Years ago, when I first discovered Winchell Chung’s Atomic Rockets site and its list of common misconceptions about space travel, I was taken off guard by a simple point that’s obvious in retrospect:
Rockets got wings. If your rocket has a multi-megawatt power plant, an absurdly high thrust thermal rocket propulsion system, or directed energy weapons it will need huge heat radiators to purge all the waste heat. Otherwise the rocket will melt or even vaporize. Radiators look like large wings or arrays of panels. The necessity of radiators a real problem for warships since radiators are pathetically vulnerable to hostile weapons fire.
(Also, there ain’t no stealth in space, but that’s less apropos…)
Andrew Cavalier, writing in IEEE Spectrum, argues that orbital data centers are harder than Silicon Valley thinks:
Space is cold, but it also has no atmosphere. That means the best heat-removal mechanisms, conduction and convection, are off the table. The only option is radiation. To prevent a chip from overheating in space, a large, costly surface area is required to dissipate the energy and then radiate it.
Solar energy is abundant, but collecting it with functional solar panels that maintain perfect alignment toward the sun is a complex task requiring extensive attitude control systems. On top of that, ionizing radiation in space from cosmic rays and other sources poses a unique challenge, degrading the solar panels, the radiative coolers, and the chips themselves. Because regular maintenance in space is difficult, redundancy has to be built in at launch, and cost estimates have to account for efficiency degradation over time.
At ABI Research, where I work as an aerospace analyst, we did a rough total-cost-of-ownership comparison between a data center on Earth and one in space. It showed that the cost to launch and run a GPU in space for a year is at least an order of magnitude higher than the same feat in a terrestrial data center. Our model was simple, assuming an Nvidia H100 server rack launched with the requisite-size solar panel and radiator on a spacecraft akin to Starcloud’s pilot launch. We assumed SpaceX’s Starship was used at a highly optimistic launch cost per kilogram of US $44, and a terrestrial energy cost of $0.20 per kilowatt hour. This is a simple back-of-the-envelope calculation, but it does signal something real.
From our perspective, the cost of delivery and space hardening of the payload makes general-purpose space-based data centers difficult to justify economically today, despite the fact that data-center builders in many regions are scrambling for electric power. However, there are niche applications where the much higher costs of computing in space could be justified. Examples include preprocessing data from Earth-observation satellites, real-time detection and tracking of hypersonic missiles, and active collision avoidance in the increasingly crowded low Earth orbit. Even for these, though, contending with fundamental physics will still be a demanding challenge. And a technologically compelling one, too.
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To understand how big this baseline area is in practice, I used the Stefan-Boltzmann law to model the heat-rejection area needed to keep a single chip that draws 700 watts of power—such as the H100 GPU chip, an AI stalwart—at a constant 60 °C, usually considered the sweet spot for GPU longevity and stability. I further assumed that the radiator is perfectly facing deep space, at a chilly background temperature of 3 kelvins. By this calculation, a single chip would require 1.4 square meters of radiator surface.
To put this into perspective, consider that a common AI rack can hold approximately 32 GPUs (four H100 server boards). With CPUs, memory, and networking equipment, this rack would draw around 40 kilowatts of power. This single rack includes 2.5 terabytes of memory—enough capacity to serve over 20,000 concurrent users or run 16 simultaneous instances of Llama 3, an open-source AI model. But to cool this thermal load in a vacuum, that single rack would require an 80-square-meter radiator, roughly the size of a pickleball court. For an aggregate 100-megawatt data center, you’d need at least 2,500 of those radiators.
And that’s the best-case scenario. Additional problems are hidden in the low Earth orbit environment itself. Space exposes radiators and their coatings to a chemically hostile brew of ultraviolet light and atomic oxygen, quite the opposite of a clean-room environment. Over a LEO satellite’s typical 5-year lifespan, these elements degrade the radiator’s surface properties and lower its ability to shed heat.
Including this degradation in the model reveals that as the radiator degrades from a “fresh” state to an “end-of-life” state, the physics demands a further penalty. To maintain that same 60 °C operating temperature for the GPU chips, the required surface area jumps from about 1.4 square meters per chip to nearly 2.0 square meters. In other words, the physics tax rises by 40 percent. Therefore, you must launch at least 40 percent more radiator mass, endure higher atmospheric drag, and sacrifice valuable launch volume just to survive the degradation of the thermal coating. This increase adds significantly to the launch cost and further erodes the economics of a space-based data center.
When Dwarkesh interviewed him, Elon made the point that the availability of energy is the issue:
If you look at electrical output outside of China, everywhere outside of China, it’s more or less flat. It’s maybe a slight increase, but pretty close flat. China has a rapid increase in electrical output. But if you’re putting data centers anywhere except China, where are you going to get your electricity? Especially as you scale.
The output of chips is growing pretty much exponentially, but the output of electricity is flat. So how are you going to turn the chips on? Magical power sources? Magical electricity fairies?
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It’s harder to scale on the ground than it is to scale in space. You’re also going to get about five times the effectiveness of solar panels in space versus the ground, and you don’t need batteries. I almost wore my other shirt, which says, “it’s always sunny in space”. Which it is because you don’t have a day-night cycle, seasonality, clouds, or an atmosphere in space. The atmosphere alone results in about a 30% loss of energy.
So any given solar panel can do about five times more power in space than on the ground. You also avoid the cost of having batteries to carry you through the night. It’s actually much cheaper to do in space. My prediction is that it will be by far the cheapest place to put AI. It will be space in 36 months or less. Maybe 30 months.