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🚀🌌 Elon Musk made a highly impactful yet severely underestimated judgment.

"Remember my words, within 30–36 months, likely closer to 30 months,
deploying AI in space will become the most economically optimal choice.
Those who have long lived in the software world will soon learn a profound lesson in the face of hardware."

The truly shocking part of this statement isn’t "space,"
but how he pointed out a long-overlooked reality:

AI’s bottleneck is shifting from software to hardware and the physical world.

For over a decade, the tech industry has been accustomed to one thing:
computing power issues = writing better code, training larger models, stacking more servers.

But now, things have changed.

As AI enters the phase of ultra-large-scale deployment,
what truly limits it is no longer just the chips themselves, but—
power, cooling, land, infrastructure density, and marginal expansion costs.

This is the core logic behind Musk’s mention of "space."

In an orbital environment:
• Solar energy is virtually unlimited
• No need for complex ground cooling systems
• Can bypass some ground power and land bottlenecks
• Highly concentrated deployment may significantly reduce marginal computing costs

When model scale and inference demands continue to grow exponentially,
the most economical solution may not be on the ground.

And the phrase "software people are about to be schooled by hardware" is even harsher.

It means:
The next phase of AI competition won’t be about
who codes faster, builds bigger models, or has more parameters,

but about:
who can solve the engineering constraints of the real world.

Where does the power come from?
How is heat dissipated?
How can computing power be scaled, low-cost, and stably maintained long-term?

These problems don’t exist in code;
they exist in the physical world.

This is also why you’re seeing a clear trend:
AI is being forcibly tied to energy, infrastructure, aerospace, and manufacturing.

From this perspective, Musk’s words aren’t "sci-fi speculation,"
but a judgment about timing:

As AI demands continue to grow exponentially,
the marginal costs of ground systems begin to spiral out of control,
and capital will naturally seek new physical carriers.

Space is just one of the most extreme—yet cleanest—solutions.

The question is no longer just:
How powerful will AI be?

But rather:
Where exactly should we place AI to make it the cheapest and most sustainable?

If AI’s "ultimate computing platform" truly begins migrating to space,
who do you think the biggest winners will be—
chip companies, energy systems, aerospace infrastructure,
or the first to integrate all three?

📬 I’ll continue tracking key judgments at the intersection of AI, computing power, energy, and aerospace infrastructure, documenting which radical ideas are becoming reality step by step. Subscribe to stay updated and keep an eye on those underestimated structural changes.

#ElonMusk #AI #SpaceComputing #Infrastructure #Hardware #Energy #Aerospace