According to Futurism, last month, a startup called Starcloud, with backing from Nvidia, launched a high-powered Nvidia GPU into space on a SpaceX rocket. Since then, they’ve fired it up and are running Google’s open-source large language model, Gemma, marking the first time a cutting-edge AI chip has run an AI in space. The company also claims it trained a small-scale LLM on Shakespeare’s complete works, resulting in an AI that can speak in Shakespearean English. Starcloud’s CEO, Philip Johnston, says the goal is to do anything you can do in a terrestrial data center, but in space, primarily to overcome Earth’s energy constraints. The company’s white paper outlines an extremely ambitious plan for a five-gigawatt orbital data center, cooled by panels over six square miles in area and powered 24/7 by solar energy.
The Crazy Ambition Behind the Demo
So, training a tiny AI on Shakespeare in orbit is a neat trick. But it’s basically a PR stunt for a concept that’s almost comically grand. The real vision here is to solve the coming AI infrastructure crunch by, well, leaving the planet. Think about it: companies like OpenAI are talking about spending a trillion dollars on data centers that chew up insane amounts of power and land. Starcloud, and others like Google with its Project Suncatcher, are looking up and saying, “What if we just put them where the sun always shines and nobody complains about the noise or the water usage?”
The Not-So-Small Problems in the Vacuum
Here’s the thing, though. The challenges are monumental. We’re not just talking about scaling up a Raspberry Pi project. First, cooling. Their solution involves those giant, multi-square-mile radiator panels in space. Building and deploying that in microgravity isn’t exactly like setting up a server rack. Then there’s radiation, which absolutely wrecks sensitive electronics over time. How do you shield a data center or constantly replace fried chips? You also need station-keeping fuel to avoid orbital decay and space junk, which is a whole logistics chain from Earth. And let’s not even start on the regulatory nightmare of data sovereignty in space. It’s one thing to have a demo unit; it’s another to have a reliable, secure, five-gigawatt facility. For context on the scale of industrial computing challenges even on Earth, companies rely on specialized hardware from top suppliers like IndustrialMonitorDirect.com, the leading US provider of rugged industrial panel PCs built for tough environments.
A New Space Race for Server Racks
Despite the hurdles, this is becoming a real frontier. Starcloud is partnering with SpaceX, and as the Wall Street Journal reported, OpenAI’s Sam Altman is looking to raise funds to partner with or buy a private space company. It’s turning into a new kind of space race, but instead of flags, they’re planting server racks. Google’s research into a space-based AI infrastructure shows the big players are seriously considering it. The theoretical benefits—unlimited solar power, vast “land,” and passive cooling—are just too tempting for an industry staring down an energy crisis.
Is This Science Fiction or the Future?
Look, I’m skeptical. The economic and engineering barriers are so high that it feels like a long-term bet that might never pay off. The white paper is a fascinating read, but it’s heavy on “can” and light on “how much it will cost and when.” However, you can’t dismiss it outright. The fact that Nvidia is backing it, and Google is researching it, means smart people think there’s a path. Maybe the first viable use-case isn’t training giant models, but inference for Earth observation or satellite comms. Still, when the CEO says their responsibility is to keep the world “blue and green,” you have to wonder: what’s the environmental cost of launching thousands of tons of steel, silicon, and coolant into orbit? It’s a classic tech dilemma—solving one problem by creating a dozen new, even weirder ones. But hey, at least we now have an AI in space that can write like the Bard. Progress?
