Photonics Defined: The Technology at the Heart of the Next AI Boom

Photonics is the science and technology of generating, controlling, and detecting light. In the context of AI infrastructure, it specifically refers to using light instead of electricity to transmit data between processors inside data centers. The term comes from “photon,” the fundamental particle of light, just as “electronics” comes from “electron.”

Jason Bodner’s Accelerated AI presentation is built on this single concept: replacing copper wires with laser beams inside AI data centers. He calls it the “light-speed device” and says it will make AI 100 times faster and 100 times more energy efficient. The definition matters because understanding the technology is the first step to evaluating the investment thesis.

The Technical Definition

More precisely, photonics in AI data centers involves silicon photonics, the integration of optical components onto silicon substrates. This includes:

  • Lasers that generate light pulses at specific wavelengths
  • Modulators that encode data onto the light by varying its intensity or phase
  • Waveguides that channel light through the chip, similar to how copper traces channel electricity
  • Photodetectors that receive incoming light and convert it back to electrical signals

The key insight is that these components can be manufactured using standard semiconductor fabrication processes. This means photonic chips can be produced at scale in existing fabrication facilities, which dramatically lowers the barrier to adoption.

Why It Replaces Copper

The reason photonics matters is that copper has hit its physical limits in AI data centers. Every time you ask ChatGPT a question, it burns roughly 10 times more electricity than a Google search. A single AI data center can consume as much power as 100,000 homes. The bottleneck is not the GPUs themselves but the copper connections between them.

Electrons in copper travel at less than 1 percent of the speed of light. They generate heat, which requires additional power for cooling. They consume significant electricity. And they cannot keep up with the bandwidth demands of modern AI workloads where thousands of GPUs need to exchange data simultaneously.

Light, by contrast, travels at 124,000 miles per second. It carries far more data, barely uses power, and does not generate heat. As Bodner puts it: “Nothing in the known universe moves faster than light.” The physics is not in dispute. The question is how quickly the transition from copper to photonics will happen and which companies will benefit.

The Historical Precedent

Bodner defines photonics within the context of his Acceleration Curve framework. The argument is that every major technology transition goes through a copper-to-light shift:

  • Internet (1990s): Copper phone lines to fiber optics. The “World Wide Wait” became the high-speed internet. Companies like Equinix rose 37,000 percent and Netflix rose 188,471 percent.
  • Smartphones (2007): Copper to fiber in mobile networks. Companies like Monolithic Power rose 17,000 percent and Meta grew 42-fold.
  • AI (now): Copper to photonics inside data centers. Bodner says the second wave will be bigger than the first.

For more on this pattern, see our copper to fiber article. For a deeper technical explanation, see our photonics computing article.

The Investment Thesis

Bodner reveals Broadcom (AVGO) for free in the presentation. Broadcom debuted the industry’s first 400G optical chip, which is the specific component that converts electrical signals to light. Broadcom’s AI revenue was $10.8 billion last quarter, up 143 percent year over year. The company also designs custom AI silicon and builds networking switches, making it the most directly exposed large-cap stock to the photonics transition. For more on Broadcom, see our Broadcom stock article.

The three bonus picks behind the paywall include a pure photonics play with $6 billion in sales that is 20x smaller than Broadcom, a company that builds optical components inside AI clusters with a multi-billion Nvidia partnership, and a secret weapon inside every major AI data center. For the full thesis, see our Accelerated AI review.

Structural Validation

The photonics definition is not just Bodner’s opinion. The technology is backed by the largest companies in the world:

  • Nvidia has invested over $7 billion in photonics companies.
  • AMD is building a $280 million photonics research hub.
  • Ayar Labs raised $500 million from ARK Invest and Sequoia Capital.
  • Bill Gates has personally invested over $200 million in two photonics companies.
  • The Optical Interconnect Alliance includes Nvidia, AMD, Broadcom, Microsoft, Meta, and OpenAI.

Sequoia Capital called photonics “holy grail tech.” Bodner uses the same phrase. When the largest venture capital firm and the largest semiconductor companies in the world all converge on the same technology, it is worth understanding. For more on the industry alliance, see our optical interconnect article.

Considerations

Photonics is a well-defined technology with clear applications and substantial investment. The definition is not in dispute. What is uncertain is the timeline and the magnitude of the transition. These infrastructure shifts take years, and the companies that ultimately dominate may not be the ones getting the most attention today. Bodner acknowledges: “I don’t always get it right.” But the directional thesis is sound, and the structural evidence is strong.

If you want to explore the full thesis, you can access the Accelerated AI presentation through Brownstone Research.

This is not financial advice. Always do your own research before investing.