Edge Computing: A Real Life Example With Elliot

The New York City tech ecosystem is exploding

In the five years following 2009, funding supplied by the venture, angle, and private equity for New York startups has increased by 200%.  Between 2010 and 2016, growth in the NYC tech sector increased by more than double, rising three times faster than the rest of the private sector.

Simply put, emerging technologies possess an unparalleled ability to disrupt. Gartner research indicates that AI initiatives are top priorities for companies in 2018. Almost half of CIOs surveyed from 98 countries are actively experimenting with AI or have medium to long-term plans to incorporate artificial intelligence into their roadmaps (46%); another 35% have artificial intelligence on their radar.

Conferences, workshops, and accelerators are delving into the new technologies niche. Emerging tech concepts are becoming more ubiquitous, even being considered mainstream buzzwords. The industry frameworks are ever-evolving with development communities. Innovation studios are solving problems with new technology for partners, facing down problems for startups, brands, and enterprises with fresh eyes. 

Crunchbase categorizes over 200 companies with NYC headquarters under the umbrella of “artificial intelligence.” Businesses such as these utilize AI to solve problems that touch on everything from health diagnostics, financial services, and predictive analysis to compliance and security. One start-up utilizing AI that we’re particularly fascinated with is Elliot, a B2B retail start-up tackling edge computing for retail. 

But what exactly is Edge Computing?

Edge computing is an innovative technology which is bringing computing applications, data, and services away from centralized locations to the edge of a network. It enables analytics and data gathering to occur at the source of the data. The technology leverages resources that may not be continuously connected to a network such as laptops, smartphones, tablets, and sensors. The role of edge computing thus far is to ingest, store, filter, and send data to cloud systems.

According to the International Data Corporation (IDC), the premier global provider of market intelligence, edge computing is a

“mesh network of micro data centers that can process or store critical data locally and push all received data to a central data center or cloud storage repository, in a footprint of less than 100 square feet.” 

When you hear “edge computing” it’s usually in conjunction with the Internet of Things (IoT.) IoT devices transfer data to a local device where it will be computed, stored, and connected. This data is processed “at the edge,” and then sent to a central storage repository in a corporate data center, co-location facility, or IaaS cloud.

In the context of IoT, ‘edge’ refers to the computing infrastructure that exists close to the sources of data, industrial controllers such as SCADA systems, and time series databases aggregating data from a variety of equipment and sensors. These devices typically exist outside of centralized computing available in the cloud.

Edge computing deployment is most ideal when, for example, an IoT device cannot be constantly connected to a central cloud. Edge devices collect data (usually in large amounts) and send it to a data collection center or a cloud to be processed. Edge computing sorts this data and allows it to be processed locally to reduce traffic and create a quicker processing time.

“Edge computing reduces latency because data does not have to traverse over a network to a data center or cloud for processing. This is ideal for situations where latencies of milliseconds can be untenable, such as in financial services or manufacturing.” as stated by International Data Group, Inc. (IDG).

To sum it up,

Using technology innovations, industrial companies are beginning to drive new levels of performance and productivity. And while cloud computing is a major enabler of industrial transformation, edge computing is rapidly becoming a key part of the Industrial Internet of Things (IIoT) equation to accelerate digital transformation. Edge computing allows data produced by internet of things (IoT) devices to be processed closer to where it is created instead of sending it across long routes to data centers or clouds.  

as quoted by GE.

Edge computing is more than just a buzzword, it’s the future

McKinsey & Co. estimates that the Industrial Internet of Things (IIoT) will create $7.5 trillion in value by 2025. The Industrial IoT connects humans to machine data that accelerate digital industrial transformation. At jakt, we are constantly looking to our peers in the realm of technology and innovation for insight and inspiration. We are enticed by both emerging technology and the infinite possibilities it puts forth. Having the  New York tech ecosystem at our disposal, we wanted to learn more about edge computing in real-life applications. So, we jumped on the subway and went a few stops uptown to sit with Elliot’s CEO and founder, Sergio Villasenor.  

Read our full interview with Villasenor below. 

In a couple sentences, how would you describe yourself as an individual?

I’m an extroverted introvert -shy but outgoing at the same time. I find myself liking to solve problems.

Alternatively, how do you describe yourself as the founder of Elliot, an NYC start-up tackling problems for global businesses with edge computing and AI?

As the founder of Elliot, I would say I’m a fearless risk-taker. I think what I come with is an ability to kind of work within situations that aren’t always favorable. Being as courageous as possible, and then vulnerable, which is challenging.

Can you tell us a little bit about your background and what lead you to the NYC artificial intelligence development ecosystem?

I was an athlete-turned-programmer. I graduated college from the University of Nevada. I played football there. I was a pre-safety but didn’t really know what I wanted to do after. I moved to Europe for the first half of my 20s. I lived in Barcelona, Milan, and Frankford. My flatmates were both creative and technical so they had backgrounds in programming, Adobe,  photography, and editing.

