ArchiTECHt Daily: Amazon's broad ambitions are on display with Connect

I don't know the first thing about call centers, but I do know that the newly announced Amazon Connec
ARCHITECHT
ArchiTECHt Daily: Amazon's broad ambitions are on display with Connect
By ARCHITECHT • Issue #48
I don’t know the first thing about call centers, but I do know that the newly announced Amazon Connect platform could be a very big deal. Nearly every company—and every large enterprise—has a call center, and nearly every company is probably considering moving to the cloud. If I’m reading between the lines correctly on all the talk about using AI to automate call centers, a lot of companies consider them to be cost centers, as well. 
With Connect, Amazon is offering those companies the chance to kill two birds with one stone. They can automate their call centers (without going full robo-representative) and offload an expensive, if not mission-critical, process to the cloud. Better yet, Amazon claims Connect is simple enough for businesspeople to set up, which is critical to driving the type of bottom-up adoption that made AWS so successful.
Oh, and speaking of AWS, Amazon gets to reap the rewards as Connect customers gobble up all those AWS resources on the backend. 
When you start looking at Amazon’s string of non-compute services as a whole—Connect, Chime, WorkSpaces, WorkMail and more—you see a cloud provider that really wants to evolve into a full-on business platform. A lot of people are rightfully high on Microsoft Azure right now, but Amazon is somewhat sneakily trying to usurp Microsoft’s business-friendly reputation. Directly competing with Microsoft (and Google) on things like email might just be a check in a box, but coming from the side with services like Connect could prove an effective, and sticky, strategy.
On a somewhat-related note, Google has released the internal documentation it uses for starting and managing open source projects. Earlier this month, I complained about the first day of Google’s cloud conference being too enterprise-y without really distinguishing Google from the competition. On the third day, I think it nailed a big part of its message, which is essentially Google is the open cloud. Sharing its OSS protocol is another good step toward making that message stick.
Finally, watch the video explanation (below) of a robotics and machine learning paper, performed by the robots themselves rapping about the study’s methods. You might learn something, and if you’re nerdy enough you’ll certainly smile. Just click on the image to watch on YouTube.

Robot's Delight
Around the web: China's huge growth
Yesterday, I shared some concern over China’s ambitions in quantum computing and supercomputing. Now, it’s semiconductors that some folks in the U.S. nervous.
This is a smart thing to do, IMHO. Targeting big-money industries with custom tooling, even if not applications, will only bring them on board faster. 
There has been a fair amount of hyperbole about AI coming from Chinese companies and government voices. Too-high expectations paired with too much money would suggest problems if it’s true.
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Around the web: Artificial intelligence
Rigetti Computing is doing some interesting things with cloud computing and APIs for quantum computing. Experimental today, but obviously it has grander goals, and a great set of investors.
As usual, if you’re looking for a great explanation on the state of affairs in AI, especially deep learning, Geoff Hinton of Google/University of Toronto is a great person to ask.
Training machines to be perfect in real-world settings is very difficult, in large part because there’s not always enough good data. So when is a driverless car “good enough” to hit the streets?
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Any time you’re listing 100 of something, you’re bound to go a little too broad at times. But this is useful nonetheless.
An insightful take into research that helps AI systems learn like children, in part by doing things for their own sake rather than for a “reward.”
Sponsor: Marshal.io
Around the web: All things data
According to Dice, jobs requiring skills in HANA, MapReduce, Cassandra, HBase and Kafka offer some of the highest salaries of all software engineering jobs. 
This blog post from Hortonworks provides a decent overview on Ford’s data platform and use cases. This mirrors my experience with Ford being remarkably open about its big data strategy—which is a good thing.
The goal of DataSlicer is to make it easier for analysts to find the information they’re looking for. It’s just research, but the method and the results seem promising. 
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It seems like so many startups trying to “make data easy” have come and gone, but Flourish seems promising. I like its focus on straight-up visualization rather than data analysis.
Around the web: Cloud and infrastructure
In case you were wondering, Intel is still the 800-pound gorilla in microchips and it’s not letting up anytime soon. Here’s another good take, on Intel’s challenges, from Fortune.
I asked yesterday when OpenShift will start moving the needle at Red Hat. It looks like it is in terms of margins (20x RHEL) but it’s OpenStack that’s driving most cloud revenue at the moment.
Fair allocation of compute resources is already a thing, so why not for bandwidth? If it makes bloated websites load faster, I’m for it.
… if only because two-thirds of respondents were using Microsoft Azure, compared with 55 percent using AWS. It’s a small sample, but echoes a lot of recent sentiment.
Jess Frazelle drops some knowledge on why containers are inherently different than their predecessors. Very much worth reading.
Among other things. I would be curious to know how many users are demanding to run 5,000 nodes at this point, though.
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