When Pixels Become the Priority

Time Markers

00:21 – Introduction

00:35 – In terms of 30 centimetre resolution, what are we talking about?

01:44 – A discussion on how an image can really make make a difference in the geopolitical landscape

03:17 – This level of detail seems almost a paradigm shift in terms of the nature of understanding who we are

5:18 – What does that look like from business perspective, but also from, like, a more holistic perspective in terms of we’re going from this flat world to this 3D world in terms of how we look at things?

07:00 – How do you scale? How do you automate?

09:34 – How do policy makers and corporate decision makers make decisions when speed is such of the essence?

12:10 –  How does quantum technologies fit into the Maxar equation?

14:47 – How do you think about privacy with the state of technology?

16:44 – A personal question, people talk about the 1960’s as the heyday of space, but aren’t we just at the inception of where we’re going?

20:00 – Space Takes with our Co-Hosts David and Mike: A bad week in space

24:54 – Launch infrastructure issues

28:53 – What’s happening at the Satellite 2025 conference

Transcript – Dan Smoot Conversation

David Ariosto – Dan, it is good to see you again. I want to get into this interview, and like the most, let me start that again. Sorry, Dan, it’s good to see you again. I want to just get right into it in terms of what Max our intelligence does and sort of the capability behind it. I mean, first of all, we’re talking about just an enormous amount of geospatial intelligence that’s used by US governments, particularly for national security purposes. But security purposes. But I kind of want to get into just like, the precise nature of how all this works. And sort of, you’ve mentioned in the past, in past speaking engagements, this sort of 30 centimeter resolution, in terms of, like, how each pixel corresponds to, like a real world area of what satellites and sensors are capturing. And my sense is this is like, about the size of a piece of paper. Is that essentially what we’re talking about here? Is that, right?

Dan Smoot – It is. And by the way, David, it’s great to connect with you as well, again, always in conversations. But yeah, when you think about 30 centimeter capabilities, and what we talk about from a geospatial perspective, it is really looking at the swath of piece of paper. And one of the ways, I think about too, is if we’re taking an image from maybe an airport, it’s literally being able to see the numbers on a tail fin of an airplane, but you’re also covering an area that might be the size of a you know, to get that imagery of size of a large parking lot. So it’s really the exquisite nature to be able to capture that detail, versus just getting a large area of imagery that kind of gives you roads and and buildings and so forth. We’re actually getting down to that really exquisite level to give you really detailed information of maybe what the object is on the ground.

David Ariosto – And this is, this has played, I mean, your company has played, sort of a key role, crucial role, in terms of the geopolitical landscape. I mean, remember back in 2022 you know there was, there was Maxar satellite images that were showing up. They were showing up, they were showing sort of the positioning of Russian military equipment that was sort of building up on the Ukrainian border. There was imagery of Chinese weapon sites. So, like, you know what a difference an image can make? It just sort of like changes the math in terms of the information that operators are using.

Dan Smoot – It absolutely does. And it’s not just about the imagery more it’s now about how do you actually coalesce that data, to actually be able to bring out differentiations? What people are really interested is the information on the ground, but also what’s changing. So it’s not just about that one image. It’s about the ability to have multiple revisits into an area now, to be able to give people and the analyst what’s really changing on the ground and what are the objects that are moving around? So by having that exquisite nature that you referred to, we actually can bring more intelligence to everything, by the way, from definitely on a defense and Intel perspective, but also from a civilian perspective, I’ll give you a great example of that was the detailed information we provided during the Palisades fires in LA that really helped first responders really think about movement of what was going on in a natural disaster in almost near real time. But it wasn’t just about taking that image that kind of gives you that stark reality of, oh my God, look what the devastation did. It also gave people reality like, where’s it moving to? So is being able to do that exquisite detail with movement.

David Ariosto – I mean, I think that’s seemingly sort of core part of your business, where, I mean change is the only constant, sort of the old adage. But I mean anything from just like the slightest adjustments and enemy troop movements, to a maritime perspective, from like shipping fluctuations, or even just in terms of vegetation, in terms of, you know, where the Amazon is at. It’s just, it’s sort of, I think what I find most fascinating about this is that it starts to paint this picture of who we are as a species, as a civilization, both in terms of the security landscape that they clearly, you know, Maxar has been at the vanguard of but. Yeah, but also just in a bigger scope of how we’re, like, almost looking at ourselves like you might, like, look on an ant colony from from above, in a way that you know, with this, just this, this level of detail that I don’t know, it seems almost from a paradigm shifting in terms of the nature of, like, understanding who we are.

