3 things to read today: From Rackspace's MSP acquisition to human-robot interaction at Amazon

On a relatively slow news day (if your beat doesn't involve covering iPhones), here are three stories
ARCHITECHT
3 things to read today: From Rackspace's MSP acquisition to human-robot interaction at Amazon
By ARCHITECHT • Issue #136 • View online
On a relatively slow news day (if your beat doesn’t involve covering iPhones), here are three stories you don’t want to miss:
Rackspace announces agreement to acquire Datapipe (Rackspace): Hey, if you’re going to quit the cloud business to focus on managed services, you might as well become one of the biggest MSPs around. Rackspace is definitely the bigger party here in terms of revenue, but Datapipe does bring some pretty strategic assets to the table. Rackspace and Datapipe both have pretty strong offerings lined up around the Big 3 public clouds, although Datapipe offers managed services for Alibaba Cloud, as well as traditional colocation services and 29 additional data center locations, including in mainland China, Russia and Brazil. Managed services aside, I also think Rackspace has its eyes set on owning the private part of hybrid cloud deployments.
As Amazon pushes forward with robots, workers find new roles (New York Times): I don’t know if it’s just wishful thinking, but this story follows in a line of research and analysis lately suggesting that there’s little evidence robots will actually take too many human jobs. In this case, as Amazon has increased the number of robots in its warehouses, humans have transitioned to new jobs (and arguably better ones), but haven’t lost jobs. It’s ironic to here this coming out of Amazon, because people also used to believe its cloud computing division would kill all sysadmin and ops jobs, but that clearly did not happen. What not entirely clear, though, is how these robots affect the hordes of Amazon seasonal contract workers we used to hear so much about.
How neural networks think (MIT News): This is more cool research into figuring out why models make the decisions they make—in this case by analyzing the effects of different inputs on a model’s outputs. One particularly interesting insight here is about just how important it is to pair large datasets with large-enough models. Run an underpowered model, and you end up with a dialogue system that automatically answers “I don’t know” whenever it sees a question beginning with “Who” or “What.”

Sponsor: Bonsai
Sponsor: Bonsai
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Sponsor: DigitalOcean
Sponsor: DigitalOcean
Cloud and infrastructure
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ARCHITECHT delivers the most interesting news and information about the business impacts of cloud computing, artificial intelligence, and other trends reshaping enterprise IT. Curated by Derrick Harris.

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