Tim: So, tell us a little bit about Lynx?
Chris: So Lynx Laboratory is a 3D imaging company. We produce cameras that capture 3D content as quickly and easily as your video camera. So, you can use this content to make video games, to animate models and visual effects, to even do things like architectural modeling.
Tim: And what do you make that lets people catch this content, how does it work?
Chris: So, we’ve developed technologies, it’s a hardware and software platform that makes 3D imaging about 40 times cheaper and 100 times faster than what’s available today.
Tim: That sounds like a pretty big leap, how do you get to that?
Chris: Well, what you have to consider is that that in the vast majority of cases people are building this content by hand. So, if I want to make a model of a building, I’ve to go out with tape measures and basically measure every single room, the height of every room, all the details and then I spend a month modeling all that content by hand and what’s different about this is that we brought that quality of content production into a capture device. So, it’s a camera that produces that type of 3D content.
Tim: Now the camera you’ve got which we’ll try to take a look at in a few minutes, I know it’s got some off-the-shelf stuff and some things that you probably had to modify. Describe the hardware itself?
Chris: Sure. So, our company thinks that hardware is changing, what you don’t want to do is go to a really expensive chip or an optics innovation. If you can solve the problem in software, then you don’t have to raise a ton of money to make it possible. So what we’ve done is, we’ve integrated off-the-shelf parts and made incredible software that makes them do things that you never thought that they would do before.
Tim: Now, what kind of off-the-shelf parts are you talking about?
Chris: So, we use a very low cost camera, we use standard computing components, so things like RAM and video cards and we put it all together to basically create this intelligent device that has brains and the camera.
Tim: Is it running on an underlying operating system like, it’s running Android for instance or is it running a lower-level embedded software operating system?
Chris: So, we could have worked with anything. For this particular model we’re using run-of-the-mill Linux and into the future we might consider something like Android.
Tim: Is it an X86 chip underneath?
Chris: It is.
Tim: Okay. But it is battery powered because it’s portable?
Chris: It is battery powered. So the battery lasts for about two hours and if you are just using it to visualize, it can last long as five or six, so compared to regular cameras that’s a lot better.
Tim: Okay. Now the size of the data sets you’re collecting, how big is that? If you run this and you get your model, the Sistine Chapel, how much data are you collecting?
Chris: So one of the big innovations that we created is reducing the amount of data that you’re processing when you’re using the camera and when you’re exporting it. Now we export to all these standard formats, but our data format that we use to move data around and that you’ll use to move the data around after you capture can do very big things in just megabytes.
Tim: Okay. When you say just megabytes, what will that include? I know if I take a picture with a camera, I’ve got rough idea of what a megapixel camera snapshot is like?
Tim: If you capture a suburban house in pretty good detail, what are you looking at?
Chris: You’re looking at maybe 25 megabytes.
Chris: So, in comparison if I was to maybe do four raw snapshots of each room over eight rooms, you could be talking about 200 megabytes. So, usually the way that I explain this is that, the simplest explanation is the right one, so when you go and you capture all of the shape and you get it correct, it’s the smallest way to represent the data.
Tim: Now, your background is in math, can you talk about how it led to actually being basically in charge of a combined hardware/software company?
Chris: Right. So, yeah, our story is pretty interesting. My background is, I’m an applied mathematician and I had some experience with entrepreneurship, but most recently I was a researcher at the university. So, what we were working on there is basically, what would happen if we made 3D imaging techniques a 100 times faster and 40 times cheaper and we thought it would have this impact in robotics and defense applications, but we’re really surprised that all these people from architecture and visual effects came to us and said, wow I could really use that, so that’s how the company formed. We just had so many people lining up saying, could I get my hands on that, that we just had to build it.
Tim: Now, the cost of this, it ranges from about $1500 to about $1800, is that right?
Chris: So, the most basic model that we sell right now is available on Kickstarter today. You can find it by searching for the Lynx A camera on Kickstarter. To do things like model people and then turn them into a 3D printing, we charge about $1800 for that camera. For professional users that want to map things that are a lot bigger, do animated characters, we charge about $2800.
