Will Marshall - Indexing the Earth - [Invest Like the Best, EP. 251]

My guest today is Will Marshall, the co-founder and CEO of Planet. Will founded Planet in 2010 with a small team of NASA scientists to build a constellation of satellites that would image the entire Earth every day. Since then, Planet has successfully built and deployed 450 satellites into space, which the company is using to create a time series of images for every place on Earth. Our conversation covers the untold space story. How space is going through an internet moment where cost reductions and performance enhancements have led to a seismic shift in what’s possible above our atmosphere, and how that can drastically improve life on Earth through unique datasets like the one Planet is piecing together. Once you listen to Will speak about Planet’s progress and mission, it’s hard to think of a more underappreciated company in business today. Please enjoy this great conversation with Will Marshall. For the full show notes, transcript, and links to the best content to learn more, check out the episode page here. ------ Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes. Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more. Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here. Follow us on Twitter: @patrick_oshag | @JoinColossus Show Notes [00:02:57] - [First question] - His thoughts on the renaissance of the space industry [00:05:09] - The earliest days of Planet and why he started the business [00:09:22] - Unique data units captured by their satellites [00:13:35] - The real estate of space and interesting angles to consider [00:15:59] - How customers interface with Planet and their early use cases [00:20:57] - Thoughts on the sovereignty of space and the laws that exist currently [00:23:43] - Figuring out the dynamics and pricing of Planet’s business model [00:27:34] - Examples of stress and tensions when working in space [00:29:08] - The future of privacy and concerns we should have there collectively [00:30:29] - Five different types of satellites and their functions [00:31:39] - The most sci-fi potential futures that Planet may unlock someday [00:32:54] - Indexing the Earth and using data to train machine learning algorithms [00:34:02] - What he’s learned about Earth that is most surprising [00:37:12] - Contributing factors to a 70% decline in life on the planet in 40 years [00:38:35] - Ways that going public might impact Planet’s long term goals [00:40:23] - The hardware story of building various prototypes of satellites [00:42:18] - How much is built in house versus outsourced to fabricate their satellites [00:43:48] - Complimentary space trends that are compounding beyond imagery [00:45:32] - Whether or not they plan on making their data open-source [00:47:15] - Democratizing their data and allowing other companies to build on top of it [00:48:30] - The kindest thing anyone has ever done for him

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Patrick O'Shaughnessy?

  I know firsthand how complex the tech stack is for asset management firms. And seemingly every new tool and data source makes the problem even worse, adding more complexity, more headcount and more risk. RidgeLine offers a better way forward. One unified platform that automates away the complexity across portfolio accounting, reconciliation, reporting, trading, compliance, and more, all at scale. RidgeLine is revolutionizing investment management, helping ambitious firms scale faster, operate smarter, and stay ahead of the curve. See what RidgeLine can unlock for your firm. Schedule a demo at ridgeline.ai. This episode of Invest Like the Best is sponsored by Canalyst. Canalyst is the leading destination for public company data and analysis. Founded by a former buy-side analyst who encountered friction sourcing, building, and

• 0:43Patrick O'Shaughnessy?

  updating models, Canalyst is now used by over 400 institutions, including the largest money managers globally, and by a number of guests on the show. With detailed company-specific models and data on virtually every public company, Canalyst's clients are able to ramp up faster, update models instantly, and incorporate the highest quality fundamental data into any workflow. If you're a professional equity investor and haven't talked to Canalyst recently, you should give them a shout. Learn more and try Canalyst for yourself at canalyst.com/patrick. That's C-A-N-A-L-Y-S-T.com/patrick. This episode of Invest Like the Best is brought to you by Watchbox. Whether you're looking for a special gift or something for yourself, at Watchbox, the world's finest watches are available at your fingertips.

• 1:26Patrick O'Shaughnessy?

  The growing selection at Watchbox features all the most renowned brands, plus the industry's most exciting independent watch companies. All certified authentic and collector quality. Watchbox's global team of expert client advisors can help you find the watch you've always wanted. Step into the collector's circle at thewatchbox.com/patrick.

• 1:48Patrick O'Shaughnessy?

  Hello and welcome, everyone. I'm Patrick O'Neal and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. Invest Like the Best is part of the Colossus family of podcasts, and you can access all our podcasts, including edited transcripts, show notes, and other resources to keep learning at joincolossus.com.

• 2:14Speaker 01

  Patrick O'Shaughnessy is the CEO of O'Shaughnessy Asset Management. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of O'Shaughnessy Asset Management. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of O'Shaughnessy Asset Management may maintain positions in the securities discussed in this podcast.

• 2:39Patrick O'Shaughnessy?

  My guest today is Will Marshall, the co-founder and CEO of Planet. Will founded Planet in 2010 with a small team of NASA scientists to build a constellation of satellites that would image the entire Earth every day. Since then, Planet has successfully built and deployed 450 satellites into space, which the company is using to create a time series of images for every place on Earth. Our conversation covers the untold space story, how space is going through an internet moment where cost reductions and performance enhancements have led to a seismic ship in what's possible above our atmosphere and how that can drastically improve life on Earth through unique data sets like the one Planet's piecing together. Once you listen to Will speak about Planet's progress and mission, it's hard to think of a more underappreciated company in business today.

• 3:24Patrick O'Shaughnessy?

  Please enjoy this great conversation with Will Marshall.

• 3:29Patrick O'Shaughnessy?

  So Will, I think the place to begin, since this is such a cool, exciting area of space, the space renaissance that we're going to be talking about today in your company Planet Labs, maybe you could just give us your impression of what's happening in space. And I think it's going to draw a nice contrast to the very obvious rocket-focused, billionaire-focused thing that ever, going to Mars, going to the moon. I think you're seeing a very different side of space and are a part of building that new industry and that new world. Just give us your overview, how you interpret what's happening in this space renaissance.

