LIDAR Spells Autonomy: Luis Dussan, Founder and CTO at AEye, Inc

Brandon Cardwell: I’m Brandon Cardwell, your host of the Startup Tri-Valley podcast. And we’re back — it’s April, 2022. Our last recording was in December of 2021. And part of the reason for that break is I’ve taken on a new role. I’m now the Innovation and Economic Development Director for the City of Livermore. I’ve been with the city for quite some time, but representing the Tri-Valley startup community, including as your host of this podcast.

Looking out over 2022, we’re going to be adding some new voices to this show, including our next episode, featuring Lynn Naylor of Innovation Tri-Valley. I’ll be joined by Yolanda Fintschenko, my collaborator at the East Bay Bio Network, and co-founder of FounderTraction. Today, we have Luis Dussan, co-founder and CTO of AEye, an original incubator member company that went public last year.

I hope you enjoy the show.

Welcome to the Startup Tri-Valley Podcast. I’m your host, Brandon Cardwell. We are back here. It is April 13th. And I’m here with Luis Dussan, founder and CTO of AEye. (That is A E Y E, for those of you Googling.) Luis, welcome to the show. 

Luis Dussan: Thank you very much. Happy to be here.

Brandon Cardwell:  So this is a fun one for me personally. We’ve had a couple of guests who have been part of our broader ecosystem and story over the last, uh, few years, almost a decade-plus now, I guess.

So AEye started as US-LADAR. 

Luis Dussan: That’s very few people [who] know that, so that actually tells you a lot about our relationship. 

Brandon Cardwell: … And how long we go back. Um, I dug up when you guys got to ring the bell, when you went public. I went back through my emails, because I knew I had some good stuff in there from you going back to 2013, I think I had to dig into the web archive and I found an email from you.

And the whole email was: “Just bought our tickets. So we’re definitely coming,” or something to that effect. And it was, you know, 2013. And we’d been going back and forth while you were in Orlando, Florida — they’re still, um, working out, you know, whether you were going to come to that incubator, uh, quotey fingers — “incubator space.” We were operating on Longard Road — uh, basically a big empty warehouse, before you and a handful of others showed up.

You know, I, I’m kind of jumping the gun here a little bit, because I tend to do that when I have guests on here that I’ve known for more than 10 years or whatever. Tell us a little bit about your background. So let’s start at the beginning — education, how you came to the position that you’re in now.

So, start us off. 

Luis Dussan: Oh, okay. So that has to go back quite a bit. You know, I, one thing about me was I’ve loved learning all my life, and I really thought that my career was going to be something like, I was going to get my bachelor’s. My master’s. Another masters, another masters, a PhD, potentially another PhD. And I would eventually just go and teach or work at Jet Propulsion Lab, which is one of my all-time favorite places to work, right — the Jet Propulsion Lab in Pasadena. 

And, you know, for the most part, that’s how it went. I graduated with my bachelor’s in electrical and computer, went and took a communications engineering — electrical engineering, communications engineering, masters. Two classes before I had to finish, I was like, oh, I don’t like that.

And, so I left, while I was at a startup — and went and did another masters in optical communication, which I liked a lot. But that company ended up going bankrupt, right? It was the, if you recall, it was like the telecom industry back in just before September 11th and then September 11th kind of killed it.

And at that point I moved to Orlando, Florida, and I was lucky because Orlando, Florida was exactly the right place. The University of Central Florida-Creole was exactly the right place to study the things that I really liked, which was light, lasers. So I got an optics and photonics master’s, which I loved, and it taught me that I really wanted to learn more about physics.

So, the next master’s was basically quantum physics. And from there I wanted to get my PhD in computational quantum physics, which is basically the study of quantum effects in condensed matter. And that’s what I really wanted to learn more about. And, so along the way, I did a lot of training, and one of the things that it taught me was not just hardware, but software and algorithms. So I had a great that — those — that set by chance or, you know, by design, that set of curriculum, along with my career, NASA, Lockheed Martin, Northrop Grumman, really taught me kind of the things that make up, what was US-LADAR —  now, AEye— which was a lot the confluence of advanced sensing concepts, hardware, and software, and algorithms. 

Brandon Cardwell: Right. 

Luis Dussan: And I’ve told you this story before, but while I was raising money, one of the things that I think helped me was I was able to just code up and simulate [what] AEye, the — the — our force item product for example, was doing. And so I could show it on a computer screen.

I could put something in the loop and show people, and people were like, Oh, I see what it’s doing. I understand what you’re trying to do. Yes. That makes sense. And I will fund you. Right? 

Luis Dussan: So, that’s my technical background. And obviously my career was NASA, or I did a lot of RF downlink, a lot of radar work.

I was lucky enough to, at the beginning, start off with the, uh, the Sojourner Rover, the one that landed on Mars — the first one — not the Viking, not the ones that were, you know, just landed it. This was the first Rover. And I was able to work on the downlink associated with communication, deep space communication with the Rover.

And then after that, I had startup experience, which really set me up. Actually, I don’t talk a lot about that. It was Qplus communications, Qplus networks, but it actually formed a lot of my ideas about startups,and otherwise it was a very positive experience from there. I went to LA. And at Lockheed, I did a lot of remote sensing.

I got to work on the sniper pod. And if you’re not familiar with the sniper pod, it’s been in the news. And if you’ve seen it in the news, there’s two really big things that happened. One was the war in Iraq. It was able to look at disturbed earth. So the planes, instead of targeting things, would just notice that some of the dirt was a different color with the thermal cameras and that’s where they buried the ID. And people were like, We didn’t even know we could do that. Right? 

