🧩 The Empire and the Rebellion: Why Nvidia’s Moat Is Deeper Than Ever

Lately, the buzz around AMD $Advanced Micro Devices(AMD)$   has been impossible to ignore. Its stock is climbing, headlines are piling up, and alliances are forming.

First came UALink, then ESUN — tech giants banding together to build “open highways” for AI accelerators, sidestepping Nvidia’s proprietary ones.

Naturally, a question began circulating:

Is Nvidia’s $NVIDIA(NVDA)$  moat in the AI era starting to crack?

If you think so, you’re missing the point.

In truth, all these alliances don’t signal weakness — they signal dominance. The very reason everyone else is joining forces is because Nvidia’s advantage has grown so immense that it’s suffocating the ecosystem.

This isn’t an attack. It’s a survival movement — a collective act of self-preservation by companies too powerful to tolerate total dependence.

To understand the “anti-Nvidia coalition,” you first need to see how deep its moat truly runs.

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🧱 Moat #1: The Visible Empire of Hardware

If Nvidia’s power came only from having the fastest GPU, its throne might indeed be shaky. After all, chip design is a game of talent and time — another genius could always build a faster engine.

But Nvidia doesn’t just sell engines.

It sells entire race cars — fully tuned DGX systems — and the private highway they drive on.

At the heart of that highway lie NVLink and InfiniBand, Nvidia’s proprietary interconnects that bind thousands of GPUs into one coherent super-organism.

They are, quite literally, the empire’s nervous system — an exclusive highway where only Nvidia-certified machines can drive at full speed.

You can build with AMD or Intel chips if you wish, but your system will crawl on ordinary roads — slower, less synchronized, and worlds apart in efficiency.

That’s the visible moat: a self-reinforcing hardware ecosystem stretching from chip to system to interconnect standard.

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👁️‍🗨️ Moat #2: The Invisible Soul of Software

If hardware is the body of the empire, CUDA is its soul.

For fifteen years, AI developers have lived inside the CUDA universe — writing code, training models, building everything on it. CUDA is to AI what Windows was to the PC, or iOS to the smartphone: an operating layer that became an entire world.

You can build a better chip, but unless it runs the ocean of existing CUDA code without pain, it’s just an expensive piece of silicon.

This is the most powerful lock-in of all — a global network effect of code, habit, and history. The longer it persists, the harder it becomes to escape.

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⚔️ The Rebellion: “Unified Text, Standard Wheels”

Once AMD, Intel, Google, Meta, and Microsoft understood the scale of this moat, they realised a lone challenger could never win.

So they did what all threatened empires’ rivals eventually do: they allied.

Think of it as a modern replay of Qin Shi Huang’s “unifying script and axle width” — an attempt to create a new open standard against a closed empire.

Two acts of the drama have already unfolded.

Act I: The Idealists — UALink (2024)

AMD, Intel, and Google formed the star-studded UALink Alliance, aiming to build an open interconnect protocol that could link 1,024 accelerators across vendors — a direct challenge to Nvidia’s NVLink monopoly.

Act II: The Pragmatists — ESUN (2025)

As idealists debated specs, engineers turned practical. ESUN (Ethernet Scale-Up Network) emerged, proposing standard Ethernet — not exotic hardware — as the new universal backbone for rack-scale AI clusters.

This wasn’t revolution; it was reform.

And it spoke volumes about Nvidia’s dominance: when an industry can’t beat you, it standardises around something simpler just to breathe.

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🪙 The Paradox of Power

So, does this wave of collaboration mean Nvidia’s supremacy is cracking?

Not at all.

It’s proof that its moat has grown terrifyingly deep.

If Nvidia were merely faster, rivals could out-engineer it. But they’re now forced to form multinational alliances just to co-exist. That’s not weakness — it’s gravitational dominance.

This “interconnect war” is about far more than chips. It’s a philosophical clash over how the next generation of AI supercomputers should be built — scale-up vs scale-out, closed vs open, empire vs federation.

In my upcoming deep-dive on Substack, I’ll dissect this first moat — Nvidia’s hardware empire — through seven critical lenses:

1. Two Design Philosophies: Scale-up vs scale-out in AI supercomputer architecture.

2. Nvidia’s Twin Barriers: How NVLink and InfiniBand create an ultra-efficient but closed system.

3. The Challenger’s Alliance: Inside the birth of UALink — the open-standard counteroffensive.

4. The Civil War Within: Why ESUN rose as a pragmatic rival to UALink’s idealism.

5. The Unexpected Casualty: How Astera Labs became the awkward victim caught between both camps.

6. The Endgame: Why the “open-standard war” might ironically strengthen Nvidia’s throne rather than weaken it.

7. What Comes Next: Why CUDA — the invisible moat — remains the most unassailable of all.

Because when rivals unite not to conquer you, but to avoid being conquered, you know you’ve built something more than a company — you’ve built an empire.

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