Dan Smoot – I’d agree with that. And I think that you said something that’s really important is we do live in a world that is ever shifting right now. You’re seeing it from the geopolitical perspective. You’re seeing it from, you know, unfortunate and adversarial perspective. And being able to see that that ant farm form in different ways is critically important. And the way that we really start to think about it is that, you know, the we talked about this digital twin of the world, right, and understanding in a digital real time, but where the pressure in the marketplace is going to and where the, you know, our both our US government and the international governments really care about is really understanding the dynamics of that changing world and how they can make rapid decision making around that what used to be, you know, foundational, and give people weeks and months to be able to kind of assess information they’re now caring about, like, within hours, and in some places they’re carrying within, you know, maybe a 90 minute time frame to make, you know, critical decision making. So that’s where I think that you’re seeing this, this, this compilation of data and and and where the geospatial intelligence really starts to drive that kind of decision making on the ground.

David Ariosto – Well, let’s talk about that. Let’s talk about the corporate environmental because, because you’ve operated for for such a long time in classified environments, but there’s such a bigger, bigger commercial environment now than we’ve ever had. I mean, just you’re starting to see companies that are sort of acting akin to space companies in a way that we just never would associate with space companies, right? I mean, like, commercial real retailers, like knowing the parking patterns of the rivals during commercial holiday seasons to kind of gain a some sort of competitive advantage. So, so, like, what does that look like from business perspective, but also from, like, a more holistic perspective in terms of we’re going from this flat world to this 3d world in terms of how we look at things.

Dan Smoot – Oh absolutely, by the way, 3D is, is absolutely where everything’s moving to. But think about the rapid change in 3D and the ability to do it. You have to do it almost from space, because trying to get that information on a low level kind of ingest is takes forever, but you can actually do it very effectively if you have the right resolution and doing things for space. Because why is this important? Is if you think about the consumer, or you think about an individual, they’re really looking about their experience they’re about to have in their interaction. So think about, you know, the mapping companies that are out there, they’re trying to give a differentiated experience to their consumers. Well, they have to be able to provide that information at a kind of a rapid pace now, and that’s just the world of which we live in. Everything from people maybe do mapping on watches, golf courses, all those things come from the same kind of dynamic, and it is all being done in people don’t realize just how you do planning and stuff around elevation, you know, is really important. 2d flat maps don’t show that, but these are the things that we’re actually seeing on a day to day basis that just the average user needs to understand today.

David Ariosto – Well, let’s talk about that. Let’s talk about speed. Because we’re not talking only about speed. We’re talking about volume here, right? Because you’ve got, you’re kind of harmonizing a lot of different data points here from like radar systems and drone video and, of course, satellites and all of this is sort of like coalescing in this what 20 years ago might seem like just an overwhelming information paralysis in terms of just in terms of the sheer processing data, but in this algorithmically fueled world, things are very, very different. So how do you scale? How do you automate? How do you kind of make sense of these so that the decision makers, not only in the corporate space but national security space, can operate in real time.

Dan Smoot – Yeah, I think the compute question is a big question. And actually, I bring the data down. Some of the things that we’re always thinking about is, how do you actually bring that information to faster processing? And a lot of people think about, oh, it’s just about the imagery and and getting it down. It’s actually about, where do you actually compute the processing of that imagery to really get that information that’s required? Things that we debate all the time in the marketplace, especially from a commercial perspective, is, do you send sensors up that have compute capabilities, or do you use more compute capabilities on the ground? And you start talking about quantum computing and large language models that…

David Ariosto – you’re talking about, sort of like processing in orbit.

Dan Smoot – There’s been the thoughts of processing in the orbit. Now my fundamental belief in working with my engineering teams is the rapid pace of the processing capabilities. If you look at where we’ve gone from large language models processing over the last couple of years, the stuff that you’re seeing come from Nvidia and actually in the marketplace. Now, you know it’s rapidly evolving that I believe that you just need to bring the information closer to how it is downlinked from the satellite and process it there. And so you’re seeing these us moving closer and closer to that processing capability. But there are companies that do it. Really well too. So we have to understand our space and role. So we look at companies like AWS and Microsoft and others that actually have these large compute capabilities, and how do you partner with them to make sure that you’re actually bringing the right solutions together? Because we do bring multi sources of data. Now we’re very prideful as a industry leader, that we can actually use pure information to help us actually solve problems. And that probably didn’t exist a couple years ago. Everybody was trying to solve their little problems. Sure, you look at ones we’re trying to solve, like, maybe we’re trying to monitor 200 sites at a time. Well, we got to be able to bring that information from multi sensors now and be able to compute that and then bring that to, you know, to the customer.

