage platform and Asus will take care of the integrated cloud service platform, cloud server, and AI applications.
(TR/ Phil Sweeney)
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