Sourcery
00:00:00 · S0, Molly O'Shea
[00:00:00] S0: We've built about 700 satellites here in the last fifteen years. That is more satellites than any other company on the earth except for SpaceX. All 700 of our satellites cost less than a typical satellite at NASA. There's about a 1000x reduction in the cost. But this is our AI interface. We can ask it questions. We have tied an LLM to the back end, and it can search the entire Earth in under a second. Someone at NASA kept on saying when we were there, why are we spending a billion dollars on a satellite when a phone like this has most of what a satellite has, but it costs $500? [00:00:35] S1: So what was the answer to that? We are here at Planet Labs. Thank you for having us. [00:00:50] S0: No problem. Welcome. [00:00:52] S1: So what are we gonna see today? [00:00:53] S0: We're gonna see some satellites. Also some AI stuff. You're you're gonna see some of our new AI interface to all of our satellite data. But we're starting down here in the satellite lab because, it's cool. [00:01:05] S1: I mean, we got a little peek. So you guys are in for a treat. There's some vibration plates and some like, what is that one thing? You have a thunderstruck? [00:01:14] S0: Yeah. That test is the shop table. Yeah. [00:01:17] S1: Yeah. Okay. So as we walk through, we'll start over here. I know you have some older satellites we can look through, but what are the different areas that we'll see today?
00:01:17 · Molly O'Shea, S0
[00:01:17] S1: Yeah. Okay. So as we walk through, we'll start over here. I know you have some older satellites we can look through, but what are the different areas that we'll see today? [00:01:27] S0: Basically, this is our satellite manufacturing facility. So this is where we build loads of satellites. We just launched 20 more last week. We can pump them out. In fact, we've built about 700 satellites here in the last fifteen years. That is more satellites than any other company on the earth except for SpaceX. So this is the manufacturing facility for satellites. We launch about five... Four or five times a year. We've done it on 40... Over 40 rockets. So what has really changed in satellite game has been just the sheer size and number of satellites. And Planet sort of pioneered miniaturization of satellites, taking satellites that are bigger than this room and shrinking them down to small size so that we can then launch loads of them. And with loads of them in space, we can do different kinds of missions. Before, each satellite was the size of a double decker bus and cost a billion dollars minimum. I mean, some NASA missions cost up to 10. The really cheapest ones cost a couple 100,000,000. We're talking about launching all 700 of our satellites cost less than a typical satellite at NASA. So it's about a thousand x reduction in the cost. And that's all to do with the miniaturization of electronics, and that's what we pioneered here in this lab.
00:02:45 · Molly O'Shea, S0
[00:02:45] S1: Something that I definitely wanna talk about during our sit down is the use cases have kind of pretty much changed substantially, especially with the new, you guys just launched with Google. Yes. So you're you're moving into the world of intelligence, which by the way I heard has great premiums on it. But... [00:03:03] S0: Yeah. A data business fundamentally. We're selling information services. Exactly. So even though we have a satellite back end, we have our data business is a very high margins business. Each sell of a picture or analytics from that picture is very, very high margins. I love that because, you know, as a business person, we do have some capex, but really it's a very high barrier to entry. People launching satellites are few and far that they come by. They're very complicated, yet we have a high barrier to entry, but our margins look like a software business. And so it has the best of both worlds. [00:03:44] S1: Amazing. Okay, so what do we have behind Let's talk through the lore of Planet Labs. [00:03:49] S0: The lore, [00:03:49] S1: exactly. Because we have some right here.
00:03:51 · S0
[00:03:51] S0: Yeah, yeah, we do. This is actually whiteboard from our garage when we were playing them out. This is the garage where we first set. This is our initial team. We were building our first satellite there in the lab. This was, we were still working a little bit at NASA and then we slowly left. This is in our nights and weekends and then we were like, okay, this is too cool. So we started building these satellites. I mean, you can see various bits of them, solar panels, actual, boards that we make for the satellites. I can actually show you. This is the optical, telescope assembly. So this is the telescope and then the camera system. You can look down there and you can see the actual telescope. You can see yourself in the mirror so to speak. And that is looking down taking pictures. Now we're 500 kilometers away, so about the same distance as from here to Los Angeles. We are taking pictures that far away, but we can see individual trees, we can see houses. It's amazing that we can do that 500 kilometers away from a telescope this big. And this is what the satellite looks like all put together except for the solar panels. Now this is one of our older ones, but it gives you a sense. As I said, this is the telescope. This is the, the motherboards. This is perking down. Right? That's taking pictures up into the stars. It automatically recognizes the constellations and then goes, okay, well that constellation is there, therefore I'm pointing exactly in this direction. Then it can turn itself around using these little wheels, so it can spin itself in any direction to take a picture that we want it to take. Yeah. Then it beams it down to the ground using these radios. Now these radios, you might think, what the heck are these bits of wire? We can get two gigabits a second from our satellite down to the ground station over a thousand kilometers away. So we're talking about about two gigabits a second down to the ground over a thousand kilometers range. Mean, it's like sometimes our Internet in this building is worse than that. Can't...
00:05:54 · Molly O'Shea, S0
[00:05:54] S1: I understand. [00:05:56] S0: So so basically, all of this electronics tells you where the satellite is in space. That's the GPS. Where it's pointing with a star camera, the sun sensors. Mhmm. And then we take a series of pictures, and then we embed that metadata on that picture so that we know where we're pointing. And then we stitch that to the Earth's surface. Now we have about 200 of these in orbit. They image the entire Earth every day. It's the only system that does that, that images the whole Earth. [00:06:23] S1: And how many images do you do a day, and what is the file size of a shot? [00:06:27] S0: 4,000,047 megapixel images, basically. So it's of order, I think, a 100 terapixels. Oh my god. Yeah. And eight spectral bands for every pixel. So it's actually... It's kind of eight pictures for every point on the Earth's surface with different colors, but not just the three that we have, RGB and our eye Mhmm. Red, green, blue, but we have eight spectral bands that cover near infrared into the optical wavelengths. [00:06:52] S1: And so for people who might be newer to Planet Labs, why is image data so important maybe versus like radio occultation data?
00:06:52 · Molly O'Shea, S0
[00:06:52] S1: And so for people who might be newer to Planet Labs, why is image data so important maybe versus like radio occultation data? [00:07:00] S0: Well, there's all sorts of data that you can get from space. Imagery is of course super useful because it is the kind of data that we can visually interpret. We're visual creatures, right? You name it, we can see it, we can understand it. Also, there's a huge amount of work in visual language models now. So graduating from the machine learning things that we're doing, recognizing cats and dogs in videos online, can now recognize buildings and ships and planes and trains or whatever it is that you're trying to find. So AI is very ready for it just like we're very ready to look at it. Of course, we can't look at 4,000,000 images per day. So we're using machines to do most of the heavy lifting there. Okay. Do wanna hold it? Sure. [00:07:47] S1: Oh my god. [00:07:48] S0: What do you think? No. Not. No. Don't drop it. Actually, if you dropped it, it won't be so bad because that is more or less dropping it from about [00:07:54] S1: your jobs is to throw this against the wall.