Luis Dussan: So the jets were flying around doing reconnaissance, not actually doing anything else. And that was a big thing. The second one was, if you remember the tic-tac UFO that kind of made the rounds a while ago, that UFO was spotted with the Sniper pod. Right? That’s the one where you see the thing and the thermal. 

Brandon Cardwell: Yeah. 

Luis Dussan: Right. So that was the thing that I worked on. And, and, and, and that system was super complicated. Three lasers, three cameras, all down one single aperture. So think about three different ways — uh, six different wave links actually, and wave bands all going down one aperture.

So that’s one material that handles all the wavelengths. Just the material science alone on that was a learning experience, right? It was a thesis. And I got to learn from a bunch of great engineers. 

Brandon Cardwell: And you were at Northrop for that? 

Luis Dussan: That was at Lockheed. At Northrop, I worked for the general, the special forces ground troops. Those were our main customers. And they wanted the sniper pod in a five-pound unit that basically did the same thing. 

Brandon Cardwell:  Right. 

Luis Dussan: And of course that was impossible. So you did some trades, but, um, but that was also an amazing experience to learn. Just the things you have to do to be able to do some of those things.

And I got introduced to a lot of concepts, a lot of materials, a lot of devices that I worked with DARPA on, and those things, little by little, all those things kind of made their way into the AEye sensor. 

Brandon Cardwell: So you’re at NASA. And then you go to a startup. What was your role at the startup — at Qplus, you said?

Luis Dussan: I was one of the first employees. Yeah, I was one of the first employees there. My job was to simulate the optical communications, like we were doing a fiber optic communication using polarization and modulating the polarization. And right now — I mean, at that time, the way it was done was you just turn the light on and off, really fast. And that’s still a way to do it, but recently, so polarization.

So you leave the light on, but you change the polarization axis and you track it on the receive side. And depending on which way the polarization is, that’s your signal, that’s your bitstream. And it has a lot of really positive things about it. But, if you recall during that time, the big thing was there was not enough capacity in the fiber optic network in the US.

Well, it was a big lie. There was plenty. Way more than the demand. And so all those telecom companies basically did that and I got caught up in it. 

Brandon Cardwell: Okay. So it’s an interesting path, though. So you go from NASA to a startup and then back into defense contracting while you were in that leg of defense contracting, your career. Did you know that you wanted to be a founder at some point from that experience that you had at Qplus, like being an early employee? 

Luis Dussan: I mean, I didn’t, I don’t think I had formalized it in my head, yet, because I hadn’t had the full experience of working for an aerospace [company] or a large company. But by the time I got halfway through Lockheed, I was like, Hmm. Yeah, this is not, you know, I could become a Lockheed Fellow. That’s probably the highlight of my career. Right? And that wasn’t exactly what really made me wake up in the morning. And I wanted to, I thought, you know, for me, one thing characterizes my career everywhere. I went, I came in as a certain position, and I ended in a position that I created with my management team. Like, look, you need somebody to do this. 

Brandon Cardwell: Totally different fields, but I understand that. Yeah. 

Luis Dussan: And I think that. It is potentially an indicator of the kind of person that you are, like —  

Brandon Cardwell: There’s an entrepreneurial characteristic that people have when it’s like you actually follow problem sets and create solutions to those problem sets outside of the formal hierarchy or structure of an organization.

Right. You’re like, I actually want to work on a complex problem and the sort of bureaucracy around that will have to take care of itself, or I’ll like invent a thing that lets me do what actually needs doing so, no. Yeah, that’s kind of a founder mentality expression there.  

Luis Dussan: Yeah, and, and of, obviously I didn’t know that at the time, but for me it, what it was, as what I was really saying to myself was, I’m not happy doing what I’m doing.

Right. Like I want to create my own thing and, you know, then, you know, Ransom and the whole story that we tell, we tell about how, you know, we actually decided to do it. And then one day I was doing my PhD, the opportunity presented itself. And I took it. 

Brandon Cardwell: And that was when? 2013? So did you finish your PhD?

Luis Dussan: I did not. I had a choice — take the qualifier or start the company. And I decided to start the company. 

Brandon Cardwell: That worked out okay.  So, you’re in Orlando and you make that choice. Why come back to the Bay Area and the Tri-Valley? That’s, you’re from the area, right? You’re from the Bay. 

Luis Dussan: Yeah, we did consider Boston.

So you know, Ransom and I looked at this very objective, like, okay, you look at all the startup companies in the world. Right? And I think, and I’m, you know, don’t quote me on these numbers — but it’s like, you know, 25% of the investments are in. You know, the Bay Area or Boston or something like that. And I think 90% of the returns, right in California, like that tells you that the success is ridiculously high.

And I had family in California. So for me it became kind of a no brainer. You go back to California, go back to the Bay Area, call it a day. 

Brandon Cardwell: Yeah. Well, and I’ve told this story before in other venues, but you and I had a conversation back in 2013 or maybe early 2014, and then I think it was 2013, because it was before you even officially set up in our, our space back then, of, you know, of why the Tri-Valley, why not just sort of keep going and go down into Silicon Valley proper or the city or wherever, you know, the more traditional — especially at that time, more traditional startup hubs and you said to me then, like, you wanted to start a company where your future employees would be able to live and afford to live and you know, it was, it’s always a relative conversation. So we’re talking about, you know, at that time it was relative to Silicon Valley and still today, relative to Silicon Valley, this is  a good place to raise a family and be able to afford to buy a home and live another kind of life that you want.

