00:14:49 · Molly O'Shea
[00:14:49] S0: To walk through the satellites that you produce, you produce a handful and they're all called different birds. I know we talked about this on the tour, but could you walk through the different use cases or the specs for each one of them starting with dove?
00:15:03 · Will Marshall
[00:15:03] S1: Yeah. So the doves are our mainstay scan. That's the thing that no one else has on the planet, the daily scan of the earth. They cover all the earth landmass, about 200,000,000 square kilometers. So more than the landmass of the earth, they cover a bunch of ocean territory as well in eight spectral bands at three meter resolution. Then we have our pelicans, which are our highest resolution satellites, and those ones, are imaged in particular tasks locations that our customers ask for. So one is automatically scanning. The other one you say, Hey, take a picture of here, here, here. And then we can do that. The most unique aspect of that is that we're building up to a fleet that has much more revisit than anyone else and faster timeliness. So if you say, our goal is if you say, hey, I want a picture of Tahiti, you can get a picture of Tahiti. You can make the request, get the image back and analyzed in thirty minutes, no matter where it is on the planet. And then we have our Tanager spacecraft, which are hyperspectral satellites. So instead of having three colors like our eye, these have four twenty color bands that enable you to sort of get a fingerprint of what you see on the Earth. It's basically 400 different images for every point on the earth's land mass that you're imaging and with really narrow spectral bands. And that what that enables you to see is not just that that's blue or green. There's this type of blue or green such that you can identify tree species, crop species. So it's useful for ag and biodiversity and monitoring, land, but it's also, good for defense because you can see camouflage and the distinction between camouflage and a real vehicle. It's good for emissions and pollution so we can detect, methane pollutants around the world. So if there's a gas leak, can literally see the gas. Even though methane gas is colorless, We can see it because in this spectral band it sticks out like a sore thumb. So we can detect those gas leaks and help people tell operators, hey, you've got a gas leak and then they can turn it off. That's good for the planet and it's good for them. Saves them money. So basically different kinds of satellites that do all these different things. They're all about collecting better information to help people make better decisions and actions.
00:17:24 · Molly O'Shea
[00:17:24] S0: And to the point of being in San Francisco, we're moving into the intelligence era. You guys are in beta with your AI app. So what are you doing in AI and how does that change?
00:17:37 · Will Marshall
[00:17:37] S1: Yeah, well, I mean, what this enables is an explosion of the number of people that can get value out of data. So I used to work at NASA. I know those guys really well that use our data there. It is amazing what they do, but that's because they've got a thousand people that know how to analyze satellite data. That's great for them, but that farmer in Kansas or the journalist in Kentucky, what the heck are they going to do with 4,000,047 megapixel images every day? They don't know how to deal with that, right? So AI is coming along and is like, you could just ask questions and get answers. That is going to totally explode the number of users. So, you know, I was saying how satellites are going from like a desktop or mainframe to desktop is what we've done on the hardware side. This is like the explosion of the number of people that could get value out of it. It's like giving people a desktop with no software on it and say, All right, off you go. One in a thousand people can get value out of it. So now you've got a basic operating system that anyone can use. Now suddenly that computer is useful to everyone, right? Basically. And that's what we see today. So space hasn't gone through that transition yet. And I think AI is the thing that opens it up for everyone else. So not just the big, country. So I think it's actually going help with a lot of defense and intelligence because it can help monitor large areas for threats and so on. But even more, it's going to explode the commercial applications. It's going to explode all the applications in civil government. So many things could be benefited. Firefighters trying to stop and respond to fires, farmers, counties trying to just stop illegal activity of whatever people that don't have permits for swimming pools. Mean, there's just bazillions of use cases of our satellite data in principle, but the AI enables it to have value in practice to them.
00:19:41 · Molly O'Shea, Will Marshall
[00:19:41] S0: Adding the layer of AI as another business model. And we were joking about this when we were walking over there because through all the AI conversations that we have on Sourcery, it always comes down to compute. So where are you first, like, where are you storing all this? How are you handling the shift in business model? Like, where are you getting all the compute? [00:20:01] S1: Well, the compute pieces are simple. We put it on Google Cloud. We have some stuff on AWS as well, but mainly on Google Cloud. Yeah, I mean, it's not changing the business model that much because we were mainly selling data anyway, but now it's just exploding the number of people that can get value out of it. It's true that we're now adding more analytical layers towards what we call solutions, right? That's already using some AI. But the AI tools that you were seeing are much more flexible. So again, it's not so specialized. It's more that you can answer, ask any question in simple language terms, and it will have a go. [00:20:38] S0: Satellites, I mean, between what we're seeing, with Planet Labs, with Starlink, with, even geopolitical issues, like they've just become a really hot topic. One of the hot topics is data centers in space. So have you thought about this at all? Is this rational, irrational? Why would this make sense?
00:20:59 · Will Marshall
[00:20:59] S1: We more than thought about it. We just launched last week the first data center's test project for Google. Suncatcher is the name of their project. And before that, we've launched NVIDIA chips on our Pelican spacecraft. The reason we're putting more compute upstairs is to process the data quickly. It's great if we can do the image processing, recognize the ships, do the querying up there, and then just send down the answers. That means we can get the answers much quicker. In the case of the LA fires, we took an image within a couple of hours of the fire starting. We got it down a couple of hours later and then had processing time, maybe that's another hour, and then they got the image. So now we're talking several hours into the fire. What if we could have got that in minutes? That could have meant potentially those firefighters saving more lives or those other first responders getting more quickly to help people, right? So we want to reduce that timeline. And so having compute in space helps with that. Separately though, yeah, there's like, should we just put all of the computers in space? And yes, I believe it totally makes sense from a basic economic analysis. And why? The intuition comes down to something very simple. Data centers are all an energy problem. So, on the ground, you would naturally power them using solar panels if you were just thinking about the cheapest way to do it, because solar panels are the cheapest watts per dollar. However, then you have intermittency because of cloud and nights, but you don't want an intermittent data center. So then you have to add gas power or you have to add nuclear power. Then now we're starting to get really complicated, much more permitting, much more time. In space, for each solar panel, you get five times more power than you get on the ground because you can put them in a sun synchronous orbit that is always looking at the sun. And that means that you just keep the panel facing the sun, and it always is drawing power. No interruption from clouds, no interruption from day and night. So you don't have to have batteries, you don't have to have gas, you don't have any of those other power systems. Five times more power, straight to the chips, and then you just have to add radiators to cool those chips into the darkness of space.