Tim: And the business itself, when you said the university, I should give people who are watching this a little context... you say the university here in Austin, the University of Texas?
Chris: Yep, the University of Texas at Austin.
Tim: So, your employees also came from UT, it sounds?
Chris: Yeah. So, not every startup is going to begin at a university, in our case we did and the University of Texas is doing a lot to make startups that come out of it more viable and to make the path of creating a startup at the university more viable, so there’s people like Bob Metcalfe, the inventor of Ethernet that spends every single day working with senior entrepreneurs to help their companies become a success. We also have the Austin technology incubator and the capital factory. So, the university working together at these commercialization outfits is going to help Austin be the hub for the next big research and technology innovations.
Tim: But, this isn’t your own first experience with a startup company, is it?
Chris: No it’s not. So, I was a technical architect at a startup focused on machine learning for solid state disc drives and what I’ve learned there is that, creating great technology is really important, but even more important is finding ways to talk to customers, learn what they need and build something that really resonates with the target audience, so I think that’s what we’ve done here.
Tim: One thing, your software itself, I got a glance at it yesterday and I was impressed by how much you’ve pared down your available options to make it little bit more humane. I mean, I’ve looked at Blender and I find it a pretty overwhelming interface.
Chris: Right. Well, Blender has a place in the world. If you’re trying to create highly detailed content or something that doesn’t exist, you need all those options, right? But, if you are imaging something that’s actually there, there is not that much you need control over, we want to help people adjust their polygon counts so they get the right size for their video game, we want to help people smooth things out, but beyond that really it’s done when your image it.
Tim: Okay. And talking about entrepreneurial aspects of your company, one of your employees got hired in an interesting way. I’d like you to tell me the same story to our watchers?
Chris: Hey Dustin. Can I introduce Dustin?
Chris: Dustin, come here. So, the thing about entrepreneurship is that there is not a specific career path to become an entrepreneur, right? So, I wouldn’t say anyone should just drop out of college, but that’s what Dustin did and so I met Dustin when he was 18 years old and he was playing World of Warcraft all day and as I am sure a lot of World of Warcraft people imagine that they’re doing, they try to crack the map of World of Warcraft and create the best character that he could and what I thought was really odd was like the map checked out. So, I started throwing him side work. I was like, hey $100 if you can solve this programming problem. And with no prior experience, he sort of took to it really quickly and after a year we had people coming to us and saying I really want to poach that engineer. So, he got better than the college education in a year just on his own personal drive.
Tim: Dustin, was it UT that you dropped out of? Dustin: It was Texas State.
Chris: I think he could have picked a better university to drop out of.
Tim: Well, right, I mean, Michael Dell dropped out of UT.
Chris: Texas State is a great university. I’m just going to put a little plug in for you too.
Tim: All right, and what else should people know about your system and your company?
Chris: So, this is a breakthrough technology and right now it recreates 3D content faster and easier than anything else that’s out there. Where we are headed next is do things intelligent with that data. So you could imagine all these great applications when you start doing decision making on the data. For example, when something like this goes into the Xbox Arcade and you can scan your feet to order the correct size shoes, a sense of mass personalization things. And even on top of that, just something like comparing a model that you require against something that you already have on record. So to correct defects and maybe save yourself millions of dollars on defective parts, you’d be very surprised on where this platform could head.
Tim: One more thing, about the openness or closeness of the software you’re using, you talk about what model you are using, is there anything open source? Does your company have any connection with the open source world, you talked about formats you can export to. So where are we in that role?
Chris: So there’s two things, it’s how open is your platform to interact with other technologies and then whether you are using open source software. So our platform is fairly open. All these applications that workflows exist around, we export models that can be imported into architectural software, visual effect software, it plays nice with all the processor sort of creating things by hand today. As far as open source software, under the hood there is a real scientific innovation and for now, we have our platform closed source because we’re trying to defend our invention. But we have a great relationship with the open source community including great 3D companies, like Open Perception. And I would stay tuned, because over the next year we’re really going to look for opportunities to get better.