How NVIDIA's Vera Rubin AI Factory Is Driving the Next Generation of PCB Manufacturing

Artificial intelligence is becoming a driver of the industries. Adoption of AI across sectors like manufacturing, healthcare, transportation and others is being driven by advances in large language models, automation, robotics, and data-driven applications. According to market forecasts , the global AI market is expected to reach USD 601.93 billion in 2026 and grow to USD 3,638.08 billion by 2033, representing a CAGR of 29.3%.

The size and complexity of AI models are increasing rapidly, leading to a surge in computing infrastructure needs. This demand has accelerated the development of AI factories - next-generation data centres designed for AI workloads, specialized computing facilities designed to support large-scale AI training, inference, and advanced applications.

Thus, much attention is being paid to Japan’s project on NVIDIA’s Vera Rubin AI Factory . The facility will be developed in collaboration with Noetra with support from Japan’s Ministry of Economy, Trade and Industry (METI) and will feature 13,750 Vera CPUs, 27,500 Rubin GPUs and 140 MW of data centre capacity. It will provide computing support for Japan’s FRONTia initiative, backing applications such as AI agents, digital twins, robotics and physical AI.

More importantly, the project has relevance far beyond AI chips. Building out the AI infrastructure of the future at scale requires sophisticated servers, networking systems and power solutions – all dependent on increasingly sophisticated printed circuit boards (PCBs) . As computing performance increases the demand for PCB layer count, signal integrity, material performance and manufacturing precision increases.

This articleexplores how NVIDIA’s Vera Rubin AI Factory is powering the next generation of PCB manufacturing, and how the growth of AI infrastructure will bring opportunities and challenges for PCB manufacturers, OEMs, and procurement teams.

What Makes the Vera Rubin AI Factory Different?

Artificial intelligence is growing rapidly and the computing infrastructure is being transformed radically. For decades, traditional data centres have been the go-to infrastructure for general-purpose computing, but the growing complexity of AI models demands a new type of infrastructure optimized for large-scale AI workloads.

NVIDIA’s Vera Rubin AI Factory is an example of the shift to a “AI-centric” computing environment. An AI factory is not just a computing power source. It is dedicated to the continuous development, deployment and scaling of advanced AI applications through closely integrated computing systems and infrastructure.

AI Factory vs. Traditional Data Center

AI factories and traditional data centres both provide computing power, but differ greatly in their architecture and operational purpose. Traditional data centres cater mainly to cloud, enterprise software and data storage use cases, while AI factories are designed for handling large data volumes for AI training, inference and other intelligent use cases.

As AI models become bigger and more complex they require orders of magnitude more computing power than traditional applications. Large language models, autonomous systems, and physical AI solutions all require continuous data processing and high-speed computing. So the AI factories are built to provide the massive computing power that is required to train and perform inference on large-scale AI.

The AI factory design also includes the entire AI development lifecycle, from data processing and model training to the deployment of AI applications in real-world contexts. This makes it a key enabler for future technologies such as digital twins, robotics and industrial automatization.

Why This Project Matters to the Electronics Industry

Vera Rubin AI Factory project is a major change in technology in the world. As AI transitions from the experimental stage to practical application, industries from manufacturing and logistics to healthcare and robotics are increasingly dependent on sophisticated computing infrastructure to fuel AI-driven innovation. Also, the establishment of large-scale AI infrastructure drives the demand for a strong electronics industry ecosystem. To build and run AI facilities, you need not only powerful computing platforms, but also sophisticated hardware components, high-performance networking systems and reliable supporting technologies. Therefore, the development of AI infrastructure can have a substantial influence on several segments of the electronics supply chain.

A good example of a broader trend toward long-term investment in AI infrastructure is the “Vera Rubin AI Factory” project. Data on market growth shows that as AI applications grow in a variety of industries, governments and technology companies around the world are investing more in large-scale computing facilities to support the future development of AI technology.

The electronics industry too will experience new opportunities and challenges as AI infrastructure projects become more global. Companies designing, building and managing hardware supply chains will need to meet ever more demanding requirements for performance, reliability and scalability.