• 3:57Speaker 02

  It certainly is a space renaissance out of the gate. So there's no question I agree with that statement. We are seeing Massive shifts. Rockets have decreased their cost about four X. That's a big deal, mainly through reusability of especially because of SpaceX. And then and a proliferation of nano rockets as well, which is kind of cool. But I think the other side of it is what's happening to satellites, which is we've seen about a thousand X cost performance increase in satellites of the same period of the last five, 10 years. What the main upshot of both of those trends compounding, and they do compound, is that we are seeing vastly new data sets emerging. We are generating and transporting vastly more data, like

• 4:39Speaker 02

  10 times more than we were before or more about the earth and transmitting that around the earth. And what's that relevant for? It's relevant for everything here on the earth. It's about data about the earth that helps us to transition to a sustainable economy. Everything that the countries are trying to do in missions, every company trying to measure ESG targets is relevant for that. And it's relevant for digital transformation, the general trends of AI and big data, helping all these industries become more efficient, like agriculture, transportation, government, and so on. And a lot of that data for those digital transformations comes from space. So space isn't this esoteric distant thing with rockets billionaires only, although that is happening. I think the far more exciting

• 5:24Speaker 02

  story and less sexy perhaps because it doesn't involve the rockets or the billionaires. It involves massive new data that is helping us here on the earth. It's helping the earth economy. It's helping us transition to a sustainable planet. And both of those things are super important. I think that's the untold story.

• 5:41Patrick O'Shaughnessy?

  I think one of the coolest trends in technology generally is making certain things legible to software through data sets, through image sets in your case, et cetera. And the wild things that can then be built on or learned on top of those emergent data sets. And so I'd love to tell that whole story through the planet lens in as much detail as we can, maybe going all the way back to the beginning. You have the benefit of literally starting, I think, the first of satellite was built in a garage. So the proverbial garage was a real one in your case. Take us back to the earliest days of Planet, its origin story and why you started the business.

• 6:16Speaker 02

  Yeah, happy to do that. And by the way, the investors of D M Y, the group that we're merging with as part of going public. His name's Nicola and he says, all the best software companies build their own hardware. Apple, you can think of like that. Tesla, he considers a software company, but he's building his own hardware. There's a way of viewing that. I think certainly Apple's, I think, a really fantastic example. We feel that the same. We're not selling the satellite hardware. We're selling data that is produced from that. But by building our own satellite hardware, we create much efficiencies in that. Back to the garage days, myself and a small team, about seven of us left NASA to start Planet. Then we literally started building the satellites in our garage.

• 7:00Speaker 02

  What we were thinking about at that time was, how do we as space geeks help all these challenges of the world? From poverty to climate change to everything that was going on. And we felt that there's a huge business opportunity as well in one and the same mission, which was to image the whole earth every day. Because we thought that data would spur economic development and it would help with these real huge problems. And no one had ever done that because it required at least about a hundred satellites in the orbit. Well, no one had ever launched a hundred satellites. We'd have to do things very differently. We had been pioneering at NASA this thing called the Small Spacecraft Office, which was low cost planetary missions and other things. And we were trying to take that a couple of steps further.

• 7:45Speaker 02

  And say, okay, can we even leverage consumer electronics, like the kind of electronics that's in your laptop or in your phone in space? And thereby, instead of spending billions of dollars per satellite, spend a lot less, like a thousand times less than that, or 10,000 times less than that, like a million or 100,000 dollars, and do something like image the whole planet every day. We figured that we could. And so we left NASA to do that. And six and a bit years later, we achieved that mission of having launched the largest constellation of satellites in history. We had just over a hundred satellites in orbit. SpaceX, by the way, has just overtaken us recently in numbers of satellites.

• 8:24Patrick O'Shaughnessy?

  The bastards.

• 8:25Speaker 02

  Not that I'm too upset about that. By the way, if you count the number of satellites in orbit, they doubled roughly in the last five years. And half of the satellites are now of two companies. That's Planet and SpaceX. So although there's a proliferation.

• 8:41Speaker 02

  It's really quite concentrated at the present time. But anyway, yeah, so we started building our satellites in the garage and six or seven years later, we got to our daily cadence, having launched all these satellites. It was much harder than I thought. I thought we could do it in three years of, and it took six. But we achieved something that was really cool. And we have this brand new data set of an image of the entire Earth every day. So it's a bit like when you go onto Google and you see the satellite layer, that image is maybe three or five years old. We're doing that every day for the whole planet and we're keeping all of those images. So we have about seventeen hundred images for every point on the landmass of the Earth. So a deep stack of images. So it's like Google Earth, but with a time axis. So it's a recent data and a tall

• 9:25Speaker 02

  stack of information. And that's how we figure out what's changing on the planet, where all the resources are being moved, all the vehicles, agriculture, shipping, we figure out all the changes on the planet over time, and we can train all our machine learning on top of that stack of data. You ask any machine learning expert, like, what's the most exciting thing? It's training data. Well, we have gobs of it. We have seventeen hundred images, as I said, very close on the Earth's landmass on average, to train all your algorithms about what's going on.

• 9:54Patrick O'Shaughnessy?

  Sounds like the coolest thing ever. If you were a data scientist getting your hands on this data set, tell me a little bit about the unit of data. So if I take one of those images, what is being captured by you or the satellites and what isn't being captured? And maybe that's something that may change in the future, but give us a deep dive into the actual unit of data itself.

• 10:14Speaker 02

  Each pixel from our scan is about three by three meters. We collect them in forty seven megapixel images. So each satellite takes an image forty seven megapixel. So it's around twenty or twenty five kilometers across and twenty kilometers high frame image, a full frame image. We take about three million of those images per day to cover the entire landmass. In fact, we cover about just over three hundred million square kilometers per day. So that's the unit measures of the area coverage. And the Earth's landmass is about a hundred fifty million square kilometers. So we cover all the Earth's landmass and some ocean territories like Mediterranean. Caribbean and the South China Sea and a few other hotspots and coastal areas around all the landmass.