Um, affordability is becoming a challenge here as well, but relative to the rest of the bay, that’s still the case. So I’ve just always thought that that was a, uh, phenomenal, I think, insight and, uh, and foresight on your part to recognize that the people who you were going to want to hire, these experienced engineers, folks who were, you know, maybe had families of their own, because of the demographics who were likely to come and join your company would want to be in a place like this.

Luis Dussan: Yeah. And for the most part that worked well, that plan worked well. We were able to steal folks (quote unquote) who wanted not to commute right to the Bay area, but liked living in the Tri-Valley area. Um, and, and that worked well. That, that actually, you know, I think, for the most part characterizes the first, maybe five, six years of the company.

Brandon Cardwell: Yeah. Okay. So. You know, you incubate with us for a little while, maybe 12, 18 months, something like that. I know we shut down our warehouse facility incubator and ended up moving downtown. That was like September, 2014 or so. And you moved over to Innovate Pleasanton, but that sort of transition of those early days of founding this company, you’ve got, you know, technical, technical breakthrough, or a combination of different technologies that you’re putting together at a time when I don’t, maybe you remember it, you were certainly closer to it.

I don’t remember autonomy being so present in the narrative around technology and around, you know, everyday life. Like we weren’t really talking about autonomous vehicles in mainstream applications at that time. And so how did you make that decision to make that bet? 

Luis Dussan: So let me, let me answer that by saying, first of all, to your comment about that, I don’t remember it wasn’t because I remember calling you and saying, I don’t see my category in here.

And what was your response? Your response was like, yeah, don’t worry about it. Just come. That’s fine

Brandon Cardwell: We have a lot of space. That was my comment. It was true.  

Luis Dussan: For me to remember that when you work in advanced programs, you’re looking at technology that’s several years before the commercial sector. Right? And I, you know, I’ve tried to answer this question to myself. For me, it, I already knew that things like the DARPA Grand Challenge, things like, autonomy, were starting to become possible because we, as this, group of intelligent people that worked on this stuff, there was enough body, there was enough of a body of work to say, Hey, you can start doing this now.

Right? And I want to give credit to DARPA’s Grand Challenge for really showing that, right? Like that was the Google X team, what became the Google X team,  what became the Uber team, what became, you name it. You know, Aurora, a lot of these companies were essentially folks that worked on the DARPA Grand Challenge.

You and I both know that. The DARPA Grand Challenge was basically the kluge of a bunch of LIDAR sensors: camera sensors, radar sensors, just duct-taped together. And then you just, you know, put software as kind of an afterthought with amazing compute power that would never sell. Right? So if you actually tried to commercialize, that would be like a $10B, $10M car, right?

That wasn’t ready — but the idea was enough for you to start working on it. And for me, I looked at that and I go, well, I mean, the first mistake is they’re not fusing together some sensors that need to be fused. There’s not a software definability in the sensor. So you need multiple sensors.

Even if you only use one sensor for one aspect of the road, as an example, and the other ones, for some other aspect, you have one that can kind of change around and do it. You’d solve not only that issue, but a lot of other corner cases that haven’t even come up. And just as a side note, I think a lot of the people today look at the autonomous problem as, okay —you know, your typical rectangular puzzle, right? Where you have four corners, a couple of edges, right? The edges are there, but the bulk of it is just the inside of that rectangle, right? Autonomous is not like that. It’s more like a puzzle that has a very irregular shape, where corner pieces and edge pieces are the majority of the problem, and the core is actually a very small percentage of it. And once I think you understand that you understand the need for adaptability, software-defined ability in the hardware, and it starts making things a lot easier to swallow to, to digest. So for me, I saw that early on from my experience working in missile defense systems, targeting systems, and how important it was to have that, because if you didn’t, it was just a crazy hard problem.

And I think that’s part of why maybe I was able to sort of see this coming. 

Brandon Cardwell: So how did you convince early investors and early employees that you were right about that problem set and that you had the solution to that? Like what, what does that experience you’re you had not been a founder before you were deeply technical by background, and you’re pitching your product and your company and yourself as a solution to this relatively, you know, commercially unknown problem space. So how does that happen? You know, you, maybe you can even like frame it in the sense of like how you got your first check in. 

Luis Dussan: That’s a great question. And I keep going back to that to try to find a good answer for that. I think there’s a couple of things.

Number one, LIDAR wasn’t new. It was starting to… Velodyne was there, there was the DARPA Grand Challenge. And so people were, you know, okay, you need LIDAR. Why do you need LIDAR? I don’t think people understood why you needed LIDAR. Right? I think, and we could talk a little bit about that later.

But I think one of my strengths is when I speak technically about a subject, I’m able to convey it in terms of most people can understand. That’s what I’ve been told. I’m sure other people might think differently, but that’s what I’ve been told. 

Brandon Cardwell: Okay. And just for uninformed listeners, tell us, what is LIDAR and why does it matter?

Luis Dussan: Sure. So, I think everybody’s familiar with radar, right? Radar, you send it an electromagnetic pulse out, it comes back and you get a return — a little bit about the return, which is called a signature, and where it is. Right? And as much as it has to do with elevation, and range or where it’s located in 3D space. Radar is very similar in that sense to LIDAR in that LIDAR does the same thing, except that the wavelength it uses is obviously a much smaller wavelength, which means higher resolution.

