# Chip failures could make or break orbital data center economics

Markdown copy of https://realalpha.app/s/chip-failures-could-make-or-break-orbital-data-center/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Philip Johnston](https://realalpha.app/builders/philip-johnston/) · Co-Founder & CEO, Starcloud · Building Starcloud’s space-based data centers to scale AI compute beyond terrestrial constraints.
- Host: [Molly O'Shea](https://realalpha.app/people/molly-oshea/) · Founder, Sourcery · Ex-Upfront Ventures investor; has interviewed Alex Karp and Palmer Luckey.
- Show: Sourcery
- Episode: [Nvidia GPUs in Orbit: Inside Starcloud’s $2B Factory](https://realalpha.app/v/mdq6urSx-f8/), Oct 31, 2026
- Moment: 33:42 to 37:45 of the episode (4 min), playing on https://realalpha.app/s/chip-failures-could-make-or-break-orbital-data-center/; the episode from there: https://realalpha.app/v/mdq6urSx-f8/?t=2022

## Quote

> “So for StarCloud 2, we had a three-month burn-in period, it basically means you run the **chips hot for three months** so you can find all those failures early.”
> — [Philip Johnston](https://realalpha.app/builders/philip-johnston/) at [35:14](https://realalpha.app/v/mdq6urSx-f8/?t=2114) · Sourcery

## Takeaways

1. Chips are the most expensive part of the system.
2. A three-month hot burn-in screens for early chip failures.
3. On-orbit inference could turn imagery into insights in minutes.

## About this segment

Philip Johnston explains how radiation-related failures could undermine the business model, and how burn-in helps screen chips before launch. He then describes using orbital GPUs to deliver satellite-image insights faster.

From “Nvidia GPUs in Orbit: Inside Starcloud’s $2B Factory”, Oct 31, 2026. [Watch the full episode](https://realalpha.app/v/mdq6urSx-f8/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[33:51](https://realalpha.app/v/mdq6urSx-f8/?t=2031) handful of your interviews one of the other very concerning points is chips and chip failures so how does that work into the model yeah for sure it's actually a super uh like relevant point i think it's actually more relevant and pertinent than even cooling which is people think is the biggest challenge we've basically solved the cooling challenge um the other part of it that we're working on is the radiation shielding and testing all the chips in different particle accelerators to make sure they can survive the radiation environment of space and the reason we put so much time into that is if the chips have you know like a 10 or 20 percent higher failure rate in space than they do on the ground then the whole economics of the model fall apart and the reason is the chips are by far the most expensive part of what we're doing actually

[34:36](https://realalpha.app/v/mdq6urSx-f8/?t=2076) and so there's a few ways that you you can go around that i mean essentially we're not going to have access to the satellites once they launch so they operate a bit like the way the starlink satellites work which is you need to have redundancy on critical systems you know things like pumps and then you over provision things which fail over time like the solar panels you're going to lose a few percent per year so you slightly over provision that um and then on the chips we have a longer burning period on the ground um most chips actually fail in the first period of their life and so if you can put them through a more rigorous burn why is that i don't No, it's basically, they call it infant mortality of the chips.

[35:14](https://realalpha.app/v/mdq6urSx-f8/?t=2114) Oh, no. Yeah. Oh, my God. I know, it sounds kind of terrible. That's horrible. So what you want is to get through the infancy period and find out all those failures. So for StarCloud 2, we had a three-month burn-in period, it basically means you run the chips hot for three months so you can find all those failures early. It's basically like, yeah, if you can survive, if the chips can survive three months at full power the chance they have a failure from that point onwards diminishes very dramatically versus the chance to have a failure in the first three months so you have five chips up in space right now including one each 100 yes what are they doing um so actually we have yes we have three chips from NVIDIA, two from ARM and we also have some CPUs from AMD on StarCloud One. And what they're doing is, at the moment, we use them to do some interesting workloads, like train the first model in space, NanoGPT from Andre Carpathy.

[36:09](https://realalpha.app/v/mdq6urSx-f8/?t=2169) We ran the first version of Gemini, but now they're actually doing useful workloads for government customers. So they are mainly in sort of as a test phase, but we're doing inference on satellite imagery, so on synthetic aperture radar data, on hyperspectral data. So we actually just will do an announcement about some of the results of this, but we've got some very interesting results. And the use case for that is, let's say the government has a bunch of military satellites.

[36:38](https://realalpha.app/v/mdq6urSx-f8/?t=2198) They collect enormous amounts of mostly imagery, but also other types of data. They don't want to have to wait for a ground station to downlink all of that data. So if they can run inference on that at the edge, we can then send down the insight much quicker. and so for example if they're monitoring a patch of water they might want to know is there a vessel crossing some some boundary at the moment what they do is they take an enormous amount of imagery and then they have to wait at least an hour and a half to get to a ground station and then they try and downlink as much as they can but that's usually not very much once we're in space we have a bunch of optical terminals on our satellite in real time they can send data to us we can then run the inference workloads on our satellite and then we can downlink the coordinates of a vessel

[37:22](https://realalpha.app/v/mdq6urSx-f8/?t=2242) for example, in minutes rather than hours and days, which is the current way that this works. That's wild. Oh my gosh. So our initial use cases for these satellites and what they're doing right now, all the satellite operators and that kind of data, when do you think it'll