• 10:57Speaker 02

  And in some areas of the land, we do multiple times. You have a fleet of higher resolution satellites that can have a resolution of about fifty centimeters, about three meters. They don't scan the whole earth. They're tasked to specific locations. So if you say, where do you say you were in?

• 11:11Patrick O'Shaughnessy?

  Connecticut.

• 11:12Speaker 02

  Connecticut. If you want to take a picture of town town there, we can do that up to ten or twelve times per day. But you have to tell me I want that picture. And actually, these systems work together. So we have the scan that finds changes around the planet. Oh, this iceberg moved, these ships moved, this whatever, this field's got tilled. Then you can use the high res system to point at those changes. We can say, oh, there's a big new building construction here. Let's have a look. There's a lot more ships in this port. Why is that? Let's take a deep look. What sort of ships are they? So the systems work in complement. Really, I think of three legs, the story of planet, which is the scan, the zoom in and the analytics, the machine learning that enables us to understand it all.

• 11:53Patrick O'Shaughnessy?

  Is there a future where you start to measure more than like a visual image? So you start to measure infrared, or I don't know what the other spectrums would be or the other information. But if so, what does that roadmap look like? In fifteen years, what might we know daily about the earth that we don't today?

• 12:08Speaker 02

  Generally, the answer to your question is the data is going to get better and better. Better resolution, that's the size of those pixels. Temple resolution, that means more frequently. And better spectral resolution, which is more spectral bands is what you're getting at. Right now, our satellite fleet, the main one that does the scan of the whole earth, which is one hundred and eighty satellites, does that in eight spectral bands. So three that are familiar to the eye, the red, green and blue. But we also have five other spectral bands. So there's a near infrared band, a red edge band. Then there's various different things. One helps us to tell biomass. So basically, we can tell crop type and yield for agriculture. Another one that enables us to tell the top of the atmosphere haze level, which helps us to calibrate all the other data and so on.

• 12:53Speaker 02

  Yeah, with time, we will increase that as well. So it's not just pretty pictures, actually. You can't even see these things. We do do false color images of them. But for example, that near infrared. And as I said, we can tell it's wheat and it's doing this well. And that is how it gets into this agricultural application, which is actually our biggest market. We can tell crop type and yield in every farmer's field, in every bit of the farmer field, that three by three meter box. We can say, how well is the crop doing? And does it need fertilizers? Does it need harvesting? When does it need water? And so actually, yes, we're already getting other information. And then that's before we build up analytics on top of that, that are the things that automatically detect certain things like we automatically with machine learning, pull out roads, buildings, ships, planes.

• 13:37Speaker 02

  So you can now, if you're interested in shipping, you could circle the top 10 ports of the world. Just tell me how many ships there are in these ports over time. That's all I want. I don't want to look at the pictures at all. You can now do that on our platform. Now, you can't do everything. You might ask some other questions we don't yet answer. We're trying to get better and better so that one can actually not have to have a PhD in geospatial science to to understand this imagery, but rather actually everyone could get information and value out of the imagery every day.

• 14:07Patrick O'Shaughnessy?

  What is happening in space, literally? Where are these things? Are they in low Earth orbit? Is it getting crowded up there? Give us a little bit of education on the literal real estate of space and the angles there that are interesting. If this is just going to keep compounding and it's going to get more and more higher resolution and more satellites, what implications does that have? What's the story up there?

• 14:26Speaker 02

  These satellites are in low Earth orbit, about 400 kilometers up. And that's considered quite low. Most of the satellites are in 800 to 1200 kilometers orbit altitude in low Earth orbit. And then there's the higher ones in geostationary orbit to manage communications. And a few others like MEO, which is sort of in the middle, like GPS that you use every day for your navigation. Our ones, um, we care a lot about the space debris problem that you're referring to. There is a challenge of space debris. It's mainly not the satellites. There's about 3,000 satellites in orbit today and operating. There's about 100 million pieces of debris.

• 15:03Speaker 02

  So the vast majority of it is bits of old satellites. We're not talking about asteroids. We're talking about manmade stuff circling the earth, but it's all the fragments of previous launches. We didn't know about space debris early on in the space industry. So the Russians and Americans in particular did a lot of stuff that created a lot of junk in space, like exploding bolts on rockets. Or they leave fuel in the satellite. Some spark happens after the satellite's dead, long years afterwards. And it blows up the satellite accidentally. Instead of being one bit, there's now thousands and thousands and thousands of it. And then occasionally, countries have blown up satellites deliberately. Recently, the US did, China did, India did.

• 15:46Speaker 02

  And that's mainly to say to the other countries, hey, we can knock out your eyes and ears if we want to. Really frustratingly, from our perspective, because you make a bloody great mess.

• 15:58Speaker 02

  There are challenges, mainly not the satellites. It's the debris. So what do we do about the debris? We can maneuver the satellites out the way of each other. No problem. What do we do about the debris which don't have propulsion systems on them? We actually came up with a scheme when I was at NASA to deal with that using a ground-based laser. It's called a system called Lightforce. Anyway, it's a longer story, but we keep our satellites way down low to make sure they're out of the way of debris, not creating any more debris. They come down naturally at the end of life after about three years and burn up in the atmosphere and get out of the way.

• 16:31Patrick O'Shaughnessy?

  Let's talk now about how customers interface with you. So I love the story of starting in the garage, building a very low-cost satellite, the Dove satellites, getting the constellation up there, mission accomplished. It's going to keep compounding and getting higher and higher resolution. What was the first commercial intersection that you had? Did you plan to cater to the agriculture industry to start, or did that emerge as sort of like an unpredicted or unpredictable use case?