So you can do it with much higher resolution. And there’s two interesting things about radar and LIDAR with respect to other sensors like camera or an ultrasonic, for example, which is that they’re very deterministic. They actually go out and measure the properties they are trying to measure with good fidelity across a wide variety of, let’s say, lighting conditions or obscurants or things that could cause interference. Because of that, they, when you end up coding for an AI attribute, like lane, keeping whatever, come up with something, it, the math is always easier. And the algorithms are always easier with a deterministic sensor. They’re always much harder with a non-deterministic sensor because it’s an interpretation, and now that interpretation can be misinterpreted.

Then you have to count for that. And then you have to have 20 different conditions for like, when it could fail as opposed to maybe one or two where it could fail. And so that’s what LIDAR is, it’s like radar, but shorter pulses, typically shorter ranges for automotive. Well, That’s not necessarily true — automotive radar is the same range as LIDAR, but in the military, it’s a lot longer in radar. It is much more powerful. Okay. Okay. So having said that, why is it important?

And it’s important for the reason I just said. The one thing that things like LIDAR can do — and this is above radar and above cameras, is that way they detect an object.

It is a really good bet that that object is really there, right? It is not that way with radar, because with radar, everything is a mirror. And so there’s multiple echos, multiple bounces, multipath problems, and you have to unfold all those, and then remove it. And sometimes you remove something that’s true,  and sometimes you add something that’s true.

And so that’s a big issue with radar. Radar, remember, is designed for — there’s nothing in the sky except one plane, and I can see it. When you start going into a clutter-filled situation, that’s a little different. That’s tough, right? 

Whereas light doesn’t bounce from — not every material to a laser light  wavelength is a mirror. I mean, obviously a mirror is a mirror, but you know, you’re not a mirror. I’m not a mirror, that wall’s not a mirror, so it hits it once. And then really the energy dissipates. So the unfolding, this multi — becomes child’s play. It’s easy. Right?

But it’s also directed like the energies contained in a very small beam. So the energy that leaves the sensor is the energy that hits the object. And that’s really efficient in that case. So the determinism, the size of the object, the size of the sensor, because of the fact that the light’s wavelength’s so small, it can be relatively small, very small.

And the fact that it is not open to a lot of interpretation.

Look, at the end of the day, when you’re coding, you don’t want to sit here and have 30 corner cases for when it might not work. You want to really concentrate on what you do when you have the data that you know worked. And that’s just the problem with all the other sensors. Not LIDAR. It’s really deterministic.

Brandon Cardwell: Okay, great.

Luis Dussan: The other important thing about what I did was, you know, Jordan, you know, Ransom, you know, Barry, you’ve met him.I was able to know my limitations. Right. And, I was always big on doing what makes me happy so I can be the best at it. Right. 

And delegate, or find people that are partners that do the things you don’t really like, or you’re not really that good at, at, to begin with, and so getting the right people excited about the technology. That was a big part of it. And so that all came together. For example, when I chose to have people that were really good at presentation material present, and then I was really good at explaining the technical aspect of it. 

And I think the third aspect is investors were waiting to hear about it.

Brandon Cardwell: Yeah, right. That feels like a really concrete piece of advice to the aspiring founders out there in the world is, is know your limitations, know where your skill set starts to weaken, and the sort of broader landscape of what’s required to run a company and then go find really great people to fill in those roles so that everybody can sort of do their division of labor and specialize in that stuff.

‘Cause it’s really hard to be good at things that you don’t enjoy doing. Right. 

Luis Dussan: I would add one more thing. So, you know, I always tell this to my employees — that there are these general circles that you could describe somebody:

 You know, the big circles, everything you could possibly know. Right.

And there’s a, there’s a circle in there, which is the things you know that you’re pretty sure about that, right? 

And then there’s this other circle that nobody knows. So sometimes not you, right. That basically says these are the things you don’t even know that you don’t know, right? And, of course it’s another one of the things you know you don’t know.

So there’s three things: you know you know, things you don’t know but you know that, and then there’s the things you just don’t know that you don’t.That one is the dangerous one because you have no idea where you’re at. 

So for me, through the years of experience I had, I had a pretty good idea. And this is where I always say, like one of the important things about a secondary education and master’s and a PhD, is that it tells you how important it is to know the things that you don’t know.

Right? Like how dangerous it is to know that there are things out there you don’t understand — and if you make assumptions, you could be very wrong. Right? You’ve heard the same before, you know, the trick is that you know enough to think you’re right. But not enough to know you’re dead wrong. 

Brandon Cardwell: Right. Well, yeah. You know, enough to be dangerous. Right? Yeah. 

Luis Dussan: And so, I had a good idea of what I didn’t know what I didn’t know. What I didn’t know, fortunately for what I was trying to do, was small. And, and I think that’s got to do with a lot of experience. 

Brandon Cardwell: Well, and how much do you think being in the middle of a tightly networked group of people with a lot of varied domain expertise helps reduce that risk.

Because it seems right. If you’re, if you’re like, I’m going to talk to 10 people about my idea and those 10 people are going to be really like high-performing operators in a variety of different spaces. And some of them might be investors. Some might be subject matter experts in the field. Some might just be really good, you know, managers, um, and the broadest sense of like taking startup companies from like nothing to, you know, all the way through exit and that, that experience.

So I’m trying to, I have always felt, that my  assumption is that when you have a really tightly networked ecosystem of people, it’s a lot of what our Startup Tri-Valley work is based on, when you have a tightly networked ecosystem of people with different kinds of experience. But, you know, within the same kind of landscape of scaling startups, especially in these kinds of deep tech, life sciences, like complicated — there’s technical risk, there’s market risk.

