Is that the idea?

Yeah, you got it.

So we're launching 20 satellites.

It's actually our fourth launch this year, and we've got another one coming up in a couple of weeks.

So it's exciting times.

Our teams are very busy.

Yeah, got 20 satellites on this one.

Does that take longer from space down to Earth than it would if you're running on a fiber cable on Earth?

What is this danger, as you say, that carries the existential risk for humanity?

Alignment is about whether or not the interests and goals of AI and the interests and goals of humanity are the same or different.

And right now, it doesn't matter too much because we're telling the AI what to do, so it doesn't really matter.

But there comes a point where if AI gets to a certain level of intelligence, it might decide for itself what to do.

There's a lot of debate about whether it can as a deterministic machine.

But Alan Turing himself said something like, we can expect that AI will take control at some point.

Alan Turing was the founder of AI.

Forget about all that stuff on this philosophical journey of humanity that we've been taking for the last, over this podcast.

Could you describe where you think AI is going to take us?

I think there's a new era of machine intelligence that I call planetary intelligence.

So let me do a little backdrop first.

Everyone's familiar with large language models now.

Incredibly powerful.

They've read all the books in the world and the text on the Internet, can write an essay, can hallucinate obviously sometimes, but they can do code.

I was testing some of those LLMs early on.

That sounds like a really great science fiction story where you train the AI to value the beauty of Earth and humanness in order to protect our long term.

Who are your customers, and how do you think about that problem?

So let me start with the customers.

We service customers in civil government, so that's agencies like NASA that buy it for science research, or it's the Brazil Federal Police that are trying to stop deforestation.

We work with commercial applications, so insurance, for example.

After disasters, instead of sending a person out to see if that farm or that house has been affected by the flood or the storm, they can just look at our imagery instead and save themselves a lot of time and effort.

And then there's defense and intelligence applications.

For example, we work with the US Navy monitoring the South China Sea, where they're tracking illicit activities, North Korean evasion of oil sanctions.

Do you think over the next fifty years orbital data centers are a long shot? A sure thing? Somewhere in between?

What's that mean?

Yeah, well, planetary intelligence to me is sort of a next era in machine intelligence.

Um, and it's all about building models of the real world, and of course AI model is only as good as the data set they're trained on, and we have gobs of real world, uh, data.

I think of it in two phases.

The first phase is combining planetary, uh, uh, sensing, which is already in space for all the obvious reasons, we've been doing planetary sensing space, um, with large language models to what I call large Earth models, um, which is, you know, wrapping up not just the text of the internet that's, uh, uh, embedded in LLMs, but all of Earth data so that you can ask physical questions about the real, uh, planet.

And the second phase in big arc terms is, is putting the compute up next to the sensors into space, and we're doing that too.

Uh, that's a bit further out, but that sort of led- leads to phase two of capabilities in, in, in this world.

Hmm

You and I have been talking about it for quite some time, but it does seem like the rest of the world is awakening to this idea that we're seeing this convergence and this confluence of AI and space right now.

100%.

I've been speaking for a while.

I mean, you were just talking in the previous segment about next frontier in AI models and how important that is.

Well, the next frontier in AI models is all about real world models and real world models need real world data.

It stands to reason, right? So the chat GBTs and Geminis of this world right now are mainly trained on the text of the internet.

That means they're very versatile about the text of the internet, but they don't know much about the real world.

So how far are we from fully, truly realizing this technology?

I, I would love for you to talk about that because I thought it was fascinating.

Yeah.

I mean, we help people do, uh, all sorts of, uh, things around the world.

I mean, even though we're having, uh, uh, the satellites are all in space-All of our applications are in the real world here down on the Earth's surface.

Um, we are helping farmers, we're helping energy companies, we're helping civil governments, we're helping security.

Um, but you asked about the, uh, uh, methane, and we, we track methane leaks using a special hyperspectral camera that we've got on one of our satellites, and we're launching a couple more of those this year.

But basically, this, this gas, methane, um, absorbs in a particular spectral line.

Yeah

So maybe Will, you start, and then Andrew, you start.

I mean, what we're seeing firstly in space is all these new applications based on data and AI.

So, you know, we're collecting vastly more data about the planet.

And with SpaceX and Starlink and OneWeb, they're transporting far more data around the planet.

As you say, we're sort of changing the nature of data using satellites.

And that's... basically doing what was once the province of governments only, and giving everyone else access to satellite capabilities.

And that's gonna, I mean, I estimate there's a 75 to 100 billion dollar market just on Earth observation, this kind of data we collect, and AI on top of that.

And so the next few years are gonna be really spicy.

Yeah.

