Artificial intelligence has a copper problem.
Inside every data center powering ChatGPT, autonomous robots, and the next generation of AI applications, thousands of chip clusters need to talk to each other. Right now, most of that communication happens through tiny copper wires carrying electrical signals.
The problem? Copper is too slow. It generates too much heat. And as AI models grow larger and more complex, the old copper infrastructure is buckling under the load.
The solution is photonics — replacing copper wires with laser beams. Data travels through glass fibers instead of metal, at speeds approaching 124,000 miles per second. The result: AI systems that run 100 times faster and consume 100 times less energy.
This is not a theoretical concept. The biggest players in tech are already moving billions of dollars to make it happen. And if the pattern holds, the companies building the photonics infrastructure for AI could deliver returns that dwarf the first wave of AI stocks.
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The Acceleration Curve: A Pattern That Has Played Out Twice Before
To understand why photonics matters, you have to understand the pattern.
In the 1990s, the internet exploded onto the scene. The number of people online went from 16 million to over 500 million in five years. Stocks soared. Netscape jumped 500% in four months. Yahoo reached a $125 billion valuation. The Nasdaq rose 572%.
But the old infrastructure could not keep up. Data moved too slowly. Websites crashed. People started calling it the World Wide Wait. The Nasdaq fell 78% from its peak. AOL cratered 87%. Pundits declared the internet dead.
Then a breakthrough happened. Telecom companies spent over $500 billion laying fiber-optic cable around the world — 80 million miles of glass strands carrying data as light. Speeds jumped from 56kbps to 1Gbps, a 20,000-fold improvement.
The companies that emerged from that second wave became the biggest in the world. Akamai gained 16,497%. F5 Networks rose 14,768%. Equinix soared more than 37,000%. Google, Amazon, and Netflix — all built on the fiber-optic backbone — went on to deliver returns exceeding 10,000% each.
The same pattern repeated with smartphones. When the iPhone launched in 2007, cell towers were wired with old copper lines. Networks buckled under the load of streaming video and mobile data. The solution was the same: rip out the copper, replace it with fiber. Speeds jumped 200 times.
The companies that powered that transition delivered massive returns. Cirrus Logic gained over 6,500%. Lattice Semiconductor rose 12,720%. Monolithic Power Systems went up more than 17,000%.
Now the same pattern is playing out for the third time — inside AI.
The AI Bottleneck Is Real
AI has slammed into a wall. The problem is not algorithmic. It is physical.
One question to ChatGPT burns 10 times more electricity than a Google search. A single AI data center consumes as much power as 100,000 homes. The International Energy Agency reported that data center electricity demand surged 17% in 2025 alone.
The copper wires inside AI chip clusters are the bottleneck. Electrical signals pushing through copper generate heat and resistance. Data moves slowly. The system cannot scale.
Jensen Huang, Nvidia CEO, has said that without photonics, AI cannot scale. The demand for this technology is so high that the biggest problem is producing it fast enough.
What Photonics Actually Does
Photonics replaces electrical signals with light. Inside AI data centers, microscopic laser beams travel through glass fibers instead of copper wires.
The advantages are not incremental. They are transformational:
Speed: Light travels at 124,000 miles per second. Electrons through copper move at less than 1% of that speed. Photonics makes AI systems 100 times faster.
Energy efficiency: Unlike electrical signals pushing through copper, light has minimal resistance and does not generate heat. Photonics makes AI 100 times more energy efficient.
Data capacity: Light carries far more data per second than electrical signals. As AI models grow, the ability to move massive datasets between chips becomes critical.
Heat reduction: AI data centers are consuming unprecedented amounts of electricity. Photonics dramatically reduces the heat generated by chip-to-chip communication, lowering cooling costs and enabling denser, more powerful clusters.
The bottom line: photonics is not one application. It is the foundational layer for everything AI touches going forward.
Who Is Building It
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The race to build photonics infrastructure for AI is already underway, and the biggest names in tech are leading the charge.
Nvidia has invested more than $7 billion in companies developing photonics technology. The company partnered with Corning to build three new optical factories in the United States. Nvidia CEO Jensen Huang has warned that demand for photonics is so high that the biggest problem is producing it fast enough.
AMD is building a $280 million hub dedicated to photonics research.
Broadcom (NASDAQ: AVGO) just debuted the industry’s first 400G optical chip — the fastest way to move data as light inside any AI data center. Broadcom designs custom AI silicon for OpenAI, Meta, Anthropic, and Google. It builds the networking switches that let AI chips communicate. And it makes the optical chips that turn electrical signals into light. Broadcom’s AI revenue hit $10.8 billion in a single quarter — up 143% year over year — with guidance for $16 billion the following quarter, representing over 200% growth.
