Sometimes, spatial computing can seem like a completely new idea, or a group of technologies that emerged from nowhere in the last few years with the release of a few notable Apple products.

The truth is that spatial computing has much deeper roots than Silicon Valley. For example, look to the work of laser scanning service providers, who specialize in the use of lidar technology to capture 3D data sets of real-world spaces. These professionals have long explored the possibilities of spatial capture for applications like construction, stockpile measurement, and more. And their experience gives them unique insight into the real-world, practical uses of 3D data.

We caught up with a true legend among laser scanning professionals, Carlos Velazquez of Epic Scan and EveryPoint, to pick his brain about the state of spatial computing. We talked about the early days of 3D data, how lidar scanning helped get us to where we are today, and the truly “infinite” possibilities for 3D data in business and culture.

Sean Higgins: Let’s start at the beginning. Can you tell me a little bit about your background and how you came to spatial computing?

Carlos Velazquez: I think, honestly, my path to spatial computing started when my parents or my grandparents got us a Commodore 64. But college is where it started to really take shape.

I studied mechanical engineering at Oregon State University in Corvallis, and I found my greatest strength was the 3D design and 3D modeling programs. I became a master of Pro Engineer, a CNC program—you can design an object, and then the program generates the code to actually build it with machine processes.

After school, I was trying to figure out what I was going to do with a mechanical engineering degree. I remember so vividly thinking that I don’t want to get caught designing bolts or something extremely boring like that. Well, as they say, be careful what you ask for. A high-school girlfriend’s father happened to be getting into this technology called lidar. So he shows me this tool and says, oh man, you have got to get into this, it’s the most exciting thing.

So I jumped into lidar, but it was still the super early days, and the software was still new. I learned all about CGP, or computer graphics perception, which then evolved into Cyclone. I taught myself the entire program, literally going through every single function. And then, based off of that, I started developing different use cases in the survey world.

So you experienced spatial computing during the early days, when 3D tech was just starting to develop. I wonder, what did the term “spatial computing” mean to you then, and what does it mean to you now?

Back then, it meant something very different. I was just learning about this cool new technology and trying to digitize the world, or create 3D models that people would want to use. Today my understanding of spatial computing is much more evolved because I see it as the connection—the fiber—between everything real and everything digital. Any time we access reality, or the physical world, through another medium? To me, that’s some form of spatial computing.

What are some the most impressive uses of spatial computing that you’ve seen in a business context? This could be from the early days, or today.

I have to point to what we’re doing at EveryPoint, with Stockpile Reports. We’re using our spatial computing platform to make the digitization of stockpiled inventory a real possibility.

The next use case is working with materials companies to perform auto-replenishment. So what that means is we set up camera systems that use photogrammetry to monitor their material piles. And every hour, the customer receives an updated volume number, or indication that there is sufficient material there. So it takes all the manual work out of that process of replenishing.

Since Stockpile Reports is based on our EveryPoint spatial computing platform, we’ve enabled the scale to be infinite. I mean that in terms of both the scale and the frequency of capture. Using spatial computing, we’ve enabled the inventory of stockpiles to be potentially infinite.

Stockpile Reports’ SR Measure app uses spatial computing to perform stockpile measurement with mobile phones

It sounds like scalability is the primary value of spatial computing for businesses. It makes it possible for companies to do a lot more.

Exactly. We can now capture the volume, location, and time of any pile of material at any scale anywhere on the planet. With the auto replenishment use case, I like to ask, How many auto replenishment models are out there that businesses could benefit from? There are material producers all over the place. So, the idea of eliminating these transactions that take lots of time and money will dramatically improve efficiency.

We know each other from the 3D-scanning hardware world. I remember always being struck by the ways that your company, Epic Scan, pioneered the use of AR and VR in survey-grade 3D scanning applications. How did that come about?

I see the evolution of the technology like this: The point cloud creation was the first big step. Figuring out, how we could improve the process of generating point clouds for these different markets, businesses, and industries?