Having lots of conversations with those people early on will help to surface those unknown unknowns that you’re talking about that are the real kind of black swan type of events that can just wipe you out, because you didn’t even see it. So it was that — did that experience happen for you like you’re the domain expert, obviously in the technical field, but you talked about, you know, Jordan Green, um, talked about, you know, obviously Ransom and then some of the other folks who you’ve connected with early on. 

Do you think that helped make sure that you de-risked some of those big unknown, um, kind of black swan events for your company? 

Luis Dussan: Yeah, I absolutely think that’s true. I mean, I think technically speaking, the early work, you could say that a lot. So first of all, I started the company in 2013, but I thought about the company in 2010, I thought about it in 2009. In fact, I just started scribbling designs for what I would do. And it changed over time because I was like, no, that’s not going to work, no that’s not going to work. And that was based on a lot of experience and a lot of seeing things that are not necessarily viewed by the general public and going, oh, that’s definitely not gonna work.

And every time I did one of those, oh, that’s definitely going to work. That’s an entire company potentially. That’s a startup that figures that out way later. So I, you know, that whole fail fast? Well, I failed fast. And one of my advantages was that I simulated a lot of it. Obviously. I didn’t even see that, but the simulation caught it.

So that’s number one, number two, just look at our business plan. Right? Think about when we went public, we, you know, I had a good team and I told you this before. I’m one of those founders who — I gave a lot of stock to a lot of people, because I wanted them to be very engaged in the company. Right? And I wanted them to be happy.

I wanted, when we went IPO, I wanted them to be like, that’s my company. Right. And so, you know, a great thing about that, Blair, Bob, Jordan, and the rest of the team over time — John Stockton, over time, you know, we started developing the business plan and it was — that business plan, I think, is just as important as the technology.  

Because, I mean, you may see there’s some companies out there who have announced wins, but they are not making any money off of it. Because the business plan sucks. Right? You have to have a way to make money out of it, right? You have to have a way to reward your investors. And the plan goes hand-in-hand with the technology.

And if you understand how you’re going to make money and you have good technology, I think that’s a win-win. But if you have one or the other, as you know, you’re not [you don’t]. So for me, a lot of the unknowns, like you mentioned, we’re in the business plan. Like, how am I going to make money off of that?

And think about LIDAR five years ago. How, like, are you going to sell it to them —oh, easy — you’re just going to sell it to the vehicle manufacturers and make money. Yeah. Oh yeah. Take me through that step. Yeah. How are you going to do that? Right. And, you know, you have to really iron it out, and we had a great team that could do that. 

Brandon Cardwell: So. All right. Let’s talk a little bit about this, the state of the industry, as you see it, obviously you don’t like this. Yeah. You have — I think there are a lot of folks who might listen to this who don’t have any expertise in LIDAR. They’ve heard about autonomy, and autonomy is an interesting one for me, just as an observer, because it sort of went from not being a part of at least, you know, my experience as a sort of mainstream, consumer of news, and even tech news. 

And then it was like, oh, we’re going to have driverless cars, like, tomorrow. Right? Very, very soon. 

And then it was like, the contrarian view became like, oh, well, never have, you know, quote-unquote level five autonomy.

And it’s just, there’s just no way to do it. I think it’s very difficult for people to make sense of that. So I’m curious as someone with such deep subject matter expertise, and then obviously a company in this space, what are those, what are the best early applications that you have seen or are seeing? What does it look like?

Luis Dussan: So, but when you say that in autonomy or in general or in automotive?

Brandon Cardwell: You pick. I guess if there are things outside of automotive that are interesting to talk about, which, you know, I think there probably are. Let’s um, I’d be interested to hear about that. I think for a lot of people, autonomy for them is vehicle-related, but, I don’t know, wherever you want to go with it.

Luis Dussan: Well, so let me just, I think I’d — let me tie the business plan back to this, because if you’re business plan is to go and sell automotive, ADAS (Advanced Driver Assist Systems)  is you know, a hundred million vehicles a year — and [if] you’re not prepared for that — you’re going to fail.

Brandon Cardwell: Prepared, meaning what?

Luis Dussan: You don’t understand how to make it, how to actually make money off of it.

Like, there are very slim margins there. Like you’re going after massive volume, right? You’re not going to sell, you know, 10, 15, 20 of them and make any money off of that. Right? You’ve got to prepare for the long haul and that long haul requires a partnership. And I think we were very smart about that.

And we said, look, we’re going for the cost basis and the high volume, as, not a tier one, but a tier two, where we would basically leverage our design experience and then we’d license the technology and then we’d have a partner doing that. We’d go for that same supply chain. And then we use it on the things we know, which are the lower-volume, higher-margin other markets.

Okay. And that I think was a very mature way of looking at it. And I think the street also looked and yeah. That actually does make sense, especially for a startup. Right. and so, you know, sort of back to your question, I think the important thing to realize was that you have to put together all that.

Brandon Cardwell: You’ve, you’ve prompted another question in my head. Um, so the, the second part of the question I think for me was, what does it look like going forward? Like what are the applications? And, yeah.

Luis Dussan: Okay. So, you know, that idea of going after the ADAS [advanced driver assist systems] market, which is a hundred million. Okay. I want to explain to you why that’s important. And I think you’ll appreciate this. There is no other market where you can introduce a technology, and after you introduce the technology and it gets adopted, it becomes really low-cost, really fast, and really robust.

