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Network World Data Center News Feed

The Network World Data Center news feed is updated most days, generally with less than five new stories. Some days there are no new stories. Frequently mixed with other network news feeds.

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Last 3 items

How AI can create self-driving data centers

Published on 10th August, 2020, 11:00 AM

Most of the buzz around artificial intelligence (AI) centers on autonomous vehicles, chatbots, digital-twin technology, robotics, and the use of AI-based 'smart' systems to extract business insight out of large data sets. But AI and machine learning (ML) will one day play an important role down among the server racks in the guts of the enterprise data center. 

AI's potential to boost data-center efficiency – and by extension improve the business – falls into four main categories:

To read this article in full, please click here

Microsoft uses AI to boost its reuse, recycling of server parts

Published on 7th August, 2020, 3:49 PM

Microsoft is bringing artificial intelligence to the task of sorting through millions of servers to determine what can be recycled and where.

The new initiative calls for the building of so-called Circular Centers at Microsoft data centers around the world, where AI algorithms will be used to sort through parts from decommissioned servers or other hardware and figure out which parts can be reused on the campus.

Microsoft says it has more than three million servers and related hardware in its data centers, and that a server's average lifespan is about five years. Plus, Microsoft is expanding globally, so its server numbers should increase.

To read this article in full, please click here

Federated learning improves how AI data is managed, thwarts data leakage

Published on 6th August, 2020, 8:29 PM

Privacy is one of the big holdups to a world of ubiquitous, seamless data-sharing for artificial intelligence-driven learning. In an ideal world, massive quantities of data, such as medical imaging scans, could be shared openly across the globe so that machine learning algorithms can gain experience from a broad range of data sets. The more data shared, the better the outcomes.

That generally doesn't happen now, including in the medical world, where privacy is paramount. For the most part, medical image scans, such as brain MRIs, stay at the institution level for analysis. The result is then shared, but not the original patient scan data.

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