← T-Minus: Space-Cyber Briefing
T-Minus: Space-Cyber Briefing
Turning space data into intelligence with AI.
00:21:03
SynMax is taking qualitative space-based information, and turning it into quantitative information for their customers using AI.
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You're listening to the Cyberwire Network powered by N2K.
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Space based data gathering has been a growing area in the space industry over the last decade. We have an abundance of commercial earth observation companies, for example, gathering tons of data every day. And our guest says turning that data into intelligence is the next logical step. And how does AI fit into this? You knew we were going to ask, right? Well, we're about to find out. This is t minus deep space. I'm maria varmazes. Our guest is Eric Anderson, founder and CEO at synmax. Eric shared why he has jumped from financial market intelligence to space intelligence and what he foresees as the growing potential in the years to come.
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I'm Eric Anderson, I'm the CEO of synmax and one of the founders and I started my career in finance and in trading and and I worked for a hedge fund where essentially my job was as a quant to collect a lot of data and turn that into intelligence. Right. And that's a transformation I think a lot of people don't appreciate. In particular, I think that there has been a growing appreciation for it in the space industry. In the commercial space industry, we recognized that there is more data constantly being created out in the world, especially in commercial satellite industry, and there is a deficit of burying that data into a refined product that is intelligence. What's the difference? I think data holds potential and in the hands of a data scientist or in somebody who understands the data and the problem, that potential can be realized into a customer use case or a solution for a particular problem. Whereas intelligence is the solution. Right? Intelligence is. It is apparently clear that this is the answer to the problem I'm trying to solve. And so that's also Max does, really. And when I was at the fund, we started recognizing that commercial space industry was growing very quickly. And all of these innovative companies like Planet Labs and Blacksky and Satelogic and Umbra and I could go down and down the list that are a part of this new space economy. Launching assets into orbit and collecting data around the globe in a novel way that's not being fully used by the market. And it's certainly not turning into intelligence. And I think that the growing appreciation of data to intelligence is a maturing part of the space industry, because a lot of these companies originally might have discounted that idea. Right. If you go back to the ancient history pitch decks of when they were all raising money and starting up, you'll notice the theme is that they own the entire customer relationship, that they will build the satellite, they'll launch, they won't launch it, they'll have SpaceX launch it, they'll put it in orbit, and then the consumer of it, Right. I'm a farmer, I want a picture of my field. You know, I'm a railway company. I want pictures of my tracks, et cetera, et cetera. Those were the use cases they were thinking of. That makes a lot of logical sense. But I think the industry is starting to appreciate the specialty that is data science and the actual transformation of something into a data intelligence product. So we started Synmax and, you know, we were very early adopters of in particular, commercial satellite imagery. You know, we're great partners with Planet Labs, Black Sky, Ombra, all the ones I mentioned a minute ago, in purchasing their data and finding ways to combine it with a lot of other data sources and intelligence and turn it into a solution that customers can pay for, you know, particularly in the energy space where we do a lot of business, and in the maritime space where we have a product called Via, that is using this novel nascent commercial satellite imagery to monitor the oceans for vessel activity. And this has been a journey of about four years now. And in that time, I think we've found that the correct strategy is to be data agnostic. Right. And that doesn't mean that we don't appreciate that every data source has its nuances that value can be extracted out of, but it is a recognition that the best customer answer is going to come from intelligence fusion, not just from a single data source being Refined into something I was talking about, you know, before we hit record. It's kind of. It's not black and white. You're not, you know, data agnostic or not data agnostic. There's a progression. And part of that is that there are some sensors that are unique enough, right, that you have to build to their uniqueness. But being data source agnostic means that you're not building for the present state of the system, you're building for the future state of the system. And we know that there is a prolific amount of additional investment in the satellite industry. And so we build our system so that they are flexible enough that they can take advantage of the future state of the system when new sensor sets come online, but they're still specialized enough that they can take advantage of the uniqueness of each individual data point.
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I remember two years ago thereabouts, I was talking to someone about the idea of the future in the space industry really is companies like yours making use of the incredible volume of data that a lot of these Earth observation companies, for example, are able to produce and making sense of it in a way that's useful for people. However, the challenge was how do you parse all that? Given, as you just said, these systems are also different. And this, to me, feels like a. I imagine AI comes into play here.