And there’s a robust supply chain. So far. LIDAR naturally wants — anything with a laser is going to be expensive. Right? Like the most optimal system is some system without a laser, right. Lasers are expensive, but you can make them cost-effective. If you are going to mass manufacturing, then you have a good team and it does happen.

I mean, CD players .. just think of all the lasers that are cost-effective at this point. Right? So the ADAS market is really important to get that started. So I don’t think you’re going to see mass production without the ADAS market adopting. That’s number one.

Number two: There’s a lot of people that are going for LIDAR outside of the automotive market. They’re never going to hit those volumes, right? The cost basis and the volume. So, companies that have a play in ADAS plus a play somewhere else, I think are going to be very important. Now this is the reason why I’m saying that. Autonomy started as robo taxi. [People said,] Well, we’re going to do robo taxis tomorrow. We’ve solved everything. 

Right? Remember where that came from? That was a Velodyne system, which, we know now had no hope of ever getting to low cost. Right? It’s a spinning system. It was very low resolution. We realized now we needed higher resolution.

It was very mechanical and mechanical doesn’t get into high reliability very well. Right. It just doesn’t, it doesn’t work very well. And, and people were always telling me, Well, I mean, motors are mechanical and engines are mechanical and they have five-year life. Yeah. But you’re asking a very macro mechanical system to maintain an accuracy over its lifetime temperature, vibration shock of like .01 degree, that’s a different thing, right?

Brandon Cardwell:  Yeah. 

Luis Dussan: Um, so. What happened was at the beginning, people were like, oh, the blue sky, everything’s possible. 

Wow. Okay. Remember I told you about the puzzle piece, right? That was the industry going, It’s not like this, it’s more like this, and we’re not prepared for that. 

So let’s lower the subset of things we have to do under 35 miles an hour. Geo-fenced. Right? We can probably handle that, but we can’t handle all the other things yet. We’re not ready. Okay? All right. And so what happened was the robo-taxi industry took a step, and they kind of took a step to the right.

But the great thing about it was all those algorithms developed. They’re great for ADAS, yeah. And they’re better than what we have right now. And meaning that the advanced driver systems features that come out of that are — people really want safety. Like, well, that’s one of the things you and I want for our kids.

We want safety and we’ll pay for it. And that’s been proven over and over again. Safety was a great way to do it. Now it comes to the automotive manufacturers. Automotive manufacturers are governed by CEOs who almost make money not to make mistakes. And this industry is going through sort of a radical transformation.

Think about the cell phone back in 2007. You had the players that were in the cell phone market; they’re not there anymore. Right? It’s all new players. Right? And those players treat it as a different platform. And now they’re the ones that are doing it. And by the way, the data companies are really starting to take over that. Apple, which I would classify as a data company today, Google, right, Android and iOS. 

So you’re seeing the cars kind of do that. And the basic problem with OEMs is they don’t know how to monetize this, other than if we don’t do it, then somebody else is going to buy a car that’s not ours. And that’s great. That’s fear, but that’s not a way to monetize it.

That’s a way to just stay in the game. Right? And as long as there’s no pressure, you’re going to see that adoption kind of like, mmm. But now you’re starting to see the pressure. Tesla, they need to add more sensors.

I think that’s clear. I think everybody knows that, the only person that doesn’t know that probably is Elon. You need to add more sensors. 

Daimler also is pushing the limits and a couple of other people are trying to push the limit, and in those limits they said, Hey, guess what? A level two is great, but level three means that I can take my eyes off for 15 seconds.

And if I take my eyes off for 15 seconds, ‘cause what you can do in 15 seconds? You can watch TV. You can watch your texts. You can potentially look at email, right? And then you put your eyes back and then you’re fine, right? I’m sorry, not 15 minutes. I mean 15 seconds. It’s enough to just gaze for a little bit and go back.

Right? And they made the determination that if you go to level three, you could do that. But at level two, you can’t. And so that was the first time I saw it in a very measurable way. And they did it with two LIDARs, a bunch of cameras, radar. And then, you know, compute that was not really that expensive. And we can talk about some of the prices that OEMs expect in a little bit.

Um, but what it basically said is, Hey, we have a way to monetize LIDAR or advanced sensors, and this is the way we’re going to do it. We’re going to let people have a chance to read their email or look at movies, and then guess what —  the HMI —  we own it. So let’s see what else we can offer them. I think Tesla’s really good at doing that.

Yeah, I think they’re having some issues because they can’t, they shouldn’t be doing that. But other companies are starting to see that, so that adoption of LIDAR and that monetization of autonomy, they have to go hand-in-hand. They have to provide pressure. And I think you’re starting to see that over the next couple of years in a big way. Right now, notwithstanding the pandemic, notwithstanding the chip shortage, all that.

That’s going to play its course a little bit and we’ll see how that ends up going. 

Luis Dussan:  One of the things that we didn’t talk about, which I think we should spend some time on is the, the function that i-GATE for example, provided for me early on. Like, we sort of didn’t, you know, we talked about how I joined it, and we talked about how I left it, going on, but we didn’t really talk about what it did. And I think that’s…

Brandon Cardwell: By all means. 

Luis Dussan: Yeah. And you know, where did I meet Hitch? Where did I meet Jordan? Where did I meet the people that ended up becoming, you know, some of my best friends. Some of the people that I, you know, was [sic] able to, you know, longtime AEye family members, right? Yeah. It was all through the initial meetings I had with you at i-GATE.

Right. Hitch being one of them, and a lot of people know Hitch. 

Brandon Cardwell: He’s been a guest on the show. 