• 16:57Speaker 02

  We had thought about that use case. It was a very early one. One way to think about it is look at the areas of the earth and how are they used? About a quarter of the landmass of the earth, twenty-five percent, is agricultural land. So we went into that. A quarter of the landmass of the earth is forestry. So we went into that. About ten percent is urban development, the suburban or urban. Then that's called large areas of marine. Anyway, but agriculture was an obvious one just from a sheer area. We knew that we could do something useful in agriculture with a near infrared band. That's a known thing from Landsat, which has been doing this for forty years, except it's just doing it in a slower cadence, which makes it less useful growing the crops and helping the crop development. It's more like for the annual survey of how do we do, which is useful at the end of the year,

• 17:41Speaker 02

  but it's not helpful for the grower in the crop growing season. Because what the farmer wants is intelligence about their field a few times a week during the crop growing season. And so by having daily information at that three by three metre area of every field of that farmer, every one of their fields, we can help them do what's called precision agriculture. And that can improve their crop yield by twenty to forty percent. And at the same time, decrease their use of things like fertilizer and other resources by similar amounts. That's a big deal. If you think of that, we can do that across a trillion dollar industry. This is, as I said, the general notion of big data and AI enabling the digital transformation of industries. Ag is a canonical example. We do that, for example, with Corteva.

• 18:26Speaker 02

  They use this to image about a million farmers' fields every day. This is not a minor operation and a lot of those kind of companies that can use our data to help with precision ag. The other areas, we help civil governments, normally things like disaster response. It's also science. So we work with NASA on a lot of science, like climate science. But we also work with state and local governments and federal governments on things like floods and fires. So we've been helping recently with the floods in Germany, where they had a lot of big floods, the biggest floods there for sixty years. With the fires here in California, helping the wildfires, we can both detect where the fires are to help the firefighters. Like where's the wind blowing? Where's the edge of the fire?

• 19:09Speaker 02

  Where is it compared with the whatever hill? And so we can help with the real time and we can help with preventative work. So we can actually, and we have, map every tree in California. And where's the fodder for growth for future mega fires? And that can help them to then make clearing or do a fire lane in the future to stop future mega fires. So. It's preventative work, same with flooding, like we can see the flood the day before, the day after the flood. See apples, arrows, which bridges down to help the relief effort. But we can also then model, where's the flood plane gonna be? Which buildings are in the wrong place? Where should they build and not build, especially in developing countries? They often build in the wrong place. So we have a big project with Google where we're doing this in Bangladesh and India.

• 19:54Speaker 02

  It's because the flood planes change. They can then advise governments, don't build here, do build here. That's important for getting assets out of the way of the flood. And it's also important for finance, by the way, because they also want to understand which assets are at risk from these various disasters or potential disasters. So civil government's another area. We also work with mapping, that's a fascinating use case. And this is where it gets into what consumers might actually see. Because we're not, they're selling the imagery to consumers, we're selling it to big businesses, but. But it does affect day-to-day people because the maps that you have online are kept up to date with our data. The news you see about world events, we're sort of shedding light about everything going on on the planet.

• 20:37Speaker 02

  Pulitzer Prize this year was won by some journalist who used our data to discover about two hundred potential Uighur, that's Muslim detention camps in western China that had previously not been known. And that sort of thing is really important journalism that happens using our data to uncover what's going on around the world. And also, if you're caught up in a disaster, our data might be helping the disaster responders to help you. So it actually affects people day-to-day, but in mapping, that one case, we work with Google, for example, on updating the maps that you see online all the time. That whenever they find any indication that the map is going out of date, they automatically task ourselves, like it takes a picture of that location, extracts out that new road, that new train station, that new building, whatever it is.

• 21:20Speaker 02

  And then it updates the map you see online so that your directions and everything stay up to date. So there's a lot of different applications, I'm just giving you a sample.

• 21:29Patrick O'Shaughnessy?

  The story that's emerging is like this incredible thing where so much of the world is dictated by illegibility around data that we've surfaced. And this is like, what's more important than like the place where we live? And it makes me start to wonder about big questions like defense or national sovereignty, the famous spy planes from the Cold War or something like this is that every day of the entire earth. So how do you think about certain nations not wanting you to see certain things? What is sovereignty in space? How will the rule of law and nations interact in this new frontier?

• 22:01Speaker 02

  Good question. Firstly, it's interesting, the US and Russia established early on in the space age that they would not be able to fly planes over each other's territory. Famously, the Russians shot down the U2 spy plane, Gary Powers, and killed him captive. But they would allow satellites to fly over each other's territory. And partially, this because satellites can't just maneuver around countries. If you're coming up, you can't come up to Russia and turn left, you're in, you're gonna go over Russia, right? Unlike a plane, you can turn around. So you're gonna go over Russia. And then the only question is, are you going to allow them to take a picture or not? Well, how are you going to stop them taking a picture? So then they were like, shit, this doesn't work. But we're gonna allow satellites to fly over each other's territory without permission. In fact, they

• 22:45Speaker 02

  felt that this is a good thing, and they cemented it, and it became international law. The up to 100 kilometers altitude is your territory, and beyond that is space. And once you're in space, you are not in anyone's sovereign territory, and you're allowed to take pictures from there of any territory without their permission. So we can take pictures inside North Korea, and the North Korean government may not like that, but they have no choice. But vice versa, in principle, the North Koreans can put up satellites and take pictures of America, and they in principle can do that. They don't have that, but like, they could. It's a bit of a thing that they decided early on in the space age was gonna be something that everyone could do, and that transparency was better. And in fact, it reduced tensions during the Cold War. We're actually doing a whole bunch of work with governments, intelligence agencies that do use our data. And you think, oh, well,

• 23:30Speaker 02

  they already have satellites. Well, they do, yes, but they don't have nearly as many as we do. We have the most by far. And so we see a lot of stuff that they don't. Yeah, we do the scan and they only task at locations they already know to look, which are very interesting to them. We find new things that they didn't know to look for, a new missile base in eastern Iran we just recently found, for example, and that's kind of interesting to a lot of people. I think this is generally a good thing. We're not, by the way, ever exclusively giving that to one government or another, and the more that we give that to lots of governments, the better it is for peace and security, just like it was during the Cold War, the Russians and the Americans knew about each other. But it's also a significant business opportunity for us because that data is relevant to a lot of countries and they all want to know.