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You guessed correctly. AI does come into play. I mean, we're so lucky that these are very new tools, right? In the grand scheme of things, I don't think anybody's impressed by a covenant anymore in an object detector. They were maybe 10 years ago when that stuff was novel. And now as AI's progressive, we're impressed now with applications of LLMs. But AI as a data science tool is completely unique because it is a way to reliably take qualitative information and turn it into quantitative information. And at the end of the day, what data science is really good at is making inferences in quantitative information. And satellite pictures are pictures, they're qualitative. That's a picture of a house, and that's a picture of a boat, and that's a picture of a car. Right? And AI has made a lot of progress in bridging the gap. So, you know, satellites have been around a lot longer than recent AI. And the traditional way the governments have done this was with imagery analysts. And they still do to a large part. Whereas the automation now exists for us to be able to leverage those human beings to get. Go deeper into the intelligence picture. Right. It is a better configuration for us to have people looking at the outputs of object detectors and LLM inference into images than it is to have manually looking at the pictures and tack it themselves.
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Current capabilities versus five years from now. Where do you see things going?
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Yeah, if we're talking about Earth observation, a lot of it is going to Edge Compute, and I think that that is a function of a lack of bandwidth. Right? So I've always thought that Edge compute and bandwidth are kind of interchangeable with each other. It doesn't make sense to run a GPU in outer space, right? It makes a lot more sense to run it on the ground. The reason we do it in outer space is because we don't have the bandwidth to be able to bring the data down quickly enough so the GPU can do a lot of the heavy lifting and parsing and do the first refinement on it. So then we do have the bandwidth to break it down in something closer to real time. Right? I've heard a lot of investment on the Earth observation side, and this is all public knowledge, right? In Edge computer, I've heard a lot less about potential investment in bandwidth, but it seems to me that either case could end up being the future state. If we can bring down in real time high bandwidth satellite images to the ground, it makes sense for us to run them in the data centers down here and do this kind of analysis. If that is not going to happen and nobody's going to make that investment, then Edge Compute seems like the future. But the end result is the same to the customer.
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We will be right back.
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And for for synmax. I'm curious also about where you guys are going in the next few years. Also because I mean, you're working especially you said energy and maritime. Are there other markets that also interest you?
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Oh, absolutely. I mean, I like to say that we have, you know, a thousand different product ideas and we have the capacity to run two or three of them.
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That's always the challenges and is the prioritization.
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Yeah. So it becomes strategic decision about how you scale and what choices you make to do that. And you know, in the early days with the tool set that was available, it's okay, well, you know, what is proven, what do we think the total expected value is? And it's a very poring, almost accounting exercise about how much risk you want to take for potential reward. I mean, there's still definitely room for innovation in it in that, you know, the market is not efficient in the application of different data sets and sensors to solve different types of problems. And I think, you know, Synmax has been a leader in the way that we have approached a lot of these problems in applying sensors in ways that haven't been done before. But the real, I guess, path forward from where we are right now in my mind is the application of Agentix to data science. Right. It's that same qualitative to quantitative exercise. But Agentix can now do this at incredible scale downstream of the models that are, you know, doing the actual interpretation on the images. I don't think anybody has solved this problem yet. But AI applied in the right structure should be able to further leverage analysis so that we can go even further up the stack of value add and be performing base level analysis. Right. And then delivering that base level analysis to human beings for final interpretation. And we are investing very heavily in that.
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Interesting. Okay, zooming out a little bit. What are you most excited about for developments within the space industry broadly?
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Yeah, so I'm really fascinated by the space industry's move beyond low Earth orbit. I think there's a proven business model right now launching satellites and sensors into low Earth orbit and selling the data as a business. And it's a great business to be in. But you know, what's the next step going to be beyond that? You know, there have been ideas that have been floated around, you know, everything from asteroid mining to, you know, a private space station in space to I've even heard, you know, people building data centers in space. And I'm very interested to see what value cases prove themselves out because I don't think this industry with the specialties that they built deserves to be restricted to low Earth orbit. You know, we have brilliant engineers working for these companies. And you know, designing systems and solutions that are extremely innovative. It is a shame that all the business seems to be happening in low Earth orbit right now.
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And I love the way you phrase that, by the way. Can I just say, it doesn't deserve to be restricted to low Earth orbit. That is a really interesting way of putting that. I love that you're saying that.
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I mean, it's a lot of human intelligence and very qualified people solving problems that under different conditions could be much bigger and produce much more value than this. But somebody has to take the risk and try to prove out the first value case and then others can follow. So if it is asteroid mining, which I think would be freaking cool, right? But also probably not a good business model right now. I don't know, maybe I'm wrong. I hope somebody thinks I'm wrong and tries to prove out these kind of cases. Then we can take all of this work that has been done in low Earth orbit and all these problems that have been solved and apply them to things that are producing a lot more value for the world.
