The company that makes glass for iPhones has seen its stock price surge 5x due to AI

On the afternoon of May 6, Nvidia announced an investment. The amount wasn't particularly large, at $500 million. But the contract stipulated that it could be increased to $3.2 billion in the future. Corning's stock rose 14% that day.

Even more intriguing was the structure of the deal. Among the 18 million equity certificates Corning gave to Nvidia, 3 million had an exchange price of $0.0001. This essentially means those 3 million shares were given to Corning almost for free. That same afternoon, Corning raised its revenue growth target through 2030 to $40 billion at its investor conference in New York.

But this isn't the most unusual part of Corning's recent months. The quarterly report of this "iPhone screen glass supplier" stated that in the past few months, two other unnamed companies have signed multi-year contracts worth $6 billion each. The reason we say "another" is that Corning had just signed a contract of the same scale with Meta not long ago.

If you count, you'll find that in the past 4 months, at least 4 major AI orders worth tens of billions of dollars have been concentrated on this 174-year-old glass company. Over the past 6 months, Corning's stock has risen 140%, and compared to two years ago, it has increased 5-fold.

From Mobile Phone Glass to AI Factory Darling

If you are reading this article on your phone, the glass covering your screen is most likely a piece produced by Corning. Since Apple's first-generation iPhone in 2007, Corning's Gorilla Glass has become the default choice for high-end smartphone screens globally. But "mobile phone glass supplier" is just one facet of Corning, and not the most profitable one.

Corning factory's Gorilla Glass production line. Image source: Apple

Founded in 1851, the company made the glass envelope for Edison's first incandescent light bulb, and in the 1970s invented low-loss optical fiber from scratch, creating the entire modern fiber optics industry. The iPhone glass in 2007 was its third major business pivot. Today, Corning is undergoing its fourth transformation, with optical communications becoming the true engine of its business.

Corning's optical communications business has a history of over 50 years, but the customer structure of this business has completely flipped in the last two years.

For a long time, Corning's optical fiber was mainly sold to telecom operators like AT&T and Verizon. These companies used it for fiber-to-the-home and building 4G and 5G base stations. In 2009, Corning launched a data center cabling solution called EDGE, formally adding data center operators to its customer list. Over the past decade-plus, driven by the mobile internet boom, the spread of cloud services, and the explosive growth of remote work during the pandemic, Corning's optical communications business rose steadily, but it was never the revenue mainstay.

In November 2022, OpenAI introduced ChatGPT to the public. From that moment, data centers worldwide began redesigning their physical infrastructure for the new computing task of AI training. The fiber optic density required for AI training is at a level never seen in any previous era.

The earliest hint appeared in August 2024. A US telecom operator named Lumen booked 10% of Corning's global fiber optic production capacity in one go, spanning two consecutive years. This was the earliest public signal of Corning's business transitioning towards the AI field.

By early 2026, the aforementioned four $6 billion-level contracts erupted in concentration. Corning has partnered with data center operators for 15 years, but the shift from "secondary customer" to "absolute主力" has only occurred in the past 24 months.

The direct effect of this customer shift is reflected in Corning's financial reports. Corning's full-year revenue in 2023 fell 11% year-over-year, marking an industry trough, but by 2025, full-year revenue surged to $15.6 billion, a 19% increase year-over-year. In the first quarter of this year, its revenue grew another 18% year-over-year. The most impressive was the optical communications business, growing 35% for the full year. Optical communications' share of total revenue increased from 30% in 2020 to 37% in 2025. The change in absolute value is more intuitive, going from $2 billion five years ago to $6.3 billion in 2025, more than tripling.

This leap from a "secondary business" to the "locomotive" was not accidental. Behind it is a growth plan spearheaded by the company's CEO, Wendell Weeks. The plan has an internal codename: Springboard.

Two years ago, in the eyes of Wall Street analysts, Corning was still a "boring glass manufacturer," classified as a mature, low-growth dividend stock. But three years after implementing the Springboard plan, Corning's stock price rose from just over $30 at the beginning of 2024 to $162, a 5-fold increase in two years, including a direct 140% rise in the past 6 months. The glass factory has transformed into the "nervous system of the AI revolution."

Springboard was first announced in September 2024. The starting point was an annualized revenue level of approximately $13 billion in the fourth quarter of 2023. The initial goal was to increase annualized revenue by over $3 billion by the end of 2026, achieving an overall operating margin of 20%.

