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Microsoft details how Azure cloud will soon predict the future


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Microsoft details how Azure cloud will soon predict the future

Businesses looking to predict the future will no longer have to seek out the advice of fortune tellers now that Microsoft is about to merge enterprise-grade cloud services with machines capable of peering into a virtual crystal ball.

The Official Microsoft Blog today detailed how Redmond's managed cloud Windows Azure services will soon become even smarter thanks to the addition of "machine learning," an increasingly popular trend which allows the accurate prediction of future behavior and trends.

That's a fancy way of saying machines will soon be able predict the future, essentially what Microsoft Corporate Vice President of Machine Learning Joseph Sirosh and his team plan to offer enterprise customers starting in July.

Dubbed Azure Machine Learning (ML), the service will couple Microsoft's existing cloud benefits with "a comprehensive machine learning service" capable of cutting forecast times for customers and partners from weeks or even months to mere hours.

Criswell predicts?

An early preview of Azure ML is already in use with partners MAX451, who are using the e-commerce and brick-and-mortar sales data of a large, unnamed retail customer to predict which products customers are likely to purchase next.

Initially available as a public preview next month, Azure ML is touted as the culmination of powerful technology algorithms first developed for Bing and Xbox, with new analytics tools and machine learning added to the mix.

Microsoft claims the service will virtually eliminate traditional startup costs associated with machine learning authoring, development and scaling, at the same time making it as easy to use (and presumably cheap) as current Azure cloud services.

To educate Azure ML customers on how Microsoft plans to implement such technology, Sirosh and his colleagues have launched a dedicated Machine Learning blog, which promises to "create entirely new solutions that bring together big data insights, the Internet of things and predictive analytics."

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