Ayar Labs, a photonics startup, raised $500 million from investors including Cathie Wood’s ARK Invest and Sequoia Capital.
Google and Microsoft are backing nEye, a photonics startup building optical switches for AI data centers that just raised $80 million.
Bill Gates personally invested more than $200 million in two different photonics companies.
The industry has formalized the commitment. Nvidia, AMD, Broadcom, Microsoft, Meta, and OpenAI joined forces to form the Optical Interconnect Alliance — a consortium dedicated to standardizing and accelerating photonics adoption across the AI ecosystem.
Why Broadcom Sits at the Center
Broadcom is not a small speculative play. It is a $700 billion company that has quietly positioned itself at the center of the photonics buildout.
Three things make Broadcom critical to the AI infrastructure stack:
First, Broadcom designs the custom AI silicon that powers the largest AI models. OpenAI, Meta, Anthropic, and Google don’t use off-the-shelf chips. They need custom-built AI processors, and they all go to Broadcom.
Second, Broadcom builds the networking switches that allow AI chips to communicate with each other. Without Broadcom switches, the AI goes dark.
Third, and most relevant to photonics, Broadcom manufactures the optical chips that convert electrical signals into light inside AI data centers. The company’s 400G optical chip is the fastest data-as-light product in any AI data center today.
BlackRock owns more than 12 million shares of Broadcom. Fidelity, Vanguard, and Morgan Stanley are also major holders. The institutional conviction is clear.
The last time a company sat at the center of a light-speed infrastructure buildout like this was Cisco in the 1990s. Cisco stock surged 3,800% during the fiber-optic boom — enough to turn $10,000 into $390,000.
AI is a far bigger market than the early internet ever was. And Broadcom is sitting right at the center of it.
The Space Connection
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Photonics isn’t just an AI story. It is also the backbone of the emerging space economy.
SpaceX’s Starlink already has approximately 10,000 laser terminals in orbit. The company filed with the FCC to launch 1 million AI data center satellites. Jeff Bezos’s Blue Origin is preparing to launch 51,000 AI data centers in space. Google has its own project in the pipeline.
Every satellite, terminal, and piece of space-based electronics requires photonics technology. There is no other way to move data in space.
McKinsey projects the global space economy could reach $1.8 trillion. Morgan Stanley estimates the humanoid robot market alone at $5 trillion. When you add AI data centers, space infrastructure, and physical AI systems, the total addressable market for photonics approaches $40 trillion.
The Risk Side
No investment thesis is complete without an honest assessment of risk.
Photonics is a real technology, but the timeline for mass adoption is uncertain. The companies building photonics chips face manufacturing challenges, yield issues, and competition from established semiconductor players who may try to extend copper technology further.
Broadcom at $700 billion is not a small-cap stock. A 10X return would imply a $7 trillion market cap. That’s not impossible, but it would require the entire photonics market to exceed the most aggressive projections. Investors should manage expectations accordingly.
The three smaller companies teased in the original research presentation carry higher upside potential but also significantly higher risk.
And as with any technology transition, there is the possibility that copper-based solutions improve faster than expected, delaying the need for photonics. The history of the internet and smartphone transitions suggests this is unlikely — both times, copper hit a hard physical wall — but investors should be aware of the possibility.
The Verdict
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The shift from copper to photonics inside AI data centers is not a question of if. It is a question of when and how fast.
The pattern has played out twice before. The internet hit a wall, and fiber optics smashed through it. Smartphones hit a wall, and fiber optics smashed through it again. Both times, the companies building the light-speed infrastructure delivered returns exceeding 1,000%.
AI has hit the wall. The biggest tech companies in the world are pouring billions into photonics. Nvidia, AMD, Broadcom, Microsoft, Meta, and OpenAI have formed an alliance to standardize the technology. Bill Gates, Cathie Wood, and Elon Musk are all backing photonics companies.
The companies building the foundational layer of the next AI wave — the photonics infrastructure that makes AI 100 times faster and 100 times more efficient — are the ones to watch.
Broadcom is the most established play. The three smaller companies may offer higher upside. But the thesis is the same: the future of AI runs on light, not copper.
The people who position themselves before the mainstream catches on will have a shot at the kind of gains that most investors only read about in hindsight.
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Nothing in this article is investment advice. Past performance does not guarantee future results. All investing carries risk, including possible loss of principal. Wall Street Watchdogs is an independent publication that receives no compensation from the companies mentioned.