They encouraged me to check out programming. I downloaded Adobe. Dreamweaver was my first IDE (integrated development environment) and I got right into designing and programming. Ultimately, that leads me to Elliot.

Do you consider yourself a self-taught programmer?

Yes, definitely self-taught, with my flatmates’ help. I learned everything from Reddit, YouTube, and whatever I could Google at the time.

Growing up, I was the kid that got stuffed into lockers. I went to a technical high school, where you pick majors as you do in college, so the concepts I “majored in” included computer science. If anything, being athletic and playing football in college kind of took me off of the programmer path, but I got back on.

Can you tell us about Elliot?

Elliot is just providing a really cool way of enabling edge computing- what that means is we provide data persistence to containerization. So, we add a layer of data persistence to things like Docker (an open platform that performs operating-system-level virtualization) and Kubernetes (open source platform for managing containerized workloads), which in turn enables edge computing. For the industry that we work in, which is retail, this allows businesses to have more transparency across all the different applications they utilize.

In today’s day and age of e-commerce, with the rise of direct-to-consumer, a lot of the brands that started more recently have had the opportunity to use technologies like Shopify, and more nimble platforms but when compared to some of the older Fortune 500s and companies using older models and systems which make innovation harder, so Elliot provides a foundational “easy way” to do that.

Elliot is a transformative software that allows those that aren’t running so fast to keep up with the others.

How do you view the New York ecosystem for edge computing and AI?

We strategically picked New York for Elliot’s headquarters. We looked at all the major markets – LA, San Francisco, and New York, and felt that the engineering community had a stronger profile here, in terms of what we are doing.

From the category of “edge computing,” I felt that the development community here is in a place that is a little more mature, so we felt compelled to HQ here, given how talented the development community is for the technologies we are wanting to use.

 

What are some of the hurdles you face in explaining the technology Elliot uses? How to you convey value proposition to non-technical clients?

It’s always a challenge. I always like to use as many non-technical as possible, ultimately treat our buyer as if they were just a kid. How would you convince a five-year-old or a ten-year-old of the offer? If you can approach it through that lens you have much better success.

How would you explain artificial intelligence to a five-year-old?

[laughter] What’s artificial intelligence to a five-year-old?

If you’re five, you probably want candy or some type of treat that your parents don’t let you consume, so, AI would be knowing when you can have the treats and when there’s no one around to get you in trouble for eating them.

How do you explain edge computing to a five-year-old?

When you’re a kid, you do a lot of different things. You help run errands, you go to your grandparent’s house, you play with your brothers and sisters. You might have a particular toy that you always want to bring along, but sometimes you forget it. Edge computing is whenever it is the right place and the right time, you can get that one toy and have it wherever you are.

According to the info from your CrunchBase, Elliot went through three rounds of funding, as well as participated in Salesforce Accelerate. Can you talk a little bit about that process? Was it your first time raising venture capital?

This was my first time doing venture capital and my first time starting a software company. It was the first of everything. With the process, I was a little bit spoiled. I went to San Francisco really not knowing what was going to happen.  

Initially, we went there through an incubator called Acceleprise. We met with them and got right into the cohort. Fundraising was naturally a topic that came up. We did our first pre-seed raise in the first or second week we were there because I went there with no funds, other than the $50,000 they gave us for being a part of the incubator.

We needed to staff and get the word out, so, we needed to get some capital. We did the accelerator, and then an angel round in October that went right into our seed round.

Are you growing the team as well?

Yeah, we have a team of seven, all based in the WeWork here in NYC, at Irving Place. What is the breakdown of your team?

We’re all unique individuals- all technologists, by trade, but it is a pretty diverse team.

An example of this is me, and Tom Armstrong, who heads up sales. He’s this “anti-sales rep” sales representative with a technical background. He was a computer science major at Georgia Tech turn “Salesman of the Year” type, an awesome overall guy.

Our engineering team has a pretty diverse profile as well. We have backend engineers, data engineers, integration engineers, frontend engineers. Ultimately, what we are doing requires lots of different trains of thought, so that is how we assembled the team.

At Elliot, how important is culture in building a team?

It’s pretty important. Not just for building the team, but for building the product.

You have a thesis that you’re going on, and the framework for what you are trying to accomplish, to achieve your goals, and you have to have certain things in place. Ultimately, for me, it comes down to the characteristics you want your company to have naturally, or organically, in the market. It’s also important that the product, as well as, the culture, simplifies the thesis as well.

What were your experiences with raising capital for emerging technologies? Where there more difficulties with VC since Elliot’s edge computing platform touches on artificial intelligence, big data, and cloud computing?

Initially, we had a different flavor. I feel when you are raising money for a company, you have this grand vision of what you want it to be. Sometimes, as a founder, you have to take a couple of steps back and peel back the onion.

How do you get there?

Really, fundraising is articulating the milestones. It’s about how do you articulate where you want to go, but realistically, in milestones that are digestible. That way, those who are helping you along can relate to them, get behind them, and explain them themselves.

Can you describe a few of Elliot’s capabilities and what makes them more attractive than competing edge computing/AI offerings?