Why AI Factories Are Creating New Demand for Advanced PCBs

The rise of “AI factories” has not only increased demand for computing power but also changed the hardware requirements to support them. When AI workloads become larger and more complex, servers need to process more data faster, with lower latency and more efficiently. The performance improvement is driven by the demand for advanced PCBs that can support ever more demanding system architectures.

Higher Compute Density Requires More Complex Server Boards

One of the major differences between traditional data centres and AI factories is the high density of the computing resources. AI workloads require thousands of processors to work together efficiently, making designing server systems more complicated.

Today's AI servers pack multiple high-performance GPUs into a single system. As the density of GPUs increases, server motherboards need to fit more components, more connections, and more complex routing layouts in a limited footprint. It means a need for bigger and more complex PCB structures that can accommodate higher levels of integration.

The increase in the number of processors and supporting components often drives the need for a higher layer count in PCBs to handle the routing needs for high speed signals, power distribution, and system interconnects. Thus, the development of AI infrastructure is boosting demand for server PCBs with higher structural complexity and performance.

Faster Interconnects Demand Better Signal Integrity

The operation of AI factories relies on high-speed communication between thousands of computing units. In order to meet the performance needs of AI training and inference, data needs to communicate between GPUs, processors, storage systems and network equipment with ultra-low latency.

High speed interconnect technologies like NVIDIA NVLink allow fast communication between computing components. As the transmission speeds increase, it becomes more and more difficult to maintain the quality of the signal. Signal loss, interference, or timing issues can compromise system performance and reliability.

Therefore, AI infrastructure requires higher PCB signal integrity. In advanced server systems, PCB designs require high-speed data transmission, stable electrical performance, and controlled impedance to ensure reliable communication in complex computing networks.

Increased Power Density Raises PCB Design Requirements

AI computing systems consume much more power than traditional servers because many high-performance processors work at the same time. As AI data centre computing power keeps soaring, power delivery has turned into a key element for maintaining system performance and stability.

With increased power requirements, PCBs are required to enable efficient power distribution across the system. Circuit boards are required to carry heavier electrical loads and to maintain stability during operation at continuous high loads.

At the same time, the higher power density leads to substantial difficulties in thermal management. AI servers generate a lot of heat when they’re running, so it’s important to manage that heat well to keep the systems reliable and the hardware lasts longer.

Thus AI infrastructure requires PCBs with demanding specifications for power delivery, thermal performance, and long-term reliability. With the proliferation of AI data centres around the world, these factors are getting more and more important.

How PCB Manufacturing Must Evolve for AI Infrastructure

AI infrastructure is advancing rapidly, pushing up the bar for PCB manufacturing performance and production capabilities. As AI systems are evolving, PCB manufacturers will need to enhance their material expertise, manufacturing precision and quality control systems to better support demanding applications.

Next-generation electronics require more than the production capacity of PCB suppliers – they require a deep understanding of material properties, advanced manufacturing processes and rigorous reliability management. Those manufacturers who can combine these strengths will be best placed to satisfy the growing market demand for high-performance electronic systems.

Advanced Materials for High-Speed Applications

Material selection is playing an increasingly important role in the development of high performance PCBs. However, with the increase of the signal transmission speed, the conventional materials often can not provide the electrically performance for stable and reliable operation.

Low-loss materials are being increasingly used in advanced PCB applications to reduce signal attenuation and help maintain signal integrity during high speed transmission. This also gives high-Tg laminates better thermal stability, enabling PCBs to survive the harshest operating conditions.

Therefore, PCB makers must have good material selection capabilities and reliable supply chains to fulfill the various requirements of different applications. Supported by several leading material suppliers, PCBMASTER has built a strong supply chain , providing the most suitable material solution for different PCB applications, such as high frequency, high speed and advanced multilayer boards, and guaranteeing timely delivery even in the case of raw material shortages .

Higher Manufacturing Precision

As electronic systems become smaller, and performance requirements increase, the accuracy required in the PCB manufacturing process increases. More sophisticated applications require even tighter control of board construction, interlayer registration and circuit precision.

The ability to manufacture fine lines is a critical factor in realizing complex PCB designs with high circuit density. The more complex the board structure, the more sophisticated processes the manufacturer can use to make the interconnects smaller and more precise (laser drilling, for example).

