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In the News

Marty Sprinzen Interviewed at nGage IoT Austin 2017

Listen to Marty’s insightful interview about IoT, microservices, AI, and how VANTIQ fits powerfully into this ecosystem.

Transcript

Daniel: Good afternoon. My name is Daniel Obodovski. I’m the founder and CEO of The Silent Intelligence, And today I’m here with Marty Sprinzen, founder and CEO of VANTIQ corporation. Hi Marty.

Marty: Hi

Daniel: How are you doing?

Marty: I’m doing pretty good.

Daniel: How’s the conference been for you so far?

Marty: It’s interesting hearing a lot of the use cases, talking to some of the people. Informative for sure.

Daniel: Excellent! So tell us a little bit about the history of VANTIQ and what VANTIQ does.

Marty: Okay. We were formed two and a half years ago with the the soul goal of making applications easier to build today. It is very complex out there you’re talking about AI and iIoT and microservices and all of these things that are being in the cloud that are being innovated. And what we do is enable applications to be built from kind of a virtual perspective above that and we do that by not worrying as much about the physical environment when you build an application and automating things you never thought of such as an Uber style application – very easy to build.

Daniel: Awesome. Let me ask you this: you mentioned utility companies. How would VANTIQ help simplify the software development and application development in the utilities environment?

Marty: Okay well we actually have an app that was built with an SI and it’ll be targeting the utilities environment. And what the app does is it monitors transformers. It monitors voltage, amperage, temperature, and some other factors. Transformers are not monitored. The old ones are 30, 40 years old, and there’s no easy way to monitor them. The benefits to this are predictive maintenance when they frequently go out or if they do go out they know that they went out. The other benefit is apparently there’s a lot of theft off the grid. They can actually measure what’s happening to determine whether or not theft is occurring. And they claim tens of dollars per month per build is lost basically because of theft. Innovative concept. So basically it’s an IoT type application. We include human interaction with it. It will inform people when there’s a problem, even monitor when the technician comes to repair it and keep track who has what skills, etc.

Daniel: Excellent. This morning in the keynote you were talking about microservices. Can you talk a little bit more about how microservices are critical for IoT?

Marty: Sure. A lot of the applications, we’re talking about external microservices first, a lot of the applications that are being built today can benefit from knowing certain things in the environment. Clearly, locations: You call Google Maps, find out where you are. That’s a service, if you will. The term microservices is sometimes used incorrectly, so I’ll say services in general. Obviously, you can find out the weather information, the humidity in a certain location. You can also find out very particular information. So as an example: CDC keeps track of what diseases appear where in which hospitals. All of those types of information can be used in applications today. It opens up tremendous amounts of new types of data for building industrial applications or enterprise applications.

Daniel: And how do you think this area is going to evolve? Are they going to be offered subscription fees or what needs to happen to make it really easy to consume those microservices?

Marty: They charge per service, typically. So if you’re using NL (national language) processing services from say Watson, you pay for it on the service basis. Many of these services are free I should say though, such as governmental service. But also many of them charge you by the use of the API.

Daniel: Very good. Now, I was going to as you about artificial intelligence, and some of the work that you’re doing in this space and also ask you how do you see this space evolving in the next 3 to 5 years?

Marty: Okay. AI, machinery in particular, is exceedingly useful for particular types of functions. So, if you have a motor and you want to determine whether or not it needs maintenance. Or if you have a jet engine, perhaps a better example. Jet engines have thousands of IoT sensors on them. Taking that data and doing a big data analysis enables you to predict failures in advance and extend the lives of these types of assets. What we see is the inclusion of the AI algorithms in the next generation of IoT applications. So, applications can be written that can use that information to basically – we strongly believe in human-to-system collaboration: telling humans when there are problems in advance. So, “That machine is about to crash. Replace it.” Or in places like retail. That customer has been standing, “dwell time”, at that location looking at the jeans for more than two minutes. He’s an existing customer. He has bought the jeans before. Tell the salesman to go over there since he is standing there alone. And perhaps, knowing that the jeans of his size aren’t even on the shelf there. And he’s looking through the shelf. That’s kind of somewhat AI, somewhat algorithmic, a little bit of each.

Daniel: Do you think AI is going to take a lot of jobs away like a lot of people think?

Marty: It’ll take the easy jobs away and that’s fine. Now, I do believe there will be other jobs created. As we build these systems, these more complex systems, people have to manage them. And it’s not just a few people. It’s a lot of people that have to manage because the systems have so many more interfaces. And I think what’s underestimated a lot in the industry is how much man-machine collaboration is going to be needed in the future. And we’ll just be a lot more effective at doing things. Safety, for example, there’s a lot of situations with oil rigs, with mines, where better safety can be accomplished, and people have to interact and monitor those situations. Or security cameras are going to be popping up everywhere using facial recognition to know whether or not you’re an employee, you’re not an employee, you’re on the FBI wanted list perhaps. And those systems are very sophisticated, but they require humans to be involved in that. So, to the extent, yes jobs will be taking away certain, trivial types of tasks. New jobs will be created. I think the hope, certainly my hope is, that those new jobs are going to be quite extensive and quite numerous.

Daniel: Excellent. Man-machine communication and man-machine corporation. I like that. Marty, thank you very much.

Marty: You’re very welcome.

 

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