Nvidia is investing $2bn each in Lumentum Holdings and Coherent as part of separate multiyear agreements aimed at advancing research and development (R&D) in advanced optical technologies for future AI infrastructure.
The funding will support both companies’ efforts to expand their US-based manufacturing capacities and to accelerate innovation in critical components for AI data centres.
Lumentum will use the investment from Nvidia to increase its manufacturing capabilities and further its R&D activities. The company, based in San Jose, California, develops optical and photonic technologies that are integrated into AI systems, cloud computing, telecommunications, industrial manufacturing, and sensing applications.
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With global research, manufacturing, and sales operations, Lumentum plans to build new fabrication facilities in the US to meet the growing demand for high-performance lasers, modules, and optical subsystems.
Nvidia founder and CEO Jensen Huang said: “AI has reinvented computing and is driving the largest computing infrastructure buildout in history.
“Together with Lumentum, Nvidia is advancing the world’s most sophisticated silicon photonics to build the next generation of gigawatt-scale AI factories.”
Coherent will allocate Nvidia’s investment towards scaling up its research and manufacturing operations as it expands its US facilities.
Founded in 1971 and operating in more than 20 countries, Coherent specialises in photonics technologies used by data centres, communications networks, and industrial markets.
The company offers a portfolio of laser products that are said to be essential for efficient data centre connectivity and advanced telecommunications. Coherent intends to leverage the new funds to address increasing industry requirements for advanced optical networking products.
Coherent CEO Jim Anderson said: “This strategic relationship underscores Coherent’s role as a key enabler of next-generation AI data centre infrastructure.
“We are proud to expand our 20-year relationship with Nvidia by increasing their access to include multiple product families to help them build the AI data centers of the future.”
Both agreements with Nvidia are nonexclusive and include multibillion-dollar purchase commitments as well as future access rights to capacity for advanced laser components and optical products. These arrangements are designed to provide Nvidia with a secure supply of critical parts needed to scale up next-generation AI factories while supporting energy-efficient connectivity across large-scale networks.
Nvidia and Deloitte expand collaboration to accelerate physical AI solutions
Separately, Nvidia and Deloitte have broadened their collaboration, focusing on the development of physical AI solutions across several fields. This expansion will see both companies working on new offerings that utilise digital twin technology, computer vision, and edge robotics, targeting organisations seeking to speed up deployment of intelligent machines while managing operational risks.
Under this initiative, Deloitte is harnessing Nvidia’s Omniverse software libraries to help clients simulate complex operations, improve real-time awareness, and adopt AI-driven systems at scale. The company is applying these technologies in manufacturing and life sciences sectors.
In the automotive sector, Deloitte is supporting customers by building digital replicas of factories and warehouses, which can be used to plan workflows, enhance operational throughput, bolster worker and equipment safety, and manage costs more effectively.
In healthcare and related fields, Deloitte is assisting firms to integrate humanoid robotics into their operations by combining simulation technology, synthetic data generation, teleoperation capabilities, and real-world validation. This approach enables a secure and scalable deployment of embodied AI systems.
Additionally, Deloitte has rolled out advanced computer vision tools powered by Nvidia platforms at an automotive manufacturing plant operated by Horse Powertrain in Valladolid, Spain.
As part of a recent internal efficiency project at the facility, Deloitte introduced machine learning algorithms designed to detect equipment anomalies early, improve inspection processes, and reinforce quality control decision-making within engineering teams.
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