• 24:15Patrick O'Shaughnessy?

  Copy through a little bit the way you figured your way through a business model because most businesses you can think about like cost-based pricing or value-based pricing, like just to really oversimplify it. Using the crop example, you're making twenty something percent improvements in a trillion dollar industry. Oh, that sounds like a lot of pricing power, right? How do you think about pricing your various products and services? It seems like a real challenge that there's enormous investment to get this ongoing thing into space and happening, which took six years, you said. Now you've got to figure out how to charge for these things. It's not like someone can spin up a competitor easily. So how do you think through those dynamics of the business model itself and things like pricing?

• 24:54Speaker 02

  Yes, so we basically sell imagery on a per-unit area basis. Kilometers, hectares, mainly just area. And the more area you get, there is a volumetric discount, but obviously you pay more. So we do have a lot of pricing power. I agree. Right now, there's no one else that does this. And to your point, it's very hard to get this data set. You have to erect a huge satellite fleet and ground stations, mission control systems, data processing and all the rest. So it's certainly not for the faint of heart. And of course, so it'd take many years for somebody to build such a system and of course, we're not going to sit on our hands. We improve it and that data archive, it's impossible to go back and get. So it's actually,

• 25:36Speaker 02

  there's some really important notes around what we've built. But yes, we do have a fair bit of pricing power. Some of it's value-based pricing, but I do think that what's most important for us is where we're going next is not just the imagery and selling the imagery, but selling information products derived from that imagery, what we call going up the stack. The main thing we're doing today and the reason we're going public, one of them is of course we have capital to then deploy and the main areas we're deploying it, one is just sales and marketing to go after the vertical markets we already know work, like agriculture, civil government, and the ones I was describing. The second thing is that there's loads of potential to other markets, but they

• 26:16Speaker 02

  need more than images. Hedge funds could get huge value out of our data. I mean, we know how well crops are doing before anyone else. The whole world saw a year. We know the output from all the world's copper mines before anyone else. So presumably those things are really valuable to those commodity prices. However, they do not want those pictures. They want a time series calibrated data. We have the data to underpin that, but we haven't built the analytics that enables that yet. So the other side of what we're doing is investing in what we call going up the stack. And then we'll be charging more and more for just information products derived from the data. Anyway, a long-winded answer to your question, but so mainly it's volumetric based on the amount

• 26:56Speaker 02

  of data, but also as we go up value stack, we'll be charging more for those, if you like, smaller bits of data that we can drive from the imagery.

• 27:06Patrick O'Shaughnessy?

  How much of that is push versus pull in terms of deciding where to go with that movement up the stack? Like, are you basically letting people tell you what they want? Or are you anticipating what they might want and then trying to sell it to them or some combination of the two?

• 27:19Speaker 02

  I think it's a healthy combination of the two. We pride ourselves on thinking more than just what the customer's immediately asking for, because often the biggest opportunities from a business perspective are doing things that people don't know they want yet. No one asked for an iPad or an iPhone. When they got it, they were pretty excited. So they were thinking ahead. No one asked for a daily image of the whole earth, thinking ahead. The same with analytics, but we also listen to our customers. So for example, a lot of our ad customers are saying, can you just fuse this data with this data? And then it will be more valuable. We're doing that ourselves right now, but we don't really want to. We want to focus on the funding. Great, sure, we'll do that and we'll follow their lead and add that stuff so that it takes that off their

• 27:58Speaker 02

  plate and adds value to us and it helps the customer, eases their use and helps them to focus where they want to focus.

• 28:06Patrick O'Shaughnessy?

  What does tension feel like in this business? When you're stressed out, what are typically the reasons? Like, it seems like the problems that you encounter are just of a completely different type than a typical business would, given the the unique nature of what you've built. What is crisis, stress, tension? What does that feel like for Planet?

• 28:23Speaker 02

  I would say we're a company like any other. There's growing pains where you have to shift different stages of company where not everyone knows each other anymore and then this happens or you need this sort of leadership and not that kind of leadership and this. There's so many growing pains as we go. I think we've done fairly well, but we're not immune to those things, just like any other companies. It's, I would say it's the nuts and bolts. There are some things that come up when a certain actors ask us for data and we're like, should we give this to them? And so we have an ethics committee that we firstly review against the embargoed list that we can't sell to North Korea, we can't sell to Taliban or something. But also we have an ethics committee that even after that goes, okay, we're allowed to sell to these guys, but should we?

• 29:07Speaker 02

  Our data is not generally relevant to militaries targeting or anything like personal privacy because we can't identify a person. But there are some cases where we worry and avoid those use cases. In general, our data really helps this wide scale transparency and helping companies and countries understand resource movements. That's really very positive and we wouldn't be doing this. We didn't think the net was massively in the direction. But we are trying to occasionally a stressful moment is when someone asks for it that we were like, I'm not sure we should give it to these people. And we have often refused in those cases.

• 29:40Patrick O'Shaughnessy?

  Data privacy has become a really interesting big issue in the world that's proliferated in data and so many companies that know so much about us. What do you think will happen in privacy over the next couple of decades when it comes to your business or just the idea that assuming all these resolution curves keep going on the same direction, presumably you're going to be able to see like into my house on a second by second basis potentially. How do you think about the future of privacy and concerns that we should have there collectively?