But over the next year and a half, this target was raised three consecutive times, eventually climbing to $6.5 billion, pushing the annualized revenue target for the end of 2026 to the $20 billion scale. After Nvidia invested in Corning on May 6th, the company directly raised its internal revenue target for 2030 to $40 billion. At the same time, Corning achieved its 20% profit margin target a year early in the fourth quarter of 2025.

The key to the Springboard plan lies in "premium." The company's sales grew by 18%, but earnings per share grew by 46%, a profit growth rate 2.5 times that of sales growth. At the operational level, Corning focused on three specific things:

First, hard price increases for its old business. Corning's display glass is a mature business that hasn't grown for years. But at the end of 2024, Corning raised prices for this line by over 10%, while also locking in the yen exchange rate through 2030. The result is that even in a depreciating yen environment, this line stably contributes $900 million to $950 million in net profit annually, maintaining a net profit margin of 25%.

Second, upgrading optical communication products. In the full year of 2025, optical communication sales rose by 35%, but net profit soared by 71%. This means that not only did Corning sell more optical fiber, it also earned more for each strand.

Third, ramping up idle capacity. Corning did not build large new factories on a massive scale. Instead, it restarted capacity that had been idle during the trough of the previous cycle, boosting the company's overall gross margin from 33% in 2024 to 36% in 2025.

Of course, prices can rise only because someone is willing to pay them. Products can be upgraded to make more money only because someone is willing to pay more for the upgraded products. The fundamental reason Springboard allowed Corning's profit growth to outpace revenue growth is that its customer structure now includes a group of people willing to pay a premium.

Everyone is Scrambling for Fiber Optics

The AGI race and order demands have made every data center operator incredibly anxious about time.

The core business of the cloud giants has always been "renting IT to enterprises." The vast majority of traffic for companies like Netflix, Airbnb, and Uber, which grew with the mobile internet, is "north-south." A user opens an app from outside, a request is sent to a server in the cloud, and the server returns data. Servers communicate with each other occasionally, but the volume and frequency are low. This network structure doesn't impose harsh requirements on the underlying physical infrastructure: Ethernet is sufficient, copper cables are sufficient, and ordinary optical fiber is sufficient. The cloud giants have used this architecture themselves for over a decade, and it was stable and profitable.

It wasn't until after the launch of ChatGPT that the rules of the game began to change.

In the following years, almost all cloud giants started training models themselves. Microsoft is the primary computing provider for OpenAI, AWS is deeply tied to Anthropic, and Alibaba is training Tongyi. The core business of the cloud giants began to shift from "renting IT to enterprises" to "training AI for the world."

But the chain reaction caused by this shift at the physical infrastructure level has surpassed all the accumulated common sense of the past 20 years.

The traffic characteristic of AI training is "east-west." Training a large model might require tens of thousands of GPUs to communicate with each other simultaneously, synchronizing the gradients they've calculated with each other. If any single line is slow, the entire training phase has to wait for it, turning tens of thousands of GPUs into "cars stopped at an intersection." Therefore, the demand for latency and bandwidth for east-west traffic is dozens of times higher than for the previous north-south traffic.

Before this, the vast majority of high-speed connections inside data centers were copper cables. Copper is cheap, easy to install, and has stable performance, making it the default option for data centers. However, the geometric structure of AI training clusters is precisely what copper cables dislike most. Tens of thousands of GPUs are distributed across dozens of cabinets, with distances often exceeding ten meters. Copper simply can't handle that distance. Optical fiber, on the other hand, has no distance limitation in this regard.

Overnight, the sparse networks that were previously sufficient became inadequate. Cloud giants had to re-lay fiber optics, denser than ever before.

The scale of this re-laying is already reflected in their capital expenditures. In 2026, the combined capital expenditure of the world's six largest cloud giants is expected to exceed $600 billion. The number of hyperscale data centers operational globally has reached 1,297, nearly three times the number at the beginning of 2018. In just 2026 alone, the number of new data centers is expected to exceed 150, with corresponding AI infrastructure spending exceeding $400 billion.

Market research firms estimate that the total demand for optical fiber from AI clusters is 10 to 100 times that of traditional cloud services. This is the fundamental reason why Corning can now sign four $6 billion mega-deals.

Between data centers, and between cabinets within a data center, all fiber optics must pass through something called a conduit. These are typically plastic or metal tubes with an inner diameter of 2 to 4 inches, buried underground or placed on racks. A key characteristic of these conduits is that once laid, it's very difficult to add more. Burying an additional conduit between cities means reapplying for right-of-way and digging up the road again, taking years. Adding an extra conduit to an already operational data center means shutting down for modification, taking months.

