1. The Internet scaled through openness; AI scales through control.
2. What was once a software problem has become a physics problem—governed by energy, compute, and material constraints.
3. The AI stack is geopolitically entangled: each layer is a chokepoint in great-power competition.

Geopolitical Transformation: From Cooperation to Competition

The Internet thrived in an era of US-led globalization.
The AI era begins under strategic bifurcation—a shift from shared innovation to nationalized competition.

The Internet’s open web became the AI era’s divided map.

The Interdependence Paradox: Critical Control Points

AI depends on a fragile global supply chain that links physical materials, precision engineering, and digital models.
Each layer introduces a potential chokepoint—and therefore a lever of geopolitical power.

Each step is interdependent—but governed by opposing political blocs.

This creates the interdependence paradox: nations must collaborate across a supply chain they simultaneously seek to control.

The Physics of AI: Why This Isn’t Software

AI breaks from the Internet model in one fundamental way:
scaling is no longer virtual—it’s physical.

1. Energy

• 1–5 GW per hyperscale AI facility
• Dependent on nuclear, gas, or solar grids
• Permitting and grid expansion take years
• Geographic concentration around power hubs

💰 Cost: Billions
⏳ Time: Multi-year infrastructure cycles

2. Data Centers

• Specialized cooling and compute environments
• Water-intensive (up to millions of liters/day)
• Only ~3–5% of existing data centers are AI-ready
• Multi-year retrofits and greenfield builds required

💰 Cost: Billions
🌍 Constraint: Geography + sustainability

3. GPUs

• H100/H200/B200 scarcity; TSMC production bottleneck
• NVIDIA dominates; supply chain politicized
• Years required to scale fabrication
• Geopolitical controls restrict exports

⚙️ Constraint: Physical scarcity + political control

4. Model Training

• $100M–$1B per foundation model
• Months of compute time
• Thousands of GPUs operating simultaneously
• Requires elite research teams and energy coordination

🎓 Barrier: Not VC-scale — sovereign or corporate capital only

Structural Comparison: Internet vs. AI

The Internet scaled horizontally; AI scales vertically.

Economic Reversal: From Infinite Scalability to Finite Physics

The Internet’s economics were defined by abundance — once built, marginal cost per user approached zero.
AI’s economics are defined by scarcity — every inference consumes real power, chips, and cooling.

AI reintroduces hard economics into the digital age — turning infrastructure into the primary competitive advantage.

The Strategic Implication: Industrialization of Intelligence

The AI revolution is not a continuation of the software era — it’s the industrialization of computation.
Where the Internet abstracted physical limits, AI reimposes them.

To scale AI, you must:

• Secure raw materials (rare earths, power)
• Build compute infrastructure (data centers, chips)
• Coordinate capital at national scale
• Manage regulatory and geopolitical risk

In short: software startups wrote code; AI startups must build empires.

The New Reality: Sovereign Compute Economies

AI infrastructure now defines national competitiveness.
Power, not protocol, dictates who leads.

The global AI order will likely be multi-speed:

• US-led compute hegemony
• China-led vertical integration
• EU-led regulatory standardization

Together, they define the architecture of the next decade.

Conclusion

AI doesn’t inherit the Internet’s DNA — it mutates it.
Where the Internet was open, AI is strategic; where code was abundant, compute is scarce.
Power has shifted from protocol designers to infrastructure sovereigns.

The AI economy will not run on venture capital —
it will run on energy, silicon, and state alignment.