$LITR

first mention in our archive Apr 1, 2026 · latest 1mo ago

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@blackpanthercap1

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@blackpanthercapApr 1, 2026 · 5:56 PM

Jensen Huang just told you where the bottleneck is. Not in one investment. In a pattern. In March alone, $NVDA committed $2 billion each to $LITE and $COHR, both photonics companies. Then $2 billion to $MRVL. Then $2 billion to $SNPS. A stake in Nokia. A stake in OpenAI. A stake in Intel. That is over $10 billion deployed in a single month. All in the infrastructure layer of AI. All in the components that connect GPUs to each other, to memory, and to the world. Here is what that pattern tells you. The GPU is not the bottleneck. Nvidia is building millions of them. The bottleneck is the optical interconnect. The laser components. The silicon photonics that let GPUs in a data center talk to each other at the speed and scale required for modern AI training runs. $LITR makes the lasers that go inside data center transceivers. $COHR makes the optical networking products that connect those transceivers across rack-scale systems. $MRVL makes the custom silicon that manages how those signals get routed and processed. This is the physical plumbing of the AI factory, and Nvidia just spent $8 billion telling you that it is not optional. Now look at $AAOI. Applied Optoelectronics designs and manufactures its own Indium Phosphide lasers in-house. It has guided for $1 billion in revenue in 2026, a 119% increase in a single year. It has already received a greater than $200 million volume order for its 1.6T transceivers. And it just filed to receive a new technical presentation at an upcoming industry event. Nvidia has not made a direct investment in

That is the gap. But the company is building exactly what the Nvidia investment pattern says the world needs: Vertically integrated laser manufacturing. High-speed transceiver products for hyperscaler data centers. And a 2026 revenue ramp that puts it squarely in the photonics buildout. The risk is real: the expanded ATM equity program ($500M) creates dilution pressure, and an insider sold 29,000 shares in mid-March. Every bull case has a catch. But if the thesis is right, and $8 billion from Nvidia in a single month says it probably is, then