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And that will be so fascinating. I know for me, orbital data centers is something I am very interested in seeing progress. But also I'm very curious about the business case for that and I really hope it bears out.
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I'm interested in the business case too.
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And the physics of it too, to be honest about that. But if it ends up working out, that will be transformative. But I think it will remain to be seen. But I'm hopeful. I'm very hopeful.
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Yeah, no, I've talked to people who are very involved in that business and it comes back to my earlier comment about the trade off between bandwidth and edge compute. And to me it just always seems to make more sense to bring it down to the Earth where you have economies of scale and you don't have all the problems of space. But maybe the bandwidth problem is more difficult than I'm realizing. And it actually makes sense to move significant edge compute into orbit.
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But that won't be easy either, certainly. So, yeah, that's.
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They're both two really hard problems.
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They certainly are. But people are. People are pretty smart. So I have a lot of hope. I like humans. Humanity often surprises me in good ways. So I've often been delighted by what people have figured out. So I.
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We don't get enough credit. Thanks for saying that.
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I.
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You know what?
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Human's pretty nice. I appreciate that. Eric, this has been a lot of fun talking with you. And I want to make sure that I give you the last Word. If there's anything you want to leave our audience with, anything at all, the floor is yours.
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A lot of the podcasts I've been on in the past have been like business focused podcasts. This is the first one that's really a space based focused podcast. So I'd like to change my standard canned advice and just say that there's a lot of, in my world, technology, I think kind of doom and gloom about AI and a lot of stories that I think would make a really bad Netflix movie about AI taking all the jobs and everybody's impoverished and just a few people control the AI and they mop up all the value of the world from themselves. Right. And I think that is extremely unlikely and unnecessarily causing people to have anxiety about it. Like I positioned all my answers before, AI is a leverage tool, not unlike any other leverage tool that we've had since the beginning of the Industrial Revolution, where in every case it is simply a mechanism by which people are able to create more value. And does this mean that we're going to, at some point, say we've created enough value for the world, we'll all stop now and have AI do it and we're going to have some kind of nightmare scenario? No, it means that we're going to be able to make more value for everyone in the world and we're going to lift more people out of poverty and we're going to grow GDP continually and continually and be able to have a better life for ourselves. And I think the same thing is true. I think the biggest risk is that if people are resistant to these new technologies in a misguided way, right, they are going to miss out on their opportunity to do something great for the world. I mean, ChatGPT dropped three, four years ago, right. And everybody was trying to figure out what to do with it. And it is just continually gotten better and we've got more companies investing in it and we're seeing all of this capability emerge. And it is one of the most exciting times, honestly, in my life, seeing this new disruptive technology come out and the opportunity is there not to be afraid of it, right, but to be the one who thinks about a novel application of it and a way to produce more value with it. And so if I'm going to leave a technical audience with any kind of advice, and I know it's not strictly space based advice, but I would say that you have to embrace disruptions. Because when a disruption occurs, you only have two choices. Are you going to be disrupted or disruptor. And think about it from the perspective of I now have the tools to be able to do a lot more than I could have done previously and that's a good thing.
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These are very wise words, Eric. Thank you. I greatly appreciate it and thank you so much for your time today. It's been a really fun chat.
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Thank you. Thanks for having me on. Foreign.
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That's T minus Deep Space brought to you by N2K CyberWire we would love to know what you think of our podcast. Your feedback ensures we deliver the insights that keep you a step ahead in the rapidly changing space industry. If you like the show, please share a rating and review in your podcast app or you can send an email to spacen2k.com we are proud that N2K CyberWire is part of the daily routine of the most influential leaders and operators in the public and private sector. From the Fortune 500 to many of the world's preeminent intelligence and law enforcement agencies, N2K helps space and cybersecurity professionals grow, learn and stay informed. As the nexus for discovery and connection, we bring you the people, the technology and the ideas shaping the future of secure innovation. Learn how@n2k.com N2K Senior Producer is Alice Carruse. Our producer is Liz Stokes. We are mixed by Elliot Peltzman and Trey Hester with original music by Elliot Peltzman. Our Executive producer is Jennifer Ivan. Peter Kilby is our publisher and I am your host, Maria Varmazes. Thank you for listening. We'll see you next time.
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SA.
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Foreign.
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