During this stage, as I worked with 3D scanning technology, I saw it develop and grow. With every new evolution of 3D scanning technology, the functionality started to increase, the mobility started to increase, and the size started to decrease. I saw opportunity everywhere, and I realized that the real business was trying to convert those point clouds into something useful for the specific industry. Whatever the market was, they wanted the point clouds in this flavor and this shape and this size.

That’s why I dove really, really deep into the world of virtual reality. I spent a couple of years with it, because I saw VR as a space, or a canvas, for viewing point clouds and interacting with them in new ways. But it’s doing more than that—it’s also blowing up the concept of spatial computing.

How do you mean? A lot of people think of VR as a place for viewing more or less static “worlds,” but not as a medium for viewing data.

I think VR is the ultimate place to make real-world data useful. You can use it to aggregate the 3D data into this infinite space. And, honestly, that’s probably one of the most significant words that came out of my time with VR: “infinite.” In VR, there’s this concept of infinite potential, or infinite possibility.

VR is going to allow us to take any bit of data from any sensor, from any environment in the real world, and feed it into this environment where we can interact with it in ways that make much more sense.

In contrast, think of a piece of paper, or an Excel spreadsheet. With those tools, we have to do all this decoding and deciphering to understand what the data means. In VR, the medium is going to fade into the background, and the data is going to have intention and purpose. AR is obviously going to be the real world version of that.

Carlos demonstrates his innovative spatial computing art project.

What’s the most interesting use of spatial computing that you’ve seen outside of the business world?

One of the coolest uses, I have to say, was my own personal creation for some art exhibits in Ashland, Oregon.

A friend of mine who’s into 3D coding designed a platform for me to ingest point clouds into Unity. Then, on top of Unity, we built all these tools that allowed us to create unique interactions for anyone visiting the exhibit. We had a 55 inch screen with a Kinect sensor hooked up, which basically turned the person who approached into the controller.

The first exhibit was the Stout Grove redwood forest in Northern California. We created this point cloud of that redwood forest, and cut it in a unique way. We placed it in space, so it felt like you were literally in the universe, surrounded by stars in the Milky Way. And then we made all the points very dynamic, meaning they would flow like water or like wind, so that your movements would push the points around as you move through the space.

The points would just float and sway. And with a single pass of your hand, you could move the entire forest. Or, your hand would move through the forest, and the points would flow and bounce and then settle back into their original location.

This sounds like a great example of the ways that virtual worlds can change the way we look at something—data, an object, a real-world environment.

We have these First Friday art evenings where people would tour around the city and look at different art museums. And they’d come into our place, so I got to see hundreds of people interact with this exhibit. I had a handful of fascinating experiences where people saw it, and connected with in such a deep way that they started to cry. It broke them down to literal tears.

I had no idea this was possible, that you could actually cause somebody to be so connected to this digital form that they felt like they were there, seeing the forest in a way that was very unique to them, even in this digital format. That was really powerful.

It sounds like you know as well anyone why spatial computing are so hyped right now. Where would you say these technologies fall on the hype cycle?

I think that we’re probably somewhere in the slope of enlightenment.

From a business angle, we’re getting into the problem of data flow with spatial computing. We’re starting to work on products that give people the ability to take any number of data streams, combine them in a single platform, and make that data more valuable than when it was fragmented. It’s what we’re doing with EveryPoint.

That’s why I’m starting to explore the marketplace for spatial computing. I’m asking, what is the market, what are the use cases? I’m starting to see some really clear and obvious use cases, often around live and critical events, or time-sensitive events.

For example, think of all of the data and information that flows around critical wildland fires, and how hard it is for different individuals to navigate that data. I can see EveryPoint acting a spatial computing platform in which all this data is collected and disseminated in an intelligent way that gets it to people quicker and more efficiently save lives and property.

Is it possible to collect and disseminate information that quickly? You had talked about stockpiles earlier, but these applications seem like they would require you to move data much faster.

Well we are dancing on the edge of our ability right now. Right now, from a business perspective we’re capturing point clouds, and we’re processing them into a customer deliverable in an hour, for hourly updates. But that frequency is going to continue to increase. Someday soon, the data will be delivered nearly instantaneously. In fact, there are already systems that we can use to deliver live data, as long it solves a business problem.