Conduit about to be buried underground. Image source: Internet

What Corning has been doing specifically for AI data centers over the past two years is to fit more fiber optics into existing conduits without adding new ones.

Besides making the fiber itself thinner, Corning also changed the arrangement of the fiber from a loose "spaghetti" style to a rollable flat ribbon. When needed, it's unrolled; when not, it's rolled up, and then tightly packed into the cable. An original 2-inch conduit could only hold a little over a thousand strands of fiber optics. Corning's new design can fit more than three thousand strands, directly doubling the capacity. For a 4-inch conduit with 6 such cables side-by-side, it can hold over twenty thousand strands, more than 6 times the traditional design.

Corning's rollable fiber optic ribbon. Image source: Corning

It's not just about fitting more; termination is also less labor-intensive. A 3,456-fiber cable, using traditional methods, would take over 200 man-hours to connect one strand at a time. Corning's ribbon design can reduce this to under 40 hours, while also cutting cable preparation time by 30%. Keep in mind, the US already faces a shortage of optical communications engineers.

During the construction of a large AI factory, every month of delay means significant GPU depreciation and postponed training tasks, costing in the hundreds of millions on paper. A product that can cut months of time and millions of dollars in engineering costs is an incredibly good deal, even with a 30% to 70% premium on the fiber itself.

Jensen Huang's "Unprecedented Scale"

On May 8th, Nvidia CEO Jensen Huang emphasized again in an interview that the next generation of AI infrastructure requires extensive optical connections, and copper wires can no longer meet the demand. He also stated that Nvidia would expand the application of optical technology at an unprecedented scale.

In the details of the investment transaction with Corning a few days prior, this "unprecedented scale" is indeed evident. Of the 18 million equity certificates, 3 million shares were essentially "free." This structure is rare in Nvidia's ecosystem investments over the past year, meaning Nvidia immediately obtained significant equity exposure to Corning without needing to use cash. It's more like a signing fee for a long-term partnership agreement.

And Corning is not the only piece Nvidia has bet on. Starting in September last year, Nvidia entered a new investment rhythm. First, the scale became larger. Second, the structure began to frequently use financial instruments like "frameworks," "options," and "prepaid warrants" to lock in commitments first and realize them in batches. Besides the $100 billion investment framework for OpenAI, Nvidia has consecutively invested tens to hundreds of billions of dollars in AI infrastructure companies like Anthropic, Intel, and CoreWeave.

The most easily overlooked part is its investment along the optical communication line. Apart from Corning, Nvidia also invested $2 billion each in Lumentum and Coherent, two of the world's largest optical device companies. Counting Corning's initial $500 million plus the $3.2 billion option, Nvidia has poured approximately $7.7 billion into the single sub-sector of optical communications.

When you put this investment table together, you realize it's essentially a checklist for building an AI factory: computing, networking, optics, power, cooling, software, customers, and models – Nvidia has locked in at least one key supplier for each layer. At this year's GTC conference, Nvidia integrated this full stack into a publicly released blueprint, unveiling a hardware reference architecture called Vera Rubin DSX and a digital twin solution called Omniverse DSX Blueprint. This whole package is essentially the "construction blueprint for an AI factory."

Building a GW-grade AI factory (equivalent to the electricity usage of 1 million households) takes 18 to 24 months from planning to operation, requiring coordination with over 100 suppliers. In the past, data center operators handled this themselves, each needing to redo interface verification. But Nvidia's Omniverse DSX systematizes this process. All partners' products have already been verified in Nvidia's digital twin, parameters have been aligned, and interfaces have been standardized. Cloud giants can simply buy directly following Nvidia's blueprints.

Jensen Huang unveils the AI factory blueprint platform at the 2026 GTC conference. Image source: NVIDIA

This is a crucial step for Nvidia's transition from a chip company to an "AI factory general contractor." As integration increases, profit margins expand. Even if AMD or Broadcom produces a GPU with equivalent performance tomorrow, replicating this supply chain coordination capability spanning chips, fiber optics, and the power grid would take them at least several more years.

Therefore, the true meaning of Nvidia's $3.2 billion option on Corning is to lock in a key player for the "localized optical communications capacity" slot in its AI factory construction blueprint. Of course, the one who can draw this blueprint right now is only Nvidia.