Nobody Is Building in Two Cities.
Except One Person...
*Jensen Huang just said we’ve achieved AGI. That’s the headline everyone’s arguing about. But the more important story isn’t what AI can do. It’s where AI runs — and who controls the ground beneath it.*
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This week, 30,000 people packed into SAP Center in San Jose — they couldn’t fit the keynote inside the convention center anymore — to watch Jensen Huang project a trillion dollars in annual revenue by 2027. Not valuation. Revenue. The whole world came to him.
And somewhere in the middle of a 2.5-hour Lex Fridman conversation, Huang said something that broke the internet: *”I think we’ve achieved AGI.”*
Everyone is debating whether he’s right. That debate is a distraction.
The more important question is hidden one layer deeper — underneath the chips, underneath the models, underneath the data centers — in a supply chain so concentrated it defies belief.
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## The Whole Revolution Runs Through Two Cities
Veldhoven is a small city in the Netherlands. You probably haven’t thought about it once in your life.
Hsinchu is a city on the western coast of Taiwan. You may have heard of it once or twice in passing.
Together, these two cities hold more leverage over the AI era than Washington, San Francisco, or Beijing. Because the entire global AI buildout — every GPU, every data center, every model powering the tools your organization depends on — runs through them.
**Here’s the dependency chain:**
**01 — ASML, Veldhoven, Netherlands**
The only company on earth that makes EUV lithography machines. No other entity, nation, or lab has replicated this. Without ASML machines, advanced semiconductors cannot be manufactured at scale. It took ASML thirty years and billions in R&D to build this capability. There is no shortcut.
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**02 — TSMC, Hsinchu, Taiwan**
Fabricates the overwhelming majority of the world’s advanced chips, including essentially every Nvidia GPU that matters. The most advanced nodes on earth exist here, and nowhere else at scale.
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**03 — Nvidia, Santa Clara, California**
Designs the GPUs. Controls roughly 80% of the AI chip market. Builds the software ecosystem that makes defection expensive. Projects $1 trillion in annual revenue by 2027.
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**04 — Global AI Infrastructure**
Every hyperscaler. Every frontier lab. Every enterprise AI deployment. Every agent. Every tool your organization is building its strategy around.
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That chain has a fault line running through it that no earnings call discusses plainly.
Taiwan sits 100 miles off the coast of mainland China. The question of whether that proximity is a present danger or a future risk is a geopolitical debate. But the structural dependency is not a debate. It is a fact. And every organization building AI strategy on top of this supply chain is, knowingly or not, building on that fact.
> *”The AI revolution has a supply chain that runs through two cities. And one of those cities sits 100 miles from a border dispute that could pause the entire decade.”*
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## Meanwhile, One Person Is Leaving the Board
Google has custom silicon. Amazon has Trainium. Meta has its own chip program. Every major hyperscaler is quietly working to reduce their Jensen dependency. They’re all solving the same problem: don’t buy from Nvidia.
That’s one link in the chain. It doesn’t touch TSMC. It doesn’t touch ASML. It doesn’t touch Taiwan. It’s a chip design play dressed as strategic independence.
Elon Musk is doing something categorically different.
At the Gigafactory in Texas, he’s reportedly building not just custom chips — but the manufacturing capacity to produce them domestically. Purpose-built. On soil where he already controls the land, the power relationships, the political alignment. And he’s not building them for data centers on the ground.
He’s building them for orbit.
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## Orbital Data Centers Are Not Science Fiction
Ground-based data centers are fighting over power grids, water rights, land, and permitting timelines that stretch into years. Every hyperscaler is trying to solve the same physical constraint problem — how do you cool a hundred thousand GPUs without a river nearby?
In orbit, that problem largely disappears. Radiative cooling is essentially free. Solar power is uninterrupted. And a data center in orbit exists outside the jurisdictional reach of any single nation-state’s regulatory environment in ways that no ground-based infrastructure ever will.
Now consider what Elon already controls:
- **Starlink** provides global connectivity
- **SpaceX** provides the launch infrastructure
- **Starship** has dramatically reduced the cost per kilogram to orbit
- **Custom chips** designed for orbital thermal and radiation conditions
- **Gigafactory Texas** as the domestic manufacturing base
No other person or organization on earth has all five simultaneously. Not even close.
Jensen Huang, to his credit, saw this coming. At GTC, when he outlined the operating system for *”Robots, Cars, Agents, and Orbit”* — that last word was not accidental. He wants Nvidia inside whatever runs in space. But if Elon controls the launch, the connectivity, the orbital platform, and the custom silicon, Jensen is selling into a market where someone else sets the terms.
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## What This Means for Everyone Else
Most organizations are not thinking about orbital data centers. Most organizations are not thinking about ASML. Most have never considered that a conflict in the Taiwan Strait could pause their AI roadmap indefinitely — not slow it, pause it.
They’re thinking about their next software upgrade. Their AI vendor’s pricing. Whether their team has the skills to use the tools they just licensed.
The readiness gap isn’t just organizational. It’s civilizational infrastructure running through a 35-kilometer strait — and nobody in the room has a contingency plan.
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The board is being reset. Not metaphorically. Physically.
The infrastructure of the AI era — where it runs, who controls it, what laws apply to it, whether it can be disrupted by geography — is being determined right now, in real time, by a very small number of people making very large bets.
The rest of us are still arguing about whether Jensen’s AGI claim is hype.
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*Part II will publish in a few days. It’s about what happens when this infrastructure meets the ground — and why your organization might be standing on the wrong side of a chasm that’s already being crossed.*