Luis Dussan: And then of course from Hitch, Jordan. Um, and then, you know, through those two, we met sort of everybody else. Um, and had I not had that. I don’t know where we would be. Right? So I think the connections are extremely important. Yeah.

Brandon Cardwell: Yeah, I mean, it’s such an interesting point, I’m glad you brought it up. I didn’t want to sort of force you into that conversation, but I’m glad you brought it up. Um, you said something to me when we were closing down that warehouse. And I remember this, because it stung for, you know, the seven years since you were like, I don’t know why you’re shutting this down.

And we were moving to downtown and we’re moving into this little, like, you know, the building that we’re moving into. And it was kind of, we’re switching more to like a coworking kind of opportunity. And, and you’re like, this seems like it works really well. Like the city pays for this warehouse where like, you know, people with technical backgrounds can come and like work on projects and try and turn them into companies like —

This has been great. What are you, why are you closing this? And the actual answer to the question was like, it made no money. That was the answer. And we moved into a space. It was like, all right, we’re downtown people will want to be there. And so we sort of, um, instead of occupying this sort of, you know, metaphorically speaking this like, vacant space, and providing this value where you couldn’t get it anywhere else, we made at least a misstep, if not a full-on mistake, which is like, okay, well, let’s go to a place where people already want to spend time, and we’ll open a space where they can like spend time with us, and then they’ll give us money. And that worked, we got to a point where we were actually like cashflow positive on that, but that really wasn’t the point, right?

Like the point of what we do and what we continue to do today through the incubator, which is now called Daybreak Labs, is, giving people like you, the runway that you need, and those connections that you’re talking about, um, to go from technical breakthrough and, you know, idea of a market to, okay, I’m going to build a full-fledged company around this.

And so ironically…so 7693 Longard Road was the address of that incubator. We just signed the lease for 7683 Southfront Road, which is literally across the street. I think I could throw a baseball from our new incubator and hit the old incubator. And that space is going to be — 

Luis Dussan: And what was the idea for that? What was the prompting that made you go back to that? 

Brandon Cardwell: For the new one?

COVID was a big part of it, and we were thinking about it ahead of time. Um, and COVID actually was more of like a reinforcing factor. The co-working space that we were running was shut down during COVID. And, um, all of those people who were working in the general-purpose office environment, like just worked from home or, you know, found or went to, you know, if there was a coffee shop open somewhere or they, they figured it out because you could do sales, marketing, software development, all that kind of stuff from pretty much anywhere.

It was the people who were working in the basement of that space that we  were occupying in downtown. They couldn’t take their biology project or their materials engineering project, for the most part, home to their garage. And so, you know, we, we knew that and we sensed that earlier than COVID, but it really reinforced that we needed to get back to those roots of providing a blank canvas for these like, technical innovators to come in and try to figure out if they had a, there there, to what they were working on. And we’d been hosting some of those companies anyway, kind of makeshift, in the space we were in. Um, and then we spent 15 months. So I went to my board and I said, Look, there are a couple of things going on here.

One is there are co-working spaces that have moved into the Tri-Valley and they’re providing that service. And we don’t need to be providing that service. We’re a government funded nonprofit organization. We shouldn’t be competing with the market. We should go into a space where the market’s not delivering a service that we think is essential to our core mission, which is like job creation, economic opportunity.

So I went to the board and I said, That’s happening. Also, I want to be in a situation where rent was not the primary driver, right? Like we’re a non-profit organization focused on economic development. We’re not a real estate play. It’s fine for us to pursue financial sustainability. That’s a good model, but we had, if you looked at the biggest successes that we had as an organization in terms of impacting the local economy, one, you guys are the biggest by far, but it was when we weren’t using ability to pay as the filter for who could come in and work with us, it was how likely is this to work. And if it does work, how important will it be?

And so I wanted to get back to that. And so the new space is 7,000 square feet. About a third of it is lab space, BSL1 and 2 lab space and instrument lab space. The rest of it is some office space, conference rooms, basically like what people need to be able to get some work done. Um, that should be ready mid to end of June, I think.

And we won’t have to use, we got our, our city and lab partners to commit to funding the opportunity so that we won’t have to, you know, be sort of taking money at the door for everybody who comes in. Now, we will have a for-rent piece of that, but we’re also partnering with Tri-Valley ventures and Greg Hitchen and company. So we have this residency program where if they’re funding a company that’s in the life sciences and deep tech space, we can provide no-cost facility space for that company for up to a year, and really try to give them that same runway that we were able to give to some of the companies in the early days.

So we’ve kind of come full circle as an organization. And, you know, really focusing on providing that essential, you know, lab R&D infrastructure at the early stages of the company. 

Luis Dussan: That’s interesting. And I think that’s, I always differentiate between hardware and software. And hardware is a lot harder to go to Starbucks with.

Right? And I think that would be so I’m glad that you said that, because that tells me like, if, oh, if I have a hardware idea, I have a place to start without having to spend a large sum of money that I don’t have. And so I like to hear that. And then of course, you know, I, I love the fact that you guys are still about the connections and, you know, cause a lot of entrepreneurs, especially if they’re like me, they’re not going to know about what they need right away.

Right. They’re like, I just got to get these patents filed. I just got to get this thing working and then everything else will just take — like, well you need to start thinking about some of those things.      

Brandon Cardwell: Absolutely. It’s those unknown unknowns you were talking about before. And I think what we’ve observed is we work mostly and have worked mostly with technical founders who are starting a company for the first time. And those people are deeply focused on reducing technical risk and achieving technical milestones. And the market component, like they know that’s the thing they need to work on, but it’s not always clear exactly how or what needs to happen first.

