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Inevitable
AI Hits a Power Wall. Starcloud Launches Data Centers Into Orbit
00:36:11
Philip Johnston is co-founder and CEO of Starcloud, a company building data centers in space to solve AI's power crisis. Starcloud has already launched the first NVIDIA H100 GPU into orbit and is partnering with cloud providers like Crusoe to scale orbital computing infrastructure. As AI demand accelerates, data centers are running into a new bottleneck: access to reliable, affordable power. Grid congestion, interconnection delays, and cooling requirements are slowing the deployment of new AI data centers, even as compute demand continues to surge. Traditional data centers face 5-10 year lead times for new power projects due to permitting, interconnection queues, and grid capacity constraints. In this episode, Philip explains why Starcloud is building data centers in orbit, where continuous solar power is available and heat can be rejected directly into the vacuum of space. He walks through Starcloud’s first on-orbit GPU deployment, the realities of cooling and radiation in space...
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- [00:00]
A
Today on Inevitable, our guest is Philip Johnston, co founder and CEO of StarCloud. AI is flipping an old model on its head. Instead of asking, where can we fit another data center, organizations are beginning to ask, where's the power? And how do we bring compute there? Bitcoin and crypto helped pioneer this idea by chasing cheap, stranded energy. AI is now following the same pattern, looking for cleaner, cheaper, more reliable power as fast as possible. But what happens if you take that logic to the extreme? If the constraint is clean, reliable, 24. 7 power, where can you find effectively unlimited solar energy with no sighting fights or interconnection cues? Space StarCloud is built around that question. Instead of forcing more data centers onto already stressed grids, they're exploring what it looks like to put compute directly in orbit, where solar is continuous and heat can be rejected into the vacuum. It's a sharp reframing from delivering more power to data centers to bringing data centers to power in the most literal way possible. There are smart people who see this as a promising direction for AI infrastructure. Google SpaceX and many others are actively working on it. And there are others who question whether cooling, radiation, and communications constraints make it fundamentally impractical. I don't know who's right, but it's a debate worth having in the open. Philip and his team are among the first actually trying to build this future. So let's get into it from McJ. I'm Cody Sims, and this is inevitable. Climate change is inevitable. It's already here, but so are the solutions shaping our future. Join us every week to learn from experts and entrepreneurs about the transition of energy and industry. Philip, welcome to the show.
- [02:14]
B
Thanks so much for having me.
- [02:16]
A
So I had a fun surprise this morning, which is I opened up X or Twitter or whatever we want to call it these days, and the very first tweet I saw, as is often the case, was Elon. And what Elon was doing is he wrote one word, which was, yeah. And in that, yeah, he was retweeting you. And what you were saying was you were quoting Gavin Baker, who's a very respected deep tech investor, who had said that the most important thing in the world over the next three to four years will be putting data centers into space. And so I thought I'd start with that conversation. What was it like to wake up, I guess, a day or two ago and had your tweet on this topic quoted by Elon Musk himself?
- [03:00]
B
It's kind of crazy being retweeted by Elon, because immediately I got 4 million views and I think I got like 4000 follows or something on X and like a bunch of messages and all this kind of stuff. It like blew up my X feed for a little while.
- [03:15]
A
Anything that like has come out of it that's actually been, you know, useful or helpful or I guess just awareness in general probably.
- [03:23]
B
Awareness in general is always helpful. Nothing in particular at the moment, but yeah, it's definitely helpful for the awareness in general.
- [03:30]
A
We're going to jump right into what you guys are building and what you're doing. But it begged the obvious question to me, which is like, is SpaceX going to go try to compete with you in data centers for space or grok? I guess to that end I'm sure you give that a lot of thought. Is that something that you have to worry about?