David Ariosto – But that to me, that is, that’s the real question, right? Because you’re operating in new speeds, you’re operating in just drastically different volumes of data. You’re working across partnerships. You’re working across borders. I mean, borders in themselves are sort of ill defined to some extent, like once you get up at a certain, certain altitude, that is true, but, but how do you how do policy makers and corporate decision makers make decisions when speed is such of the essence in in a way that is, it’s almost getting to the point where it’s it’s maybe beyond the scope of human operators in many capacities. And I get it in the sense that you know, a lot of this data is being since the thought synthesized and automated in a way that is making is taking advantage of these AI fuel algorithms, but at some point you have to have a human in the loop here. And is there going to be a sort of a lag there, in terms of just the operational tempo that’s that’s required, to the point where we start outsourcing even some of those decisions?

Dan Smoot – Yeah, I think that’s one of the biggest questions that we’re all facing in the industry today. And I was actually talking to a major colleague of a peer of ours who’s got large footprint as well. And we were actually talking about the policy challenges. It’s one thing to be able to produce information and get them into certain people’s hands. It’s actually, how do you actually how do you actually provide the information in and deal with that kind of, that last mile we call of decision making. There has to be a human element when it comes to certain types of decision making, especially when you’re talking about defense and Intel. And I think that it’s really trying to take the speed out in regards to having multiple people have to touch the information to glean what that change was, or what that object is. But now that we can produce a little faster, we can actually put it into the hands of the decision maker, who can actually do something a little bit faster. We are still challenged with technology moving a little bit faster than sometimes our processes and policies, and especially when you start talking at the government level, and I think that that’s where we start doing, you know, meeting with them to see how we can actually shift and change how commercial and or the industry, can help speed up what might be really important a couple years from now, if there’s an adversarial issue. And so that this is kind of change. This is that constant balance between being a commercial provider and supplying to the government. I think that this is our responsibility in the commercial environment to make sure that we can really validate what we’re doing, to make sure we can put it into the right decision maker. But there is always going to have to be a human decision maker in these practices.

David Ariosto – You know, we talked about some of that new technology coming online. I’d be remiss if I didn’t mention sort of the new developments with regard to quantum technologies, and particularly when it comes to quantum sensing, is sort of this. It’s sort of this. We’re having this embryonic stage of all this. But you know, for those who don’t know, it’s sort of this advanced sensor technology that kind of, it kind of vastly improves the accuracy of how we measure and navigate and study and explore and like everything with the world around is down to sort of the well using essentially changes in motion and like electric and magnetic fields. But it seems like this has the potential to impact everything from air traffic control to even underground exploration of mineral resources. So I guess my question is like, how does Max art begin to consider this and look at some of these frontier technologies as you try to stay committed in the landscape, but also something that, something that has vast geopolitical implications as well.

Dan Smoot – Yeah, and I think that that’s one thing. I think your last statement is one of the ones that we have to always take into consideration when we’re building solutions, is, what are the geopolitical implications of all these decisions, but you have to constantly be looking at the advancements are going on. You talk about quantum sensing, quantum compute, and all the different elements around those type of advancements. If there is a way to improve a sensor, if there’s a way to improve the processing of information, if there’s a way to change the dynamic of which we can monitor site or location, we have to take it very seriously. One of the things I think is important for commercial is to be able to look at how we can ingest those type of capabilities. Now the challenge with geospatial information and building satellites is it happens in time. It’s not something that we can actually build an application turn around and produce. And having space in 30 days, our capabilities often take a couple of years in the physics of how we actually do certain things. But it doesn’t mean we shouldn’t be building that into our roadmap of how we modify and staying up on top of that. That’s why I was talking about just the compute side. If you think about it, by the time we think about Compute and we get it up in orbit. It’s three years too late, or two years too late, you know. So that’s where maybe you want to do the compute, down on the ground, where that advancement is going to be happening in rapid rate. And how do you bring in? So you take that from quantum sensing. It’s the same kind of thought process, which is, what are the things you can do to modernize, maybe in certain areas, in advance your information flow, versus what you’re going to have to maybe, you know, build into your roadmap in the future. And that’s, that’s a fine balance when you’re running a technology company, about how to incorporate that, because if you’re just chasing that future, you may never get your solution up either.

