alt Hacker NewsDifferent category of doubts. It's unreasonable to say starship can't work in a world where the Saturn V did work.
For datacenters in space to work, they have to solve a bunch of unsolved problems and be more economical than datacenters in earth.
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Starlink already does this. Goalposts will be carried to next place once the first orbital data centre is serving tokens.
A better comparison would be Starlink, which had a bunch of unresolved problems and had to be more economical than existing satellite internet providers.
> For datacenters in space to work, they have to solve a bunch of unsolved problems and be more economical than datacenters in earth.
Tough problem, however it is notable that after SpaceX, there are now several other companies with similar plans, including Google: https://www.nytimes.com/2026/09/24/technology/google-suncatc...
One interpretation is they're all delusional. Another is that Musk showed the way and others now see it too.
"It's unreasonable to say starship can't work in a world where the Saturn V did work."
Most of the doubts were economical as well. Saturn V was extremely expensive, its per-unit cost could be expressed in still-human-readable fractions of the entire US GDP. Starship should be several orders of magnitude cheaper while providing more capabilities.
I don't doubt Starship, BTW. Great project.
funny that skeptics didn't pile on Google for the same plans... https://www.nytimes.com/2026/09/24/technology/google-suncatc...
To be fair, radiators in space doesn't require any new technology. It's a very well understood problem. The best method is infrared radiators. Cooling is just a function of how large the surface area of the radiators, their heat, and the cooling required.
Where I think you're correct is that typical AI data centers require a LOT of cooling, and to achieve this at scale would require enormous radiators. So large that it's hard to square the business case given current launch costs. I've read a lot of research in this space and it looks like the much more realistic use cases (at least at first) will be sub-processing. Meaning processing data already in space. These could be telemetry, Starlink, tracking, telescopes, logistics, military, GPS, weather, deep space missions, first-response, alerts, etc. In particular, applications which require lower latency.
There are also other applications which are less cost sensitive. For example, applications which might be banned on Earth, or at risk of espionage, attack, or intrusion.
If we want to make typical AI data centers in space to be economical, we need launch costs to drop to under $200/kg. Interestingly, [Starship could reduce costs down to $67/kg.] Even lower with >9 launch cycles. (https://arstechnica.com/space/2026/07/rocket-developers-used...) This would make the business case *extremely* attractive.