• 30:08Speaker 02

  Firstly, right now, we really can't see or identify a person from space. And I don't think anyone can, even with the huge satellites. And the reason is that you're just so far away. You're 400 kilometers away. So yes, we can see your house, but firstly, it's impossible with current technology to see through it. And I don't know how we would do that. And secondly, the pixel size is really large. Even as I said, the biggest spy satellites of the biggest countries cannot identify a person from space. Their resolution is just not sufficient. And so it's really a matter of distance. If you want to get in person privacy, really drones might get into that. But satellites, that's a long way off. I can't even imagine. It's just because you can't fly recently in a satellite lower than about 300 kilometers altitude. Otherwise, you're just

• 30:51Speaker 02

  starting to burn up in the atmosphere. To go below that, you really need a plane or a drone. And so I think space for a long period isn't going to get really into the thick of privacy.

• 31:01Patrick O'Shaughnessy?

  Maybe you're going to do it all, but I'm curious just to talk then a little bit more about the technology of satellites themselves. If you had to group satellites in like some sort of taxonomy into different categories, how would you do that today? So there's imaging satellites, you mentioned communication satellites.

• 31:18Speaker 02

  There's roughly five kinds today. There's imaging satellites, there's communication satellites. Those are the main ones where there's a commercial sector, although both of them have military versions of those things. The other three are navigation, which is pretty much only governments at the present time, Galileo and the EU GPS here, early warning, which is countries scan for anyone's missile launches. And then there's what they call a signals intelligence, which is listening into people's communications to listen to your cellphone or listening to things. And again, this is sort of CIA stuff. So those are the main five types of satellites that exist today.

• 32:00Speaker 02

  But the commercial ones are really just communications and now SpaceX with the Starlink system is putting up a big communication fleet and Earth observation, which is Planet has put up a big fleet on.

• 32:11Patrick O'Shaughnessy?

  If you stick in the Earth observation planet category, what do you think are the most far-fetched sci-fi potential futures for what the technology might enable, say that, you know, the rest of your career or something like that on some timeline that's long but reasonable?

• 32:25Speaker 02

  Well, I do think that it's possible in the long term that we would more or less be able to go have a live image of the Earth. I think that that's possible. It's not where we are now. It won't be for a long time, but it's possible. And then the second thing is I imagine that you should be able to just query that. You should just be able to write, instead of just imagine like a search query box on it, and you can just say, hey, how many houses are there in Pakistan? Give me a plot of that versus time. Tell me where the trees were deforested, the latitude and longitudes of the trees that are deforested in the Amazon in the last three weeks. It should be able to just tell you the answer to those questions without ever you looking at the images, or it may highlight that in the background or something. But like, you should be able to get answers just like you

• 33:09Speaker 02

  can from Google. So I think a lot of what Planet's doing in the long run is a little bit similar to Google. Google figured out how to search the internet, to index the internet, sorry, and make it searchable. And we're figuring out how to index the Earth, making it searchable with the combination of the data, the machine learning that sits on top.

• 33:26Patrick O'Shaughnessy?

  Can you say a little bit more about that machine learning and that actual exercise? That just seems like a Herculean task to go index the Earth. Pretty cool idea, but sounds pretty hard as well.

• 33:38Speaker 02

  Well, it was a hard task to index the internet. But then it's the, well, just imagine a picture of the Earth and machine learning, especially computer vision that's been developed, especially by companies like Google and academia and others, has been particularly strong in computer vision where. It does things like extract out cats and dogs from pictures, you know, that you put online. The same technology could be used in our image to extract out a road or a building or a ship or a plane or a train or a tree. So we just have to do that for every image that comes down. I said, we have about three million images every day. So you have to do that for every image and identify all the different objects.

• 34:19Speaker 02

  And then you have basically a database of every object on the planet over time. And then you should be able to exactly do that. Query on top of it, I actually think it's intellectually relatively straightforward. Of course, there's a huge amount of work behind that.

• 34:34Patrick O'Shaughnessy?

  With this unique data set, moving up the stack that you've done, what knowledge about the earth has most surprised you that's resulted from this data set so far?

• 34:44Speaker 02

  Well, the degree of calamity of the destruction of ecosystems is just staggering. So we are wiping out forests mainly to put cows on them so we can eat beef burgers. We are destroying the fisheries with ocean trawling. We are seeing huge transitions and mainly because it's not actually climate change. It's mainly these things like deforestation and illegal fishing. So it's been driven by humans deciding to change the use of those territories. And that is just really obvious and sad. But hopefully our data can help companies and countries and individuals better manage the planet. We've what lost seventy percent of life on the planet in the last forty years.

• 35:29Speaker 02

  It's gobsmacking to think about. We are just whittling it away still. Our raison d'etre in many ways is to help stop that, is to help the governments to see the deforestation. So we have a project to map all, which we do, all the deforestation in the sixty-four tropical countries with government of Norway paying for the data, helping that data be available to those forestry ministries to stop deforestation. Huge project. We have another one to map all the world's coral reefs. And we just released that a few weeks ago, which first map of all the world's coral, classification of different types and showing early signs of bleach. Or if there's any illegal fishing going on, we can alert governments. In fact, there already

• 36:11Speaker 02

  six countries have established marine protected areas around coral reefs that we mapped for them. So those are the kind of things that can really help us protect and stop the eco side that's happening on the planet. And so that is both a thing that's super important for the planet. And it's a massive business opportunity because what is really happening is that global economy is going, ah, we cannot any longer presume that natural capital is free. The trees you cut down and it's free. For the landowner, they can just cut down a tree and it's costing nothing. Or you can just put gases into the atmosphere and it doesn't matter. Or pollutants into the rivers, it doesn't matter. There's an externality of that cost. We've got to integrate that externality into our economic system.

• 36:54Speaker 02

  And that is the countries saying, we're going to measure these emission targets and set these limits. And it's companies doing their E S G targets and saying, hey, the environment piece, I'm going to measure and make sure that my resources came from a sustainable source, or make sure I don't build those assets in a flood risk zone or these sort of things. And what does that mean? All of that means those countries and the companies have to measure all that stuff. So this is a massive business opportunity because we have the data set that's pretty foundational to the measurement of all that natural capital. It's measuring all those things. It's not just that we can see every tree and subdeforestation. We can count the carbon stock in all those trees. Our data is foundational to underpinning the

• 37:38Speaker 02

  transition to a sustainable economy, which is a multi-trillion dollar transition as well.

