ArchiTECHt Daily: At the nexus of cloud, wearables and AI

Four years ago, most of the world (even in Silicon Valley) hadn't heard of deep learning and had no i
ArchiTECHt Daily: At the nexus of cloud, wearables and AI
By ARCHITECHT • Issue #15
Four years ago, most of the world (even in Silicon Valley) hadn’t heard of deep learning and had no idea the artificial intelligence revolution it would come to drive. Today, it’s powering a not-significant percentage of our consumer experiences and might even be a savior for the wearable market. 
At least, that’s my takeaway after reading yesterday about the AI (specifically, natural language processing) capabilities Google has built into Android Wear 2.0. It’s not even that I think smartwatches and “smart messaging” are particularly exciting (like a true curmudgeon, I still prefer analog watches and manually typed text messages), but the direction in which we’re heading is. If we’re running NLP models on devices as small as smartwatches today, imagine what our smartphones, home automation hubs and, let’s not forget, civic and scientific sensors will be capable of in the not-too-distant future.
Another story from yesterday that got a lot less press than Android Wear, but highlights what I’m talking about, is the new computer vision division of police-department outfitter Taser. It acquired a startup called Dextro (who I covered back in 2014, if you want some background) and the computer vision team from wearable provider Misfit in order to form a new division called Axon AI. While Dextro focused on making video searchable, and Taser is talking a lot about video analysis, it’s not difficult to imagine a future in which police body cameras and even consumer wearables are able to do advanced computer vision in real time—with or without a cloud connection.
Last week, a startup called announced $2.6 million in funding to do just that.
Of course, wearable technologies are really just a subsection of the Internet of Things, which is also largely powered by deep learning (at least if devices aim to do anything useful). And IoT is driving investment in edge computing (aka fog computing) to ensure no device is ever without low-latency access to extra processing power or storage capacity. 
Finally, on a related note, I recently covered research into a framework that can let groups of consumer devices actually train deep learning models. Other scientists suggest smartphones could benefit from advances in quantum computing. IBM is apparently showing off promising results from its brain-inspired TrueNorth chip. 
Basically, our stuff is getting really smart, really fast, and in many cases we won’t even need to worry about having an internet connection to use it.

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Around the web: Artificial intelligence
While the world focuses on Intel’s earnings and White House press events, Nvidia is busy capitalizing on machine learning.
This is mind-bending and also quite promising. Money quote: “It’s like having a machine learning how to crack quantum mechanics, all by itself. I like saying that we have a machine dreaming of Schrödinger’s cat.”
Legal issues aside, it seems like the best strategy for a company like Baidu or anyone is to pair its AI expertise with partners’ expertise in specific fields. Andrew Ng discussed this in our recent interview.
With Tom Davenport of MIT, who predicts a slow decline of of certain jobs (bank tellers are still a thing, for example) and guaranteed jobs over guaranteed money.
This is good advice from one of the early members of IBM’s Watson business. In fact, because expectations are high, so are the chances for disappointment—that goes for enterprise and consumer software alike.
Silicon on the left, gallium on the right.
Around the web: Cloud and infrastructure
The company just started talking about what it’s doing. Here’s a post explaining its process for making things simple and secure.  •  Share
Kind of important for container security. I’m pretty sure Docker is late to this party, but I’m also not sure that will matter much.
Intel item 1: Of course Intel is focusing more on data centers with its new technologies than on PCs. It should maybe try to own that IoT chain from device to cloud, though.  •  Share
Intel item 2: Intel is apparently a good place for female execs. Patricia Damkroger is VP of the Data Center Group that’s ran by Diane Bryant.
It’s supposedly a more compact, more powerful alternative to silicon. According to this report, Facebook, Google and Oracle are experimenting with it.
Fast wireless like this has a broad range of implications from smartphones to data centers. Cellular speeds peak at about 50 Mbps.
We’re not even approaching peak serverless yet. And, like many things mocked early on (cloud included), it’s probably the real deal.  •  Share
Around the web: All things data
For once, I suspect Hortonworks competitors eyeing eventual IPOs are rooting for it to at least not tank. Open source IPOs are still something of a novelty.
Benchmarks like this make good headlines, but I wonder who a company like SnappyData (a Pivotal spinoff fusing Spark and the Gemfire database) actually competes with.
I change most of these headlines in the name of brevity and clarity. Not this one. Also, people, secure your systems!
It’s to make sure your infrastructure is order. This post is very markety, but point about building a common technology platform can’t be repeated enough.  •  Share
No that anyone reading this couldn’t spot a funky data visualization if they came across it.
Around the web: Security
As was VC investment overall last year. I do think we’re hitting security overload, though, where investors and M&A types don’t know which company of a million to focus on.
Its current product monitors AWS only. I thought the rule was to not get into ecosystem businesses that AWS can cannibalize. 
Israeli? Check. Security? Check. Deep learning? Check.  •  Share
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