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[return to "xAI joins SpaceX"]
1. gok+h4[view] [source] 2026-02-02 22:06:22
>>g-mork+(OP)
> it is possible to put 500 to 1000 TW/year of AI satellites into deep space, meaningfully ascend the Kardashev scale and harness a non-trivial percentage of the Sun’s power

We currently make around 1 TW of photovoltaic cells per year, globally. The proposal here is to launch that much to space every 9 hours, complete with attached computers, continuously, from the moon.

edit: Also, this would capture a very trivial percentage of the Sun's power. A few trillionths per year.

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2. lugao+DK[view] [source] 2026-02-03 01:28:20
>>gok+h4
Only people who never interacted with data center reliability think it's doable to maintain servers with no human intervention.
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3. angled+mL[view] [source] 2026-02-03 01:33:21
>>lugao+DK
But … but what if we had solar-powered AI SREs to fix the solar-powered AI satellites… /in space/?
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4. lugao+fQ[view] [source] 2026-02-03 02:03:43
>>angled+mL
Maintaining modern accelerators requires frequent hands-on intervention -- replacing hardware, reseating chips, and checking cable integrity.

Because these platforms are experimental and rapidly evolving, they aren't 'space-ready.' Space-grade hardware must be 'rad-hardened' and proven over years of testing.

By the time an accelerator is reliable enough for orbit, it’s several generations obsolete, making it nearly impossible to compete or turn a profit against ground-based clusters.

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5. trotha+1T[view] [source] 2026-02-03 02:22:38
>>lugao+fQ
On the other hand, Tesla vehicles have similar hardware built into them, and don't require such hands-on intervention. (And that's the hardware that will be going up.)
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6. lugao+QW[view] [source] 2026-02-03 02:50:40
>>trotha+1T
Car-grade inference hardware is fundamentally different from data center-grade inference hardware, let alone the specialized, interconnected hardware used for training (like NVLink or complex optical fabrics). These are different beasts in terms of power density, thermal stress, and signaling sensitivity.

Beyond that, we don't actually know the failure rate of the Tesla fleet. I’ve never had a personal computer fail from use in my life, but that’s just anecdotal and holds no weight against the law of large numbers. When you operate at the scale of a massive cluster, "one-in-a-million" failures become a daily statistical certainty.

Claiming that because you don't personally see cars failing on the side of the road means they require zero intervention actually proves my original point: people who haven't managed data center reliability underestimate the sheer volume of "rare" failures that occur at scale.

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