• 37:44Patrick O'Shaughnessy?

  Seventy percent number that you quoted over the last forty years, which is kind of a staggering, horribly depressing number. What's the attribution of that seventy percent? What specifically has been wiped out that makes out most of that decline?

• 37:55Speaker 02

  Well, it's pretty much everything. Eighty-two percent of wild mammals have gone, seventy-five percent of insects, seventy percent of fish in freshwater rivers and lakes, over half the coral systems. These are all the things that have gone already. We've wiped out more than half of the forests. There was roughly double as much forested land of the earth forty years ago. And it's just staggering.

• 38:17Patrick O'Shaughnessy?

  So we're basically like an invasive species. That's the way to think about it.

• 38:21Speaker 02

  Yeah.

• 38:22Patrick O'Shaughnessy?

  This data set is step one in any change, which is awareness.

• 38:25Speaker 02

  Exactly. More than just awareness, I feel like satellites have already been bringing awareness about this problem for about 50 years. That's why the climate scientists have been yelling from the top of the mountain as best they can and telling us this is what's gonna happen. And no one's been listening. This is the data set that enables us to take action. You see, the difference between what has been happening before with satellites was every few months or every year, we would take a measurement and go, this is what's going on, guys. Now it's like, there is deforestation happening there, stop it. There is illegal fishing there, stop it. You know, it's the real time action and the real time measurement and the real time enforcement that is actually gonna enable us to, I hope, turn the page on tackling this massive challenge.

• 39:07Patrick O'Shaughnessy?

  One interesting thing, just where the rubber meets the road, you already mentioned the company's going public. How do you think about that transition as it relates to this big mission? I mean, if everything we've talked about holds true, this sounds like it could be both in business terms and in terms of impact terms, like one of the most important companies on the planet or off the planet, I guess. How do you think about the relationship that you build with the business and investing community to make sure that you maximize the odds that that's true?

• 39:34Speaker 02

  Well, look, I'm really excited about going public. I think it's the right step for Planet. Planet is ready to be a public company. You know, we've launched and operated satellite fleet is ready, that technology to risk is retired. We've got a mature business with over a hundred million in revenue last year. We're ready and what we're feeling is the pull. We're feeling everyone needing our data now. Well, then we need to scale up to do that, to address all of that market opportunity. And I think from what I've seen, investors really like it for a number of reasons. One is that our data is completely unique. No one else can get it. It powers a lot of vertical markets. It's not just relevant to agriculture, it's relevant for energy, insurance, finance.

• 40:19Speaker 02

  They love the fact that it's a data business. We've got this hard moat to crack in terms of the hardware that enables this, but the data business, we're selling data and we can sell each image multiple times. So the profit margins are really large. The incremental cost of us selling an image to a second customer is very, very low. So the direct margins are just huge. And then everyone recognizes how important the transition to a sustainable economy is. And so it's space, it's sustainability, it's a data company, it's exactly what the market wants at this time. I'm confident this is the right move for Planet this time.

• 40:54Patrick O'Shaughnessy?

  I'd love to learn a little bit more about the hardware. You said that great quote at the beginning that the best software companies also build hardware because it enables like a very specific one-to-one relationship between the two. Tell me what's evolved since that first satellite you built by hand in the garage. What were the components like then? And what has happened? Like, give me a sense of what it costs to make one of these things? What's going into it? What is the hardware story here that's most interesting?

• 41:18Speaker 02

  Yeah, since that time, we've had 18 design-build iterations of our satellites. So just like the iPhone, iPhone 1, 2, 3, 4, 5. And those satellites have increased in capability per satellite per day in terms of area coverage of imagery by 10,000x over that period. I am not kidding you, that is what's happened from the first satellite to the last. Just in the last year, we doubled the number of spectral bands. Exactly to this point, best software companies build their own hardware, our customers said we needed these spectral bands. So the next generation of satellites, we added four more spectral bands that addressed various customer needs. So two years ago at our user conference, I announced the Super Dove, which is the next generation of Dove. This one, I announced the fact that we'd already

• 41:59Speaker 02

  completed daily imaging with that Super Dove fleet. We'd already had seven launches, launched about 100 of these satellites, and they're now operating and getting eight spectral bands that help these extra markets. Those satellites produce five times more than the previous generation of satellites per satellite per day for almost exactly the same cost. Great. That's the kind of trajectory we're on, and we're going to continue on. We call it strapping space to Moore's law. Every time there's a better sensor that comes out, every time there's a better processor that comes out, there's a better hard drive that comes out, we stuff it into the satellite and put it up. That way, just like you don't want a three-year-old phone in your pocket, you don't want a three-year-old satellite in space, we iterate them really fast, we treat them like a server. When one goes out of date,

• 42:44Speaker 02

  we replenish it. That's why we're on a very rapid trajectory on the satellite side.

• 42:49Patrick O'Shaughnessy?

  How much do you control versus outsource the component section of a given satellite? In one of the satellites, how much is something that you're taking the best whatever sensor from some other company and incorporating it? And you're kind of just the chassis that pieces the best in class together versus the Apple M1 chip or something? I'm trying to think of the right analog where you're end to end controlling the component itself.

• 43:10Speaker 02

  I think it is a bit like Apple. I think that's a good way of thinking about it. It's all our own bespoke boards. It's all our own bespoke designs of optics, of camera systems, of radio systems. We do leverage chips. At the chip level, we're leveraging the latest quad-core computer. We're leveraging the latest WiMAX Wi-Fi components and so on. So we leverage at the chip level, but we've got our own designs at the subsystem level. You're leveraging those chips, but we're totally our own radio design and they're vastly more capable than anything you can buy online. We can get 1.6 gigabits a second over a thousand kilometer range from our little satellites to these little dishes that we've built all around the planet, 48 ground stations.