- [03:47]
B
I'm not sure competing with us is the right word, but they're very explicitly trying to deliver hundreds of gigawatts of orbital data centers into 100 gigawatts per year within a sort of five to ten year time frame. So that is exactly what we are also trying to do. But it is by far the largest market opportunity of all time, times a billion. So I don't think there will just be one company doing it. All of the other hyperscalers are going to realize in a couple of years if we don't have auto compute, we cannot scale anywhere near as fast as somebody that does. And at that point either they pay for compute from SpaceX, which is possibility, or they build it themselves, which is also a possibility, or they partner with somebody who has that capability. And at which point I think we've become an interesting partner. As you mentioned, they SpaceX will have a lower cost base than us because they own the launch, but we will have a lower cost base than all of the hyperscalers. And the hyperscalers that don't have a space ARM are Microsoft, Meta, Oracle, Google. On the neocloud front, Crusoe, coralweave, Lambda. So all of those guys are going to find themselves in a predicament quite.
- [04:52]
A
Soon to basically everyone but Amazon with Blue Origin, I suppose. Let's take a step back, maybe describe what star cloud is.
- [04:59]
B
Yeah, starcloud is building data centers in space. Initially we're providing cloud on edge services to other spacecraft, particularly DAW and commercial Earth observation constellations. And then later, in a sort of three year time frame, we're aiming to compete on energy costs with all data centers terrestrially. That is when we have a lower launch cost with Starship.
- [05:22]
A
And you have prototype up in orbit today.
- [05:26]
B
Yes, we just launched our first spacecraft a month ago. It has the first Nvidia H100 on board, which is about 100 times more powerful sort of GPU or AI compute than has been in space before. And yesterday we did some press releases around that and we've trained the first model, we trained Nano GPT from Andrej Karpathy and he retweeted that as well. We ran the first version of Gemini in space. So the satellite is now talking to us in the summit at chatgpt Mike and we're about to do a bunch more demos. So we'll be running high powered inference on synthetic aperture radar data. So SAR data from Capella and some more demos and some more actual paid workloads from government customers. And then next year we're launching our second spacecraft, the StarCloud 2, which will have 100 times power generation of the first, by far the largest sort of commercial deployable radiator in space. And a whole bunch more H1 hundreds, the black hole chip, some other chips, and yeah, no one will be commercial.
- [06:22]
A
We're going to spend some time diving into, you know, unpacking little bits of everything you just laid out. But before we do that, maybe walk us through how you got the notion to start this in the first place and decided that you wanted to be audacious enough to pursue it.
- [06:37]
B
I mean, I've been sort of fascinated by spaces for a long time. I also previously had another company and decided when I do another company, it would be in something I'm sort of passionate about and I think could have a big impact. A few years ago I went down to Starbase Texas, you know, where SpaceX is building the Starship program. While the launch vehicle itself is very impressive, you know it's going to lower the cost of launch by between 10 and 100x. What's really much more impressive to me at least, was seeing the factories they're building down there. These two starship gigafactories. So yeah, launch costs might come down by a lot. What's more impressive to me is launch capacity. A tonnage per year that we can get to orbit might go up by a thousand X or more. And the reason is these two starship gear factories can produce three starships per day. Each one is reusable, so that capacity builds on itself. So unlike with Falcon 9. You know, with Falcon 9, if you've got a new one every day for a year, at the end of the year you still only have one Falcon 9. Upstage because, because it's dependable. Whereas with Starship, if you build a new one every day for a year, at the end of the year you have 365 starships. Each one has far crime squared crafts.
- [07:40]
A
For the non SpaceX sort of deep experts listening, including myself, maybe unpack the difference between starship and Falcon 9.
- [07:47]
B
Falcon 9 is a word you might have heard before. Falcon 9 just means what almost all mass orbit gets to space on right now. So it's the workhorse of getting stuff to orbit. It's run by SpaceX. It's the first one that has a reusable booster, but it still has a dependable upstage. So every time they're throwing away $10 million or more on this upper stage. With Starship, it's completely revolutionary because it's the first one that has both a reusable booster and a reusable upstage. It's incredibly hard engineering challenge because you have to make that one re enter. But it changes the fundamental economics completely. Right now it's a bit like, you can think of it like if you were to fly from LA to New York and every time you landed you had to throw away the plane and rebuild a new one. Can you imagine how expensive the per seat ticket would be for that flight? That's currently what happens with space travel. Soon it will be like you land and the plane can take off and go back again and take off and go back again. And it lowers the cost by, you know, maybe a thousand times because this thing is reusable. That's what's coming down the line is with the Starship program is fully reusable launch vehicles.