It’s kind of funny. I’ve been watching a lot of Scott Galloway’s videos from L2. Gartner bought his firm, and he’s a teacher at NYU. I love his videos. I don’t think he knows me or knows I watch his videos but he has a good theory on the concept of laddering, about how you disposition your competition. You shouldn’t necessarily talk about what you do better than them but rather, what you do differently.

So, if I had to say what we do differently than our competition, it would be that we create meaningful connections. With connectivity software, specifically like middleware, APIs, they have themes around marketing that touch on “we connect to everything”.Conceptually, this sounds great, but we want to connect to things that are meant for someone’s business, instead of just anything and everything.

Data integrity is a big play, as well, for us. Ultimately, you have customer data platforms or ETL (extract, transform, and load) tools so you can store all your data….and most of your data is crap, you can’t really do anything with it, so data integrity is a big one.

Everyone seems to be trying to be a “source of truth.” Everyone wants to be the authoritative party in any engagement. I feel like that’s fundamentally an issue with enterprise software. They haven’t shifted the mindset of being non-authoritative and looking at team members and software not just from the top-down approach for organizations. How do you create more collaboration? By taking a non-authoritative approach or review for your applications and data, instead of just saying we sit in the middle of everything.

You’ve made a digital product to solve a problem. How did you go from problem to solution? Were artificial intelligence and edge computing parts of your mindset from the beginning? Or did the solution evolve?

A lot of what is Elliot is just a culmination of my experience, at least working with brands. I’ve had opportunities in my past to work with really awesome brands. However, they hit this wall with the current market, which isn’t highly disruptive. They needed to be able to innovate.  A lot of what prevented them from doing it was having different silos- not just within the technologies, but within the organizations. As companies, they had not gotten to the maturity level needed to have collaboration, to have agility, and have speed. They come into retail but then they can’t keep up with Shopify and direct-to-consumer brands that are eating up the market.

I was coming up with those concepts and solutions for those problems. I figured this was probably a widespread problem and thought how can I extract the technology, sell it, and make my solutions available to other brands that could use it?

As a self-taught programmer, how did you teach yourself how to build with AI or machine learning?

Intuitively, it was always there. Logically, it’s like the next step that you would get to. You have a problem and you wonder how can I learn faster so that anyone that wants to solve problems? It just gets to the inflection point of wanting to apply technology to increase output.

For me, it just logically made sense. I would get to points where I wanted to work faster, or felt that I’ve repeated this enough times to where I thought if I apply some type of advanced learning, I would be able to move faster or I can probably solve problems quicker and more efficiently. Teaching myself to build with artificial intelligence was a retrospective on myself and how I can be better.

What do you foresee in the future for edge computing and AI?

I just feel like if you want something you should be able to have it. I feel like a lot of what technology is is recreating demand. If you think about retail, you’re not going to a website or mobile app to find something from product level for the first time. You probably saw a compelling piece of content on some type of medium like Instagram or SnapChat, or like my friend on Musically, where he said “Yo, that shirt is dope, I want it.”

I want to be able to get people to have that, when and where they want it. I want to be able to take it a step further, and build really cool technologies like molecular reconstruction to solve real-world problems, like if someone wants a fruit, they get it. I’m taking on the first steps to get to that future vision.

What are fringe cases for edge computing past retail?

The problems that retailers face are pretty ambiguous across all industries. They span everything from automotive to really old industries, like utilities, where things are isolated and there is a lot of room for innovation. Ultimately, for us, how do we continue to prove out the value of our products and take them to the next milestones, which allow us to bring in more capital? This important to build out the team, because as a start-up you only have a finite amount of resources.

Can you tell us a little bit about Elliot’s scheduled launch?

We’re currently baking out the current iteration of the products. We’ve communicated that it’s going to be ready at the end of October and we’re on pace, and pretty excited. We have a lot of early adopters and are doing proof of values right now and are on pace to launch, so I’m excited.

If you could clear up a false assumption about edge computing, artificial intelligence or machine learning, what would that be?

I think they’re all cool buzzwords and everyone thinks of them as buzzwords. Before you can actually create a real solution using these technologies; you have to approach the problems you are solving with an entirely different mindset before those terms can actually be relevant.

A fundamental flaw or assumption is “I have a problem and I can solve it using these technologies.” You have to think about how you can change your mind about applying new technologies, so you can look at what those technologies can do for society, in a different light.

What do you think about the New York high tech culture?

I’m excited to be a part of it. I ultimately picked New York for a lot of different reasons, from central team member talent to customers. We felt that it’s right for growing.

I feel like in the next year or two, the NYC high tech scene can probably compete with San Francisco and the Bay Area West Coast. I’m excited to be a part of this growth.

Real Life Applications and Emerging Tech Spotlights

We at jakt are excited about not only the future of edge computing but the future of real-life applications using this innovative technology. Have a start-up utilizing IoT or edge computing or other new technologies? We’d love to learn more! Look out for our next emerging tech spotlight, and contact us if you have any questions surrounding edge computing or are looking to utilize cutting technology in your next project.