Carlos’ redwood installation used for a storytelling application.

I get why you say the technology is in the slope of enlightenment. As you’re describing what we can do with it, it seems like we’ve worked out how the technology operates and how it can be useful to us in a few limited ways. But we’re about to hit that point where it surprises us.

I think it’s going to take off when people and companies start to utilize it properly. It’s going to start to feel like magic and we’re going to start to feel like superhumans.

So what’s stopping us from getting there? What do we need to focus on to make full use of this technology’s potential? Do we need to improve the technology itself, do we need to work on the culture, or something else?

I feel like it’s ultimately people that we need to work on. I think the problem is trust.

You think people in business are having difficulty putting their trust in technologies like spatial computing, mixed reality, and augmented reality?

Right. But this is also why I’m really excited about where spatial computing is right now. It relies on point clouds, and they don’t lie. Or, at least, they’re a known interpretation of a space, a quantifiable interpretation of a space. So there is this truth to them.

You know, when I was with Epic Scan, I used to love getting a point cloud of a project completely registered, QC checked, verified, validated, on its coordinate system, and so on. At that point, the point cloud is like a foundation for that entire project—and we’re dealing with billion-dollar projects. And so the point cloud is the foundation that they’re going to make all these decisions off of. And I think that is incredibly powerful.

You’re arguing that if a billion-dollar project can rely on a point cloud, so can the rest of us?

I think that as we continue down the path of using point clouds for VR, AR, and so on, we’re going to find that it’s very hard to lie in 3D. At least, that’s true from what I’ve personally experienced in the content creation side of it. Because as human beings, all our senses, all of our ways of interpreting the world around us are tuned to understanding the world in 3D.

And this makes it harder to trick us in 3D than it would be in 2D.

Yes, I believe that when you immerse us into a completely three dimensional environment, even if these worlds are full of unknown stuff, we’ll enter knowing certain parameters about how a 3D world is supposed to operate. And it’s going to be very clear to us when something in the world isn’t true.

I think that we’re pretty amazing at being able to distinguish between the realistic and unrealistic in a virtual space. And I believe that we will always be, because digital worlds will never be an exact replica of real world.

Do you think this means that we shouldn’t be focusing so much on creating a full digital replica of the real world?

I think all explorations are worth it. But, I see that we’re missing an opportunity in VR on the lower resolution side of things. You don’t need hi-rez, high detail, perfect translations of reality into these virtual worlds in order to create an experience or accomplish a goal.

Salem’s Riverfront Carousel Building by EveryPoint on Sketchfab

It almost sounds as if we’re focusing on improving the technology toward an impossible end-point—a full digital replica of reality—rather than focusing on a more meaningful goal.

Spatial computing technologies have some clear use cases already, but we could be doing much more. I think the problem, more than anything, is that a lot of people just are not working with real intention. They’re not defining clear goals, or trying to understand what tools should be utilized for that specific intent.

Man, I’ve been feeling this way for many, many years. I feel that if we only could step back for a moment, look at the world and say, let’s make a list of issues from a global perspective. Let’s make a list of what humans have created to this point, what tools and capability we have as a result of our technological advancement. Let’s actually have a discussion about these issues, and come up with a possible solution using our technologies, or even make a plan so that we can start to make some steps towards our goal.

Why do you think we’re not moving in that direction? It seems straightforward enough.

It’s like I was talking about earlier, there seems to be this huge barrier of mistrust, misunderstanding, and fear of anything that is going to change.

What I have realized in most of my professional career, is that we love things the way they are—whatever they are. When we love something we don’t want it to change. And in business, when we’re talking about technology, it’s no different. But I believe spatial computing technology can bridge an enormous number of gaps, and solve some huge problems in how we live life, how we function, and how we even treat each other.

So you’re optimistic that if people embrace this new world of spatial computing technology, they’ll see that the future is positive and exciting?

Yes, 100%.

Find Carlos on Linkedin.