Why Nvidia Is Spending Billions to Stop Using Electrons

NVIDIA has spent billions on “light.”

Since March 2026, it has announced $2 billion each in Lumentum, Coherent Corp., and Marvell Technology, plus additional photonics commitments with Corning and Ayar Labs.

The goal is to move information with photons instead of electrons.

To see WHY, let's start with how small computing has become.

A human hair is roughly 70,000 to 100,000 nanometers wide.

A silicon atom is about 0.2 nanometers across. Today’s leading chips are built on “2-nanometer-class” processes, where some features are only a few dozen atoms wide. We have learned to build switches at the edge of the atomic world, print them by the billions, and flip them billions of times per second.

But computing is no longer limited only by how SMALL the switches are. It is increasingly limited by how FAR the data has to move.

One bit in a conventional computer is voltage on a wire. To send it, you charge that wire up and drain it down. The wire has resistance and capacitance, so every transition costs energy and releases heat.

Do that billions of times per second across millions of wires, boards, racks, and data-center clusters, and you get a central problem of modern computing: moving data can cost more energy than doing the math.

Now consider that all of modern computing runs on the electron: a tiny particle with electric charge. That charge makes the electron useful. You can switch it, gate it, store it, and use it for logic. The electron is brilliant at computing.

But moving charge through metal means fighting resistance, capacitance, signal loss, and heat. The same property that makes electrons good for logic makes them costly for long-distance communication.

That is where photonics becomes valuable.

A photon is a particle of light. It has no electric charge and no rest mass. It can travel through glass with very little loss, and many wavelengths and many “colors” can move through the same fiber at once.

Light does not win because it is dramatically faster. Electrical signals already travel at a large fraction of light speed.

Light wins because it is cleaner to move, fades less, heats less, carries more data over longer distances. AND it can multiplex many channels through one strand of glass.

That is the path NVIDIA is investing in: lasers that make the light, silicon that connects to it, glass that carries it, and optical I/O that brings it closer to the chip.

This matters even if you never touch a GPU.

We know that AI uses staggering power. But much of that power is not the “thinking.” It is the moving. Data must move from memory to cores, chip to chip, board to board, rack to rack, and sometimes across entire data halls.

That movement costs energy.

If the next decade of AI runs mainly on copper and conventional electronics, it hits a power wall. BUT if more of it runs on light, could the same intelligence become cheaper, cooler, more sustainable and easier to scale?

That's the bet NVIDIA and others are making. Until next time,

Ram — 

Ram Srinivasan

MIT Alum | Author, The Conscious Machine | Global Future of Work and AI Adoption Leader published in Business Insider, Fortune, Harvard Business Review, MIT Executive Viewpoints and more.

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Ram Srinivasan currently serves as an Innovation Strategist and Transformation Leader, authoring groundbreaking works including "The Conscious Machine" and the upcoming "The Exponential Human."

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