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# Google thinks SpaceX’s Starship has to launch 1,600 times before space data centers get off the ground

**[TechCrunch](https://daily.dev/sources/tc)** · 4 min read · 0 upvotes · 0 comments

## Summary

Google launched its first Tensor Processing Unit into orbit aboard a SpaceX rocket, part of Project Suncatcher, a long-term effort to build space-based AI compute clusters. The satellite, built with Planet Labs, will test whether the TPU can handle power, cooling, and inference workloads in orbit, running in 15-minute bursts. Google envisions a future network of 81 satellites with laser links between them. A peer-reviewed white paper published alongside the launch estimates that SpaceX's Starship would need roughly 1,800 launches over ten years (180 per year, 200 metric tons per flight) to drive launch costs down to about $200 per kilogram by 2035 — a pace far beyond Starship's historical launch cadence. Radiation testing suggests the chips can survive the five-year satellite lifespan for inference workloads, though error rates would be problematic for massive multi-month training runs.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://techcrunch.com/2026/10/01/google-thinks-spacexs-starship-has-to-launch-1600-times-before-space-data-centers-get-off-the-ground>

## Questions this post answers

### How many Starship launches would be needed to make space-based data centers cost-effective, according to Google's analysis?

Google's peer-reviewed white paper estimates Starship would need to fly about 1,800 launches over ten years, roughly 180 per year, carrying 200 metric tons per mission, to reach a total of 370,000 tons of payload. That launch cadence and volume would be needed to continue SpaceX's roughly 20% annual cost-reduction learning curve and reach launch prices near $200 per kilogram by 2035.

_Developers tracking the economics of orbital compute can follow projections like this one on daily.dev._

### Can Google's Tensor Processing Units survive radiation exposure in space for AI inference?

Yes, according to Google's testing, TPUs show an error rate of about one in a million for typical inference operations after being blasted in a particle accelerator to simulate orbital radiation over a five-year satellite lifespan. However, the error rate becomes problematic for mega-scale training runs involving thousands of chips running for months, since those are far more sensitive to logic errors.

_Engineers evaluating space-based AI hardware reliability can keep up with findings like these on daily.dev._

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- [Google Unveils Project Suncatcher, Envisioning AI Models Running in Space](https://daily.dev/posts/google-unveils-project-suncatcher-envisioning-ai-models-running-in-space-lbabw1skb) · InfoQ · 0 upvotes · 0 comments
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---

Tags: [#google](https://daily.dev/tags/google), [#spacex](https://daily.dev/tags/spacex)

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