David Ariosto – I think, I think also in terms of running a technology company, I want to get into a little bit of your background there, but, but this is a question I think all tech leaders really have is like, how do you think about privacy? You know, when you have all these different systems that have this incredible capacity, you know, there are inevitably questions about safeguarding people from unwanted surveillance. And, you know, in many cases, I’m referring to commercial surveillance, but not just and you know, in that sense, like, is this something that you you worry about, or, you know, think about in terms of safeguards. I mean, how do you approach that?

Dan Smoot – Absolutely, it’s actually a corporal value of our company when we think about how we actually display imagery and so forth, you know, we, yes, we do sell imagery to multiple nations, and we do mostly around the you know, we actually do the US, government and its allies and enterprise companies that are based in certain locations. You know, we do have kind of areas we don’t sell to. We have people who don’t sell to. And the other thing we do think about is those is that privacy 30 centimeters gives you a capability to see certain things, but it also doesn’t give you capability see a lot some detail that we just it wouldn’t be appropriate for us. And there are also bounds in our licenses that I think that the governments, and I say governments all have that give you the limitation of what you should be monitoring for modern days, foundational mapping, or certain types of mission team. And then there’s things that you’re not licensed to go do, and you have to stay within those parameters, and we lift those because the credibility of our company. Think about it, if we mismanage that we’re a commercial company, it could actually derail what we do. And, you know, we’re trying to build a healthy, profitable financial business to be able to solve these problems for these different entities. If you cross that boundary, you cross that trust, and if you cross that trust, you will lose all that good will that you’ve built up, you know, for those types of things that we were very proud of.

David Ariosto – You mentioned that 30 centimeters that I just sort of make that’s publicly available. I just, I do, I do wonder in the back of my head, how much more granular does this get in terms of the, you know, the more classified realms of what we’re talking about here. It’s not, it’s not a question for you to answer, obviously, but, but it’s, it’s one that I’m sure a lot of people are curious about. All right, last question, this is, this is more of a sort of a personal question in terms of your history here. I mean, you were a tech guy in these early stages, and I also understand that you were kind of a big fan of the shuttle program, and, you know, so that seems to naturally coalesce in terms of what you’re doing now. And it just, it’s interesting to me in the sense that a lot of people that I talk to always, especially in aerospace, say, you know, you know, I missed it. 1960s we were the heyday of a space era. And, I mean, speak to that, that it seems like we’re just at the at the inception of where we’re going.

Dan Smoot – Well, I think so. I think it’s, you know, look, I’ve been very, very blessed in my career to work with some very disruptive companies, as with a company that disrupted the internet and really changed the way that commerce is done. And that was, I was there in that heyday of when all that was going on. I was, you know, I saw the virtualization of data centers and the expand. Or think about the mass reduction in the size of data centers because some technology as a part of and then, of course, disruption of software. So seeing all these big transformations was, you know, somebody I’m really blessed with, when I was approached about Maxar and truly trying to understand it, and realized that this was a data play, yes, we build probably the most exquisite capabilities to sense the world we do. We can, like I said, we can see the tail fin airplane. We can actually see the crosswalk in the road. We can see, you know, all the different dynamics that are, you know, critical for information. But it was the large data and the what you can do with that data to actually solve major missions that was really inspiring to me, and we are at the beginning of that, not the end of that journey. We’re just the beginning of that journey. Multiple sensors, seeing that rapid change, putting information into, you know, the water fighters, hand all the way to, you know, a civilian working as a first responder. You know, the mass implications of it, doing methane alerts, you know, monitoring pipe. And oil wells. And, I mean, all the different, you know, things that we can do in real time is a very disruptive thing. So yes, I’ve always been fascinated by space. I mean, it’s, you know, who wasn’t I grew up in the the shuttle era, and, you know, grew up watching the launches, and, you know, seeing all the different things and but now seeing how it can be applied to some of the disruptive markets I’ve gotten to participate in is is just really fascinating to me. And the amazing thing is, is when we keep releasing some of our new, newer solutions, the adoption and the appetite is huge, because the fact we’re moving from sensing the world to actually how we actually show change and how we actually show differentiation and speed to solve problems now on a human level, and I think that that’s where it’s really just a really exciting time to be here. I really do think we’re on the forefront of the journey of what space can actually offer.

David Ariosto – That seems like a good place to leave it. Dan Smoot, thanks so much for joining us. We’ll look forward to seeing what you’re up to.

Dan Smoot – Oh, thank you. Love to join today. Appreciate time.