Additionally, the exact positioning of the layers is crucial for multilayer PCB’s consistent performance. PCBMASTER is dedicated to high precision PCB manufacturing, stable quality and reliable performance supported by advanced production equipment and strict process controls.

Stricter Quality and Reliability Standards

The high demand of electronic products with better performance requires advanced designs and implementation of strong quality assurance at all stages of manufacturing process. The increasing demands of PCB products necessitate the manufacturers to perform the comprehensive inspection and testing processes to guarantee the reliability of the products. Automated Optical Inspection (AOI) is used to identify possible defects during the manufacturing process. Electrical testing is used to ensure the circuit boards meet the required performance metrics. Besides, the reliability verification can ensure the long-term stable operation of PCBs.

PCBMASTER performs quality control throughout the manufacturing process, from start to finish. The company guarantees quality standards of each PCB by AOI, flying probe testing, electrical testing and final quality inspection. UL certified, RoHS compliant, IATF 16949 and ISO 9001 compliant and assures customers in many different industries consistent performance.

As AI infrastructure grows, PCB manufacturing technology will continue to develop with more precision, higher reliability and more advanced technical capabilities. This will allow OEMs and tech companies to build a more reliable hardware foundation for advanced AI use cases with manufacturers like PCBMASTER who have the material know-how, high-precision manufacturing and comprehensive quality management.

What This Means for PCB Buyers and OEMs

The rapid development of AI infrastructure has sped up the upgrade of PCB manufacturing ability but also posed new challenges for procurement in the electronics industry. As the demand for sophisticated electronic systems rises, PCB buyers and OEMs must go beyond the product itself and consider capacity planning, supplier capabilities, and supply chain stability to ensure reliable production and support long-term business growth.

Capacity Planning

As AI infrastructure and other advanced applications continue to expand, the need for high-performance PCBs will likely continue to grow. Such a demand increase could put a strain on production capacity for high-end PCBs and could possibly extend lead times for complex projects.

Buyers of PCBs need to be thinking about that early in their planning process to avoid capacity issues. Good vendors with enough manufacturing capacity can reduce delivery risk and smooth the transition from product development to mass production.

Early communication with PCB manufacturers also helps OEMs to forecast demand and better coordinate production, particularly for projects requiring long term supply stability.

Supplier Selection

The requirements for the products are getting more and more stringent and so the choice of the right PCB supplier is more important than ever. Buyers need to look at the supplier’s capabilities holistically – engineering support, manufacturing experience, quality systems and the ability to support them in multiple points of the production process.

A good PCB partner is more than just a board manufacturer to spec. They offer technical support from design collaboration to Design for Manufacturability (DFM) consulting, production management and quality control throughout the product lifecycle.

PCBMASTER offers complete manufacturing capabilities to provide customers with one-stop support from technical assessment, design collaboration, material selection, PCB fabrication, quality inspection, to volume delivery. Solutions include high frequency PCBs, HDI PCBs, rigid flex PCBs, flexible PCBs and metal core PCBs. With decades of experience in automotive, telecommunication, industrial control and consumer electronics, PCBMASTER helps customers to make trade off between performance requirements, manufacturability and production efficiency.

PCBMASTER meets internationally recognized quality standards, including IATF 16949, ISO 9001, UL certification, and RoHS compliance, ensuring strict and consistent quality control throughout the manufacturing process.

Supply Chain Strategy

PCB buyers should also consider long-term supply chain stability beyond supplier selection. The availability of raw materials, the ability to maintain continuous production and the ability to manage risks, are some of the factors that directly affect the delivery of products and the normal operation of business. A resilient PCB supply chain requires reliable materials and good communication and close collaboration between customers and manufacturers. OEMs can partner with experienced PCB suppliers to help offset the unknowns such as changes in material pricing, market changes and increased demand.

The longer you work with a PCB manufacturer, the closer you become and the more predictable your planning becomes. As AI infrastructure and other advanced technologies continue to grow, companies with strong PCB supply chain strategies will be better positioned to capture future market opportunities.