- [08:48]
A
Okay. So basically with Starship you're building almost the equivalent of a space shuttle, but you know, one that has all aspects of the rocket as part of that shuttle that goes up and down. So the boosters and everything are all.
- [08:59]
B
Connected or usable and connected.
- [09:02]
A
Yeah, we haven't featured much on the show in the space ecosystem at all. This is where the entire sort of space tech world is looking toward where we can start to launch and take more things into space at a dramatically lower launch cost than they are today. By using SpaceX essentially as shuttle to get up and back from there.
- [09:24]
B
Yes, correct.
- [09:25]
A
And so for you, that allows you to get a greater set of data centers into space. But back to my question at the beginning about, you know, competing with SpaceX like they get the transport for free, Right? So you're still sort of navigating the cost of transport.
- [09:40]
B
Yeah, we are a customer of SpaceX. So we will have a higher cost base than SpaceX and we will have a lower cost base than every other hype scale.
- [09:47]
A
Getting back to the macro question, you saw this happening and then what triggered you to think, oh, there's an opportunity for data centers here.
- [09:55]
B
So the point of being in Starbase, seeing the factories, it got me thinking of these sort of sci fi concepts that I remember reading about as a kid. I think Asimov in the 40s was writing about space based solar, which is this idea where you have these huge solar panels in space and you beam that power down somehow, which is a nice idea. And there is a break even launch cost where that makes sense. The problem with it is you lose sort of 90 to 95% of the energy and transmission from space to Earth. And so rather than beaming that power down, if you can find a cheap way to get the consumption endpoint to space, which in most cases, almost all new energy products on Earth right now being built to power data centers or net new anyway. And so if you can, instead of beaming the power down to indirectly or directly plug that into a data center, if you can move the data center space, you don't lose 95% of the energy. And so instead of the break even launch cost being around $50 a kilo, which is what we think it is for space based solar, you have a $500 a kilo break even point where it makes sense for data centers in space.
- [11:00]
A
And that's mostly recouped through cost of power. And I assume I've heard you kind of mention cost of cooling as well as being the other big cost savings side of things, is that right?
- [11:10]
B
Correct.
- [11:11]
A
So rather than assuming why space is different, let's start with the constraints around Earth. So what are the constraints that a data center has on Earth today that you maybe thought, oh, this could be different.
- [11:25]
B
Primary constraint is power, a secondary constraint is calling, but cooling is kind of a function of power. And when I say power, what I mean is if you construct a new data center, assuming that the grid is at capacity, which currently is mega over capacity, then you need to also at the same time construct a new energy project. Building a new data center is fairly easy, doesn't require too much permitting or any of that kind of stuff. Building a new energy project requires ridiculous amount of new permitting. So you can have like a five or ten year long lead time on a new energy project to that scale, be that nuclear or solar or hydro or any sort of new form of energy. You're looking at decades of lead time in permitting for that.
- [12:11]
A
So particularly it's not specifically power, but time to power I think is probably the big constraint.
- [12:15]
B
Right.
- [12:16]
A
And so for sure, time to power, interconnect permitting, all of that is the huge lead time right now. It's a much greater lead time than the actual physical construction of a data center. And then talk about the cooling and water side of things as well. I assume that's also an area where there's maybe some differences in what you can do in orbit.
- [12:37]
B
Ideally, data centers on earth use water for cooling because it's much cheaper than using air to cool if it's particularly depending on where you are in the world. But if you're in a warmer place, like in Texas or somewhere, then using water is way more efficient than using air. Actually, the amount of water you use in the actual data center for cooling is less significant than the amount of water you would use. If you're for example, building a new coal fired or nuclear power station, what they have is these enormous evaporation towers for cooling that actually uses the bulk of the water versus the actual keeping the data center cold. You know, they both consume quite a bit of water. So that's the main constraint there.
- [13:19]
A
Now you had the aha that maybe space can help with minimizing these constraints. Let's talk about each of those. So maybe start with energy. Talk about solar in orbit and what that looks like.
- [13:29]
B
So we run enormous solar panels which can generate. On our website we have a concept video of 5 gigawatt 4 kilometer by 4 kilometer solar panel. The one we've got in orbit right now is a 1kW peak power draw. The next one will have 10kW, although much more solar than the first because the first is running on batteries. A lot of time. For the third version, which is 100 kilowatts, you're looking at sort of tennis court sized solar arrays, you know, reasonably decent sized solar arrays. And then we scale up from there essentially and yeah, we get unlimited low cost energy in the form of solar in that way.
- [14:03]
A
In terms of power production, are there any valleys in power production in space? Does anything about the shape of orbit impact the ability to produce power, or are you 24 by 7 power production?
- [14:16]
B
It kind of depends which orbit you're in. But you can fly in what they call a dawn dusk sun synchronous orbit at around 1200 kilometers. Then you have 24,7 solar. And what that actually means is 1 square meter of solar panel in space over the course of a year will produce eight times the energy of one square meter of solar panel on Earth because you don't have seasonality, you don't have day night cycle, you don't have attenuation in the atmosphere. I mean that's one of the big cost savings is less solar panels. It's the third cost saving actually. So you're asking the right question. We should compare a terrestrial solar project with a solar project in space. Terrestrial solar has three big costs. One I first I've talked about already, which is cost of permitted land, biggest cost in North America it can be. Second is the cost of battery storage because you have a day night cycle and you need to charge batteries so you still have power night. And then the third is the cost of the solar cells themselves. So for number one, we don't need permits of land biggest cost gone. For number two, we don't need battery storage. So second biggest, Costco. And then for the last 1 we need 8 times less solar cells. Since 1 square meter of solar panel produces 8 times the energy of in space, the only additional cost we have is the launch cost or the main additional costs. All of the other costs are roughly either cheaper in space or the same. So the launch cost you can see is there's a break even point where the launch cost is below the cost of permitted land batteries. 18 the solar or 8 times the solar. And we see that break even point to be around $500 a kilo maybe.
- [15:38]
A
Describe what the solar arrays look like. This is a different kind of PV than you would have terrestrially, is that right?
- [15:44]
B
Used to be space companies used to use what they call gallium arsenide cells, which is ever slightly more efficient or it can be 50% more efficient. So instead of having 20% production of energy or useful transformation of sun to electricity, these gallium Austenite cells have 30% on a good day. But that is going out of fashion and people are just using bog standard terrestrial silicon cells. And the reason is if you're less mass constrained, which you are now with things like Starship Falcon 9, then you don't care about that given the cost increase. So gallium arsenide is about 100 times more expensive per watt than terrestrial silicon cells.
- [16:25]
A
What about radiative damage? Do you worry about decay from no atmosphere getting in the way of the sun's radiation?
- [16:33]
B
Depends where you fly. If you're flying at the 1200 orbit, you'd need most likely sort of COVID glass because it's much higher radiation in the lower altitudes. It's not quite as bad. And you can have much thinner film coverings.
- [16:46]
A
You mentioned the size of these arrays. You said for 100 kilowatt system you're at a tennis court sized solar array, roughly, is that correct?
- [16:53]
B
Slightly larger than ever.
- [16:54]
A
Yet how does that compare to what's been launched successfully into space today? The International Space Station, for example, I assume has a substantial amount of solar array on it, though I don't know how modern those panels are at this point.
- [17:09]
B
In aggregate, by far the most plentiful energy production in space right now is on Starlink. So each one of their Starlink V2s, I don't have the exact number, but I would guess it's in the 5 to 10 kilowatt range. V3 they're saying is going to be 20 kilowatts. The V3 is probably more than the entire International Space Station. So the radiating on the ISS dissipate around 70 kilowatts, but some of that is also just dissipating the energy from the sun.
- [17:37]
A
So these hundred kilowatt arrays, a size of a tennis court roughly are, you know, sizable. How many Nvidia chips are you able to run on that amount of power production?
- [17:49]
B
Well, with the blackwall chip, they're approaching 1 kilowatt per chip.
- [17:53]
A
So 100 or so per instance, I guess. Or do you imagine your panels scaling up even larger than that? From a volumetric perspective, what you're constrained.
- [18:02]
B
With for that Starling V3 is the launch form factor, which is we're going to be launching out of the starship Pez dispenser, which is like this, like stack that shoots stuff outside. I don't know if you've seen that. So you are constrained on volume and mass per individual satellite. And I would imagine you can probably get to about 150 kilowatts, but you can't really go above that per satellite.
- [18:29]
A
So I'm trying to think. So if you can get, you know, roughly a hundred chips, it sounds like on kind of one instance, help me paint a mental picture of what that looks like today. Compared to a typical data center, which are massive, like thousands and thousands of chips, you're sort of at a different order of magnitude here.
- [18:45]
B
I would assume per launch you're at a similar order of magnitude because each starship, let's say they can each take 50 Starlink V3 form factors. So you're talking about 5 megawatts per launch, basically. I expect that that can probably scale up as well.
- [19:01]
A
Okay, so let's move on to the second area you talked about which is cooling. So in space, you're at basically absolute zero. I assume when you're on the dark side of anything you do, is that true? Or does an object in orbit start to generate its own heat as it faces the sun?
- [19:18]
B
So even when you're on the dark side of the Earth, even when you're in Earth's eclipse, you actually get a lot of infrared from Earth. That's one thing. You're probably not going to be absolutely zero unless you are very shaded from both the Earth and the back of the spacecraft and the sun. And also, yeah, it's not absolutely. It's about 3 degrees Kelvin, but you definitely absorb a lot of heat from the sun. What's interesting and what most people don't realize is you can actually emit about 80% of the waste heat in terms of wattage towards the sun as you can away from the sun. So if the sun is like here, and the spacecraft is a flat panel here of solar panels and radiators, you're running radiators here, you can emit about 80% this way than you can emit that way. And the reason is most of what you're emitting to is not sun. Most of what you're missing to is deep space.
- [20:04]
A
How are you expelling the heat where you don't have sort of any evaporative property? I assume because you don't have atmosphere.
- [20:13]
B
All of our heat loss must come through infrared radiation. So as you mentioned, we don't have the two ways you keep a data center cold on Earth is either water past the chips or cold air. And we don't have either water or cold air. So we have a liquid that goes past the chips and then it goes out to this radiator. And then that radiator emits in infrared the heat.
- [20:35]
A
The radiator emits its own infrared.
- [20:38]
B
Yeah. So, I mean, everything is glowing in infrared all the time. Like, if you had a thermal camera on your face, you'd see that your face is glowing in infrared. When there's a temperature differential, even in a vacuum, when there's a temperature differential between two bodies, one will be emitting infrared towards the other. And so that's how it works, essentially. Like, our radiator will be just glowing in infrared if we keep it at about 50 degrees C. And that will get rid of the heat.
- [21:01]
A
So those are some of the key differences when you talk about the constraints that Earth already has and how you would be different in space. But then space introduces obviously its own constraints as well that are very unique. Maintenance obviously becomes significantly greater challenge. I assume security is a totally different challenge. It's less around physical security and more around your ability to prevent malicious hacking. I guess of the devices and penetration protection in that regard. Maybe describe some of the constraints that you're having to think about that, you know, a Earth born data center developer is not having to navigate the two.
- [21:37]
B
Big engineering constraints that I mentioned. One is the dissipating the heat in a vacuum, so building radiuses. The other is making the chips work in a high radiation environment. And so that's a combination of shielding and software. The other constraints are. Yeah, you mentioned security. So we will have encryption in the same way that a Starlink satellite has encryption, essentially. There's also some question around physical security. It's actually much harder to blow up a data center in space than it is to blow up a data center in Virginia, which is where most data centers in the US are. So that's not as much of a problem as people think.
- [22:10]
A
What do you think is the constraint that is most misunderstood by people coming at it from a Earth born lens?
- [22:17]
B
I would say the thermal challenge is most misunderstood. There's like three layers of understanding for the thermal. There's the first layer which is oh, space is cold, like you can put a data center there. And then there's the kind of mid whip meme which is space is a vacuum. There's no convection or conduction, it's impossible, you need to run crazy sized radiators. And then there's the sort of like God mode meme where it's like, okay, but there comes a point on Earth where you literally can't spew out more waste heat, otherwise you're going to be boiling the oceans. Actually one of the key advantages of space is we can scale almost indefinitely with radiative infrared cooling. And on a long term basis that is actually one of the key constraint on scaling data centers on Earth is waste heat. So it's misunderstood on a few different levels, let's say.
- [23:04]
A
Well, I'm glad I led with the midwit question. Amazing. So with all of this, what stays hard as the cost of launch sort of decreases and everyone who's trying to do this has access to launch vehicles. Basically what ultimately becomes your moat. If the GPUs are something everyone loosely has access to and launch is something that anyone can pay for, how do you stay, you know, sort of ahead of the package?
- [23:35]
B
The core IP we're developing right now is, I say, around cooling and radiation shielding and hardening. Over time, it wouldn't surprise me if the Chinese get very good at manufacturing low cost and lightweight radiators. People will not be able to use Chinese satellites for data processing. So I think we have a moat against Chinese and we can use their components. But yeah, we're just moving way faster than AWS in terms of innovating new solutions for this stuff. We completely ripped Apollo H100 that we've got in space. We cut 80% of the mass from it, removing the heat sinks, power subsystems like AC to DC converter, the casing and everything, immersed it in this liquid cooling thing. And there's a lot of new development that went into that, making that H100 working space. And I think our, like any startup, our core moat for now is that we have the best engineering team in the world moving fastest.
- [24:25]
A
You mentioned at the very start of our conversation, the current use case in space is for using actual space data. So it's pulling, I assume it's running inference loads off of data that's collected in space and helping to draw conclusions from those so that you're not having to deal with the sort of latency of sending large training loads up from Earth or sending on demand inference loads back down to Earth. Am I following that correctly?
- [24:52]
B
Correct.
- [24:52]
A
Give me some examples. What do your initial customers look like?
- [24:56]
B
So anybody that needs to get information about what's happening on Earth down quickly. And so the bottleneck right now is you have to wait for a ground station and then let's say you're taking imagery of the Straits of Taiwan. You want to know is a ship left China towards Taiwan? What happens right now is you, because these satellites are not fixed above the Earth, they're orbiting pretty fast. So you take an image of Straits of Taiwan, then you have to wait for it to pass a ground station, and then you have to downlink imagery of the entire Straits of Taiwan, which is maybe many hundreds or hundreds, hundreds of terabytes or gigabytes or whatever. You're not going to get that information back quickly. When we're in space, people will be able to ship that data to us with an optical terminal. So we will fly three optical terminals on our second satellite, either directly or through a backhaul network. And optical in space has much higher data rates than from space to ground, because space to ground is RF and optical is just way, way higher data rates. So we can then run inference on that imagery on orbit, and then we can just downlink in real time the insight from that. And the insight might be there Is a vessel in this location or it might be there's a wildfire in this location or it could be a ship has capsized and there's a lifeboat here or you know, things that you'd be interested in. The latency sensitive. Yeah.
- [26:09]
A
Do you need to be line of sight to whatever satellites are collecting said data in order to do that or is there a cross link capability in space that is still faster than having to deal with uplink downlink connection to Earth?
- [26:23]
B
There is three crosslink options coming online very soon. That would be one way of doing it. The other is when we have several of our own or more of our own spacecraft, then the idea would be that at least one of them is in line of sight of our customer satellites.
- [26:40]
A
Do you envision a world in the future where there is substantial uplink downlink from Earth and you actually are running, you know, either inference or training data centers in space or is that pretty far out there is a large enough market right now just on space based intelligence calculations that there's a near term opportunity here?
- [26:59]
B
Yes, I envision that world. That world is coming extremely fast. SpaceX is talking about building a hundred gigawatts per year of computing space. That's like the entire US power grid in three or four years. So that is coming. I mean they're not joking when they say that.
- [27:13]
A
So talk about where you are today then. You've got an initial prototype running in space, as you said. You've got the first set of Nvidia chips actually running inferences in space today. What did that look like, when did that go live and what's next?
- [27:27]
B
Sure. So we launched our first spacecraft in November 2nd, five weeks ago now with the first Nvidia H100 onboard, 100 times more powerful GPU compute than has been in space before. We've trained the first model in space from Andrej Karpathy, this Nano GPT model. We, we have run high powered inference on imagery and also we're running a version of Gemini on this more entertaining demo. It's an amazing compliment of the team, to be honest, because most people say that you couldn't run an H100 in space even a few months ago. And we've proved that you can.
- [27:58]
A
And you've announced a partnership recently with Crusoe. That's how I originally came across you guys. Was, I was reviewing some documents that I had access to from Crusoe and I saw your name in there and I was like, who are these guys? Reached out to you and you know, since then You've launched your initial prototype into space and you've announced this Crusoe partnership. So maybe share a little bit about what that looks like.
- [28:16]
B
So with Crusoe, been many speaking with Kali, one of the co founders and president there. And we've announced two partnerships actually. The first one is we will be running a version of Crusoe cloud on our second spacecraft next year for later iterations. We've come to an agreement to provide them with power. So up to 10 gigawatts from the early 2000-30s of power. And essentially the way that would work is we don't really have any ambition in building our own cloud because you know, these guys have been doing this for decades. It's their core business. Have a great offering. Our core business is essentially being an energy provider, a low cost energy provider. So we will give Crusoe a box that has power calling and connectivity. They can put whatever chip architecture they want in that. They sell that to their customers or whatever rate they want. We give them power at $0.03 per kilowatt hour and for that we can very easily cover the cost of launching, designing, building and all the rest of it.
- [29:13]
A
Ultimately then are you a power seller? Is that the business model for Starcloud?
- [29:20]
B
That's definitely one end state of the business model. People can put whatever chip architecture they like on us and we essentially sell power. Power calling connectivity.
- [29:28]
A
Your power would be, you know, sort of all in to the cost of launch, the cost of maintenance of said spacecraft and the cooling and everything else. But you're basically selling them an all in cost of power for them to run. And then do you manage and operate the spacecraft then?
- [29:47]
B
Yeah, we'll be managing operating the spacecraft. What they choose to do inside that box is up to them. They need to make sure that they don't require at least for the first few spacecraft, we're not going to have too much maintenance capability on there, so some redundancy on some of the critical systems and over provisioning over time. The whole industry is moving towards robotic maintenance and we see that as the way it's going as well.
- [30:07]
A
So it sounds like the big benchmark that matters the most for you then is dollar per kilowatt hour for gpu. Is that ultimately what you need to solve for?
- [30:15]
B
Yes.
- [30:16]
A
Is there a different business model where you are selling hardware to other people to run and operate these or is that, I guess probably still to be determined. You're pretty early in the path here.
- [30:27]
B
We are developing very useful ip, let's put it that way, for Example, any high energy use case in space is going to require being able to dissipate heat in a vacuum. So things like asteroid mining, refining of materials in space, manufacturing on orbit, space hotels, all of these types of things will require dissipating large amounts of heat in a vacuum, for which you will need a very large, low cost and low mass deployable radiator, which is the core IP that we are developing. So if somebody just want to buy that as a component, I can see a world where we start selling that as well.
- [30:59]
A
So now going back to our original conversation, the reason why you guys would exist as a standalone company relative to SpaceX and Starlink, it sounds like, is yes, they're going to always be cheaper to launch and get something into orbit, but you are laser focused on just this particular problem and this particular use case. So you will be always optimizing around operating these data center spacecraft in space. And B, there are going to be plenty of hyperscalers and others who don't want their actual inference loads being managed and run by SpaceX. Is that sort of the core story of StarCloud?
- [31:39]
B
That is a actual summary, yes.
- [31:41]
A
And I guess lastly, you know, just to complete the loop here, talk about your background. What were you doing before this?
- [31:48]
B
So my background is I started my career for the first five years on the engineering side and software. Before that I studied applied math and theoretical physics, undergrad and masters, and then I moved to the more commercial product side of things. I was with McKinsey for a few years working with the space agencies of various governments and then founded and sold another company and then started on this two years ago.
- [32:09]
A
Describe a bit about the company's path so far. I think you guys went through yc, you've raised a bit of funding from some notable investors. Where are you to date?
- [32:19]
B
Yeah, we started January last year and then in June we went through Y Combinator. To date we raised about 34 million and it will potentially look to go out for a series A in Q1 next year.
- [32:31]
A
I mean, that's a pretty amazing accomplishment for a small team on relatively little capital raise too, for what you've accomplished. I guess the last question I would have to ask you is what would be true for StarCloud to not work? There have been some critics out there who've pointed out all these reasons why your solution may not be credible from a cooling perspective, from a power perspective, et cetera. There's a NASA scientist who wrote some piece recently talking about a bunch of critiques of things he's seen in his career. Maybe talk a little bit about some of the critiques and where you believe they maybe fall short from your perspective.
- [33:09]
B
There's some pretty thoughtful analysis of what we're doing. They often point to the cooling. I think that's solvable. If there was to be a 10x reduction in energy costs on Earth for some reason for the next 50 years, that would probably mean we are not a viable business. I would say if you extend life out on a sort of more cosmic timeframe, like let's say even just a thousand years, there is zero possibility you can continue to scale compute on Earth. So at some point you definitely have to figure it out. Where that timeline is is up for debate. If the cost of energy on Earth were to come to 0.2 cents per kilowatt hour, and that may be the lowest forecast cost I've ever seen for fusion is $0.20 per kilowatt hour. And that's from Helion, and they're kind of the most incentivized to give a low forecast. So it doesn't look like it's going to happen anytime soon. But that would be one thing that would certainly stop us from, from being viable. If for some reason the demand were to stop growing, I think we would probably not replace existing data centers on Earth. Is only if you need new data centers that you would be building this in space. So if there was to be a massive drop off in demand growth, that would mean we are not super useful at that point. Thermal is completely solvable, as is radiation. So yeah, I wouldn't say that's one of them. I mean, if the launch cost were to take a very long time to come down as well, that would also be a problem.
- [34:28]
A
What do you think the next five years looks like?
- [34:30]
B
I'll say in 10 years. In 10 years, I think most new data centers will be being built in space and that will still only be maybe less than 1% of the total data center stock. But it will be a much faster growing proportion. In five years, I think we'll be at rate production. So I think we'll be producing at least tens of gigawatts per year of orbital compute. And then that will scale up to probably hundreds of gigawatts per year by the end of 10 years.
- [34:56]
A
One last question. Anywhere you're particularly needing help or areas where if our audience that's listening is excited that they can jump in and try to support you.
- [35:06]
B
On the hiring side, we're looking for electrical engineers, power, electronics and software. We're pretty good on the mechanical, thermal and spacecraft design type side of things.
- [35:16]
A
Philip this has been a incredible exercise for me just to think about something that forces me to think about the world differently. I appreciate you taking the time to join us and congrats on what you've achieved thus far. It's an amazing accomplishment for a small team. 12 people and excited to follow your journey and see what comes next.
- [35:34]
B
Thanks so much Cody. Really appreciate it.
- [35:37]
A
Inevitable is an MCJ Podcast. At MCJ we back founders driving the transition of energy and industry and solving the inevitable impacts of climate change. If you'd like to learn more about mcj, visit us at MCJ VC and subscribe to our weekly newsletter at Newsletter MCJ vc. Thanks and see you next episode.