• 43:55Speaker 02

  I can't believe we can get 1.6 gigabits a second at a thousand kilometer range with these radios, but that's how much effort we put over 10 years now, building the better and better radio systems. I can tell you that about every subsystem, the camera system, the telescopes, the power systems, all the makeup. Yes, we buy the chips if you like, but the integrated system is really complicated at the subsystem level and it all has to work together.

• 44:20Patrick O'Shaughnessy?

  How should we think about complementary space curves that are compounding in the same way? Maybe rocket launch is the obvious one. What are the other like driving tech improvements that are riding one of these kind of Moore's Law like trends that are interesting and important that will affect the space renaissance beyond imagery?

• 44:38Speaker 02

  I already mentioned that rockets have come down in cost about 4x. Satellites have increased in cost performance about 1,000x over the last five to 10 years. That's already pretty dramatic, right? Very few industries go about 1,000x change in cost performance over a few years. That's like the mainframe to desktop computer transition in computing. This is like the internet moment. There's a lot of opportunities, but it's really complicated. Like I said, it's not for the faint of heart. I would say that rocket piece is quite distinct from the satellite piece. The satellite piece has been driven by Moore's law and general mineralization of electronics. Whereas the rocket piece is just Elon's will to have a reusable rocket. And that's enabled reusable rockets. And that's kind of amazing, but it's a different trend.

• 45:23Speaker 02

  But I would say, again, the thousand X is what's dominating here. They are compounding. So we have a four thousand X in cost reduction overall, if you like. But the thousand X is what dominates. And that's really about the mineralization of satellites. That's taking bus size satellites and making them the size of a loaf of bread with the same sorts of capabilities. That's staggering. And that's what's really unleashing, as I said, the upshot of what's happening in space is massive new data sets that we collect about the earth and transporting around the earth in the case of Starling and ourselves respectively. And that's enabling new and better economic systems, more sustainability. And that's why I'm excited about.

• 46:04Patrick O'Shaughnessy?

  As you go up the stack and more and more of the business is about pre-processed analytics that become more and more valuable, like getting further away from data and closer to knowledge or information, however you want to describe that change moving up the stack. Will you then think about almost open sourcing some of the data at the bottom of the stack? Like, it strikes me that if this was a nonprofit and you just made this all publicly available, stuff would get built on top of this that would be fascinating if there was no friction or cost to doing it. How do you think about that?

• 46:34Speaker 02

  I don't think that's the right strategy. I think that the data always has value. And by the way, there's another data company around the corner. It's called Google. And but you will notice they have open sourced a lot of their algorithms, their analytics, TensorFlow, the computer vision modules, this and so on. They haven't outsourced, open sourced any of their data. There's a real reason for that. The data is where the value is. Algorithms alone have zero value. Data alone has a lot of value. The Economist quipped that data is the new oil. Obviously, there's good things and bad things about that analogy. I don't think that data is dirty like oil, and I hope not. And by the way, oil can only be used once, you know, any bit of oil. Whereas data, you can pass off to lots of users. So there's an inherent better business aspect of data.

• 47:18Speaker 02

  But in this sense, that data powers, like oil does, a lot of different sectors. You have to refine it before it's useful to them. And it even could get commoditized, but still has huge value. I think that's where we will end up with data. Those that have the best data are going to drive the world and algorithms are super important. They're going up the value, but without the data, you can't do shit there. And with the data you can, and so the power is in the data. It's very asymmetric.

• 47:47Patrick O'Shaughnessy?

  Do you anticipate that a lot of businesses build on top of you almost API style? Like you would build on top of Twilio or Stripe? And is there a good example of that already?

• 47:55Speaker 02

  Yeah, the second part I was gonna get to, but answering your previous question is I think that we do want to democratize it so that as many people can use it and build those apps. But rather than give it the data for free, we will still charge the data. But we do want to make it easier and easier to do that in small amounts, get going in an easy way. You have a free trial, but we want to enable them with the tools that can get going. You can imagine an SDK and thousands of apps being built on top of this data. We are building that right now, and that's why we're going public is to have the capital to do this. The other reason, by the way, to get to another question you asked earlier, is that a lot of people still don't know about Planet. You know, you've seen visually just a tiny bit shocked by the story. And a lot of people are, when we tell people about it, they're like, holy shit.

• 48:39Speaker 02

  No, this is gonna be amazing for my industry, whatever your industry is, hedge funds, insurance, whatever. Most people still haven't heard of it. You know, I'm telling the story the first time to a lot of people. Okay, was the other advantage of going public is we're going a bit more on a bigger stage. It's not the only reason, and that was the only reason I don't think it would be worth going public. But I do think that's a good reason for going public that is a side benefit.

• 49:02Patrick O'Shaughnessy?

  Will, this has been such a fascinating conversation. I wish we had hours more to learn about what you're doing. I ask everyone the same closing question. What is the kindest thing that anyone's ever done for you?

• 49:11Speaker 02

  I should think about that more, but the first thing that comes to my mind is mentorship. I've suffered, it has some incredible mentors that helped to guide me to where I am today. My PhD supervisor last year won the Nobel Prize in Physics, so you're just an amazing guide. And my head boss at NASA, who helped me to understand space systems and lots and give me a lot of freedom. And I think of people that have mentored me, that was a gift.

• 49:37Patrick O'Shaughnessy?

  Will, this has been fantastic. Safe travels today. Pleasure to meet you and learn a lot about Planet.

• 49:42Speaker 02

  Thanks. Bye bye.

• 49:44Patrick O'Shaughnessy?

  If you enjoyed this episode, check out joincolossus.com. There you'll find every episode of this podcast, complete with transcripts, show notes, and resources to keep learning. You can also sign up for our newsletter, Colossus Weekly, where we condense episodes to the big ideas, quotations, and more, as well as share the best content we find on the internet every week.