The Future of AI Infrastructure and PCB Manufacturing

NVIDIA’s Vera Rubin AI Factory may not be a one-off project. The rapid adoption of AI will also lead to increased global investment in AI infrastructure, opening up new opportunities for the electronics industry. There are a number of important trends that will affect the future of AI infrastructure and PCB (Printed Circuit Board) manufacturing going forward.

AI Factories All Around

AI factories will be a core part of digital infrastructure as organizations scale AI. We’ll likely see additional governments and technology companies build out dedicated AI computing centres as demand for AI training and inference increases.

New Applications Will Be Enabled By Robotics And Physical A I

The next wave of AI growth will extend beyond software to physical AI applications such as robotics, autonomous systems and digital twins. As these technologies mature, more powerful computing infrastructure will be needed to support real-time processing and decision-making.

Edge AI W ill C ontinue to E volve A long with C entralized C omputing

“AI factories will be able to deliver huge amounts of computing power, but increasingly, AI workloads will be moving to the edge of data generation. The demand for AI infrastructure will only grow as edge AI continues to grow in smart manufacturing, autonomous vehicles and industrial automation.

Demand for H igh- P erformance PCBs W ill C ontinue to R ise

As AI infrastructure continues to develop, the demand for high performance PCBs will likely increase steadily. Whether it’s supporting large-scale AI factories or edge AI devices, trusted, high-quality PCB solutions will continue to be relied upon for advanced electronic systems.”

The future of AI isn’t just software. As the infrastructure of computing evolves, PCB technology will continue to be an important cornerstone for enabling the next generation of intelligent systems.

Conclusion

“AI factories” are a new phase of AI infrastructure. As investments in larger, more powerful computing platforms continue to grow, so too does the demand for AI training and inference hardware and emerging applications, including robotics, digital twins, and edge AI.

This also puts higher demands on PCB (Printed Circuit Board) technology. Next generation artificial intelligence systems are increasingly dependent on high performance printed circuit boards– creating an urgent need for advanced materials, precision manufacturing processes and rigorous quality standards. This means PCB manufacturers and procurement teams must be ahead of the curve with growing technical and supply chain needs.

This trend provides an opportunity for PCB manufacturers such as PCBMASTER to apply their engineering expertise and advanced manufacturing capabilities to build a strong support infrastructure for next generation AI infrastructure. As the need for AI technology adoption continues to accelerate, the need for OEMs to partner with experienced PCB providers to bring reliable, high-performance electronic products to market will only increase.

FAQs

1. What is an AI factory ?

AI factory is a specialized computing facility for training, deploying and running AI models at scale. AI factories, unlike traditional data centres, are designed for AI workloads, with high-performance GPUs, advanced networking, and large-scale computing infrastructure to support applications like generative AI, robotics, and digital twins.

2. How do AI factories increase demand for advanced PCBs?

AI factories need powerful servers, high-speed interconnects and reliable power delivery systems. These requirements create the demand for high-layer-count PCBs, high-speed PCB materials, and precision manufacturing to enable increased computing performance and long-term reliability.

3. Which industries will gain the most from AI factory development?

AI factories are anticipated to cater to a diverse range of industries including manufacturing, healthcare, logistics, autonomous vehicles, robotics, telecommunications, and industrial automation. As AI adoption increases, these industries will rely more and more on more advanced electronic hardware.

4. What should PCB buyers take into consideration when choosing a supplier for AI-related projects?

For PCB buyers, they need to consider the engineering expertise, manufacturing capability, quality management system, production capacity and supply chain stability of the suppliers. Having a collaboration with an experienced PCB manufacturer may reduce the risks related to the development and assures a consistent product quality, from the prototyping to the mass production.

5. How does PCBMASTER contribute to the growing AI infrastructure market?

PCBMASTER offers customers end-to-end PCB manufacturing services from engineering consultation and material selection to PCB fabrication, quality testing and volume production. PCBMASTER has expertise in the manufacturing of high-frequency PCB, HDI PCB, rigid-flex PCB, flexible PCB, and metal core PCB, and helps customers to design reliable PCB solutions for high-performance applications, including those that power the next generation AI infrastructure.

About the Author

Carol Luo

PCB Design Engineer

I'm Carