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  "path": "/article/4139643/nvidia-partners-with-optics-technology-vendors-lumentum-and-coherent-to-enhance-ai-infrastructure.html",
  "publishedAt": "2026-03-03T01:28:24.000Z",
  "site": "https://www.networkworld.com",
  "tags": [
    "Artificial Intelligence, CPUs and Processors, Data Center, Industry, Markets, Technology Industry",
    "Brian Jackson",
    "Sanchit Vir Gogia"
  ],
  "textContent": "Nvidia on Monday announced strategic partnerships with Lumentum Holdings and Coherent which it said are designed to accelerate the development of advanced optics technologies used in AI data center infrastructure.\n\nThe agreements will see Nvidia invest $2 billion in each company to support their research and development and operations, and to build out or expand their US-based manufacturing capabilities.\n\nIn its announcements, Nvidia noted that optical interconnects and advance package integration are “foundational to the next phase of AI infrastructure, as they unlock ultrahigh-bandwidth, energy-efficient connectivity across AI factories.”\n\nEach nonexclusive deal includes what Nvidia described as a “multi-billion purchase commitment and future access rights for advanced laser components,” and a $2 billion investment in each organization to support R&D, future capacity, and operations as the companies build out their US-based manufacturing capabilities.\n\nBrian Jackson, principal research director at Info-Tech Research Group, said that with the two investments, “Nvidia is laying the groundwork for its future as a competitive provider of AI training infrastructure. While Nvidia has dominated this space over the last few years with its latest GPUs serving as the backbone of frontier AI model training, in the past 12 months, we’ve seen more deals signed by major AI developers with purpose-built silicon providers like Amazon and Google.”\n\nHe pointed out, “[this] indicates that alternatives to GPUs aren’t just more power-efficient ways to train AI, but also offer enough performance to satisfy best-in-class developers. Nvidia wants to make a leap ahead of the competition with its own next-gen chip manufacturing leap.”\n\nJackson added, “it also looks like the bet will be on photon transfer optics. Photonics-based computers have been in development as prototypes for more than a decade, and seek to address the physical limitations of copper as an electrical conduit.”\n\nBy relying on the transfer of light through glass, he said, “this architectural approach is more energy efficient and promises to be much faster than current chips. If Nvidia can mass-manufacture a next-generation GPU that integrates photonics right into its silicon, then they can solve a couple of big problems for AI developers: power consumption and speed.”\n\nSanchit Vir Gogia, chief analyst at Greyhound Research, said that the dual $2 billion investment “sends a signal about AI infrastructure bottlenecks: this is the moment where the industry quietly admits that AI scaling is no longer primarily a chip story. It is a communication story.”\n\nFor the last few years, he said, “the visible constraint was straightforward. Enterprises could not get enough GPUs. Hyperscalers reserved allocation. Vendors rationed supply. That was the first choke point. But once accelerators are deployed at scale, the bottleneck moves. It does not disappear.”\n\nGogia added that in today’s AI clusters, “each accelerator depends on dozens of high-speed links to talk to its neighbours. Multiply that across the rack and you end up with thousands of interconnects operating continuously. Every one of those links draws power. Everyone introduces latency and signal integrity considerations. Everyone carries a probability of failure.”\n\nWhat Nvidia is signalling is that the next bottleneck is the fabric itself, he pointed out. “You can add more GPUs, but if the network layer cannot scale proportionally, utilisation falls and economics deteriorate,” he said. “The company is moving upstream to ensure the arteries of AI infrastructure do not become the new point of scarcity. This is not a marketing flourish. It is a structural admission that the networking wall is real.”\n\nGogia noted that the emphasis on domestic manufacturing is not cosmetic language. It is strategic insulation. “Semiconductor supply chains are now entangled with national policy,” he observed. “Export controls, rare earth dependencies, and industrial subsidies have reshaped how advanced components move globally. Photonics is increasingly part of that strategic infrastructure.”\n\nBy supporting US-based fabrication expansion, Nvidia “reduces geopolitical exposure and aligns with domestic industrial priorities. This positioning may influence allocation decisions during supply stress,” he said.\n\nAnd for enterprises operating outside the United States, “this introduces a secondary consideration,” he said. “During capacity constraints, strategically aligned markets may receive preferential treatment. Procurement strategy must therefore factor in geography and policy alignment alongside price and performance.”\n\nRegardless of location, CIOs and senior network executives planning AI factory deployments should now stop treating the optical fabric as a networking detail. “Budget assumptions should incorporate interconnect density growth, projected energy per bit efficiency, redundancy models, and vendor concentration risk,” he said. “Optical roadmap transparency should be a formal part of vendor due diligence.”\n\n“[Contracts] should address supply allocation rights and upgrade pathways,” he noted. “AI ROI models should include GPU utilization impacts tied to network performance. Sustainability reporting should account for interconnect power draw, not just server efficiency.”\n\nIn addition, he said, “failure domain mapping should reflect optical integration blast radius, not just server node failure. AI infrastructure governance must evolve from server-centric thinking to system-centric planning. The fabric layer now belongs on the board agenda.”",
  "title": "Nvidia partners with optics technology vendors Lumentum and Coherent to enhance AI infrastructure"
}