I mean, firstly for the audience's benefit, what Planet does, we have satellites doing Earth imaging.

We have the largest Earth imaging fleet, about 200 satellites.

They image the entire Earth every day.

So think of it like the Google, uh, satellite layer on Google Maps that you can look at, except it's today's date rather than three years old, and we have every day going back.

So it's a time series analysis of everything going on on the Earth.

That's useful for farmers, it's useful for energy companies, it's useful for civil governments, uh, for flooding and fires, it's useful for security applications like you're getting at, and it's a wide variety of use cases.

Andrew, you start.

And so what was it like working at NASA, and what prompted you to leave?

Well, it was really fantastic.

I mean, honestly, it was obviously a childhood dream for me as a space geek, uh, wanting to, um, go work at NASA, um, do space exploration, do science.

I spent my time there working on lunar missions.

We sent a couple of probes to the Moon.

We found water on the Moon, which is a big deal, and it's very exciting now with the Artemis program going back there recently.

I was so inspired by those missions.

Discuss.

Uh, can you walk me through who, like, the breakdown of your customers? Is it-- how much is it government versus how much is it commercial?

Yeah.

Well, we split it sort of into three buckets.

Um, defense and intelligence, which is now the biggest area, which is where we're helping countries with security, monitoring for new threats, doing maritime domain awareness, as I said, so tracking ships, making sure they're not doing illegal things.

Uh, so for example, right now we're supporting NATO doing, uh, monitoring in the Baltic Sea, uh, for hybrid Russian, uh, warfare activities.

Uh, we're helping the US Navy monitor eight million square kilometers of, uh, the, uh, uh, South China Sea for illicit activities that the Chinese are doing and other things like that.

So that's what we call defense intelligence.

Yeah.

your time to answer.

I'm a continent away, so I don't have bio bits about Gavin to tell you about, but I will probably surprise you.

You called me a centrist.

I usually don't answer to that, but I get it why.

You know, but I like Gavin.

I met him when he was newly elected mayor of San Francisco, and he regaled me with hilarious stories of loony leftism in his city, which he had to combat himself.

day in and day out.

Could you actually speak to what you think to be kind of the pathway for a for, you know, Democratic victory in the midterms, but also for Gavin as president or any president that would actually come forward?

government can't do what you do or because the demand for what you do is on top of what the government does? Because I always think about satellite imagery as kind of a government thing.

Yeah, absolutely, and it always was for many decades.

But commercial space has taken off.

We've got lower-cost launches from the likes of SpaceX, and Planet has pioneered putting large numbers of low-cost satellites in space, enabling us to image the whole world every day.

It's an unprecedented capability that even the governments don't have.

It's very complementary to their... few, very exquisite satellites that cost billions of dollars, that have higher resolution.

But ours cover a much broader area, opening up whole new applications, including agriculture, finance, insurance, disaster response with civil governments.

It is possible.

We're going to wipe them out of business.

Well, you know, it would be very hard to do that because...

For one thing, we've got the best satellites up there that image more than anyone else, but also we have an archive of imagery going back in time now for that last eight years.

3,000 images for each point on the Earth's landmass.

Now, I know SpaceX is really good, but as far as I'm aware, they don't have a time machine to go back and get that.

Why that data set is really important, is that without that data, you can't train AI.

AI is all about the algorithms and the compute, but also the data you train it on.

You've always had an interest in the technology itself,

That's goo.gle slash workspace with Gemini.

We were at NASA, and I was in a little outfit that we helped to start called the Small Spacecraft Division, which was looking at how can we use small satellites, cheaper satellites, to do missions that NASA wants to do, exploration, science, and so on.

Initially, we had done a few missions.

I was involved with a lunar mission, a science team, this one called LCROSS that looked for and found, in fact, water on the south pole of the moon.

And that mission cost $79 million.

Now, by NASA standards, that's extraordinary.

Extraordinarily cheap.

What does that mean?

Now, I asked Planet CEO, chair and co-founder Will Marshall about the forecast.

We're putting out a plan that we feel very confident that we can hit.

It is a strong growth, but it's accelerating growth.

And what we can say is, as you mentioned, that we've got really strong increasing backlog.

Our backlog of business grew more than doubled quarter on quarter because of a lot of the deals we've been making.

It gives us not just the ability to give guidance for this full year, and we believe that's good, but then it also gives us line of sight towards strong revenue growth acceleration next year.

And we've even put out that we are able to have line of sight to get to positive cash flow in 24-month period as well.

Now, with NVIDIA forging further into space partnerships at GTC this week and Jensen Huang even touting future data centers from space, I asked Marshall about the role of Gen AI in Planet's business.