And so part of this partnership with Tri-Valley ventures, their GP and LP network are most of the experienced operators in the region who we would want to help pair technical founders with. Let’s get them involved, really early on. So they’re going to look at every deal that comes in, every applicant who comes in and then they’re not going to fund all of them, obviously.

Um, they may, you know, maybe it’s one in 10, I don’t know, but pairing that their network with the, the startups who are coming through and looking for opportunities to — and it might not be, you know, a CEO, maybe it’s an advisor, a board member, an angel investor, a technical expert, who knows? But increasing the efficiency of, of getting answers and increasing the efficiency of solving problems has to remain a key part of what we do.

And then the physical infrastructure of. You can come in and you don’t have to buy $20,000 worth of lab equipment and go lease a 2,000-square-foot space, which isn’t even available because the industrial market vacancy rate is like 2% and the Tri-Valley right now. So we can get people started and then spin them out into the cities throughout the Tri-Valley, as they hit that next stage of growth.

And they’ve got founders like you and companies like AEye, that they can follow in the footsteps of and say, Okay, this is how that gets done. And I can reach out to that founder. I can reach out to that investor, that board member. And, you know, figure out what my next step needs to be. 

Luis Dussan: Yeah, that sounds like a good method. A good plan. 

Brandon Cardwell: Yeah. Well, you inspired some of it by, you know, making me feel bad for seven years about shutting down that warehouse facility and really desperately wanting to get back to offering that kind of a resource base. 

Luis Dussan: It seemed like a good idea at the time. 

Brandon Cardwell: Well, it clearly now, in retrospect it was a good idea.

Luis Dussan: I mean, you going to —  

Brandon Cardwell: Oh, that, you know, I think it was just a lesson for me in remembering what you’re solving for. 

Luis Dussan: Maybe we got away from something and came back. 

Brandon Cardwell: It was like, you know, you, I think what we did at the time was, you know, fall victim to kind of short-termism, right. It’s like, all right, we need to get some money into this organization.

And, the best way to do that is to charge for something that we already know people want, but if it’s not directionally aligned with what you’re really hoping to achieve and what sort of core to your mission, then you don’t do yourself any favors long-term. 

Luis Dussan: So, yeah. And you might talk a little bit, like what was special about US-LADAR or AEye. I, mean, I would sort of unselfishly say there was nothing really special about me at that time.

Or AEye or US-LADAR at the time. I just think that, you know, market conditions have to be right. You have to have, well, at least somebody who understands their limitations. And I think that’s something that you can find in entrepreneurs — when they don’t, I think that’s an issue. But if that’s something you can come to understand, I don’t think that’s a large obstacle, but really it’s just, you know, sometimes entrepreneurs need to understand, they have great ideas. 

Brandon Cardwell: Yeah. 

Luis Dussan: Market isn’t ready for it. Right? Like I think I had a great idea, but I was also lucky in many senses that the market was ready for it. All right. And that’s a big deal.

Brandon Cardwell: Well, there’s always some element of timing and luck, right?

Like it’s, a significant portion of it, I think. But if you start with really talented people who are super-determined about the thing that they’re doing, and then you give them an environment where they have the time and the resources necessary to kind of push out to the contours of that idea and try and find fit, [and] then you can do something. And it’s not like we’re going to go through them. You know, it’s not like we’re going to pick winners because we are so good at picking winners. But if we create the environment where people can come in and they can do that iteration, and give them, um, the runway and the support network so that they can try to hit the timing, and maybe we can create a few lucky breaks for people, like introductions to Hitch. 

Luis Dussan: When the market is ready. Exactly. And then I would add one more thing for me. Remember. I Came in, uh, I also had two kids, three kids, you know, three kids, two little ones. Yeah. And that’s one of the things I’d like to dispel is a lot of founders think they have to be like, you know, single, or no kids.

Brandon Cardwell: Or 27 [years old].

Luis Dussan:  Got to not be true at this point, right? Yeah. Hopefully we can dispel that myth. 

Brandon Cardwell: I think that’s absolutely right. And demographically in our region, that’s really never been the case. I mean, I think I’ve worked with, you know, it’s been definitely in single digits, founders who were not, you know, family people.

Um, and some of what we’re trying to do is make sure that people who do have families and have those kinds of obligations. Don’t feel like they have to sort of mortgage their future to go and try something. Right. So we can lower that barrier and lower the burden for them and, uh, and let them go and test that idea.

I mean, the more people we get sort of playing in the pool, the more likely, and the more supportive we can be of that, the more likely we are to get some successes out of that. So, yeah, that’s absolutely right. I mean, I think one of the big advantages of the Tri-Valley I’ve said this before is, you know, we have serious founders building rational businesses.

And that comes to a certain extent with if not age, at least experience and being out in the world and seeing how things work. So, um, we see founders who are a little bit older and founders who have commitments and are invested in the community as a feature, not as something to be discouraged.

Luis Dussan: It should be. I mean, experience is — right, you’ve, you’ve already failed many times.

Right. And, there’s a lot less failures ahead when, once you finally get it right. So I, for me as I think I’ve mentioned this before, for me experience in my employees is extremely important. 

Brandon Cardwell: Yeah. So, well, that is an awesome place to leave it. Luis, thank you so much for coming on the show and hopefully we’ll have you back in the future.

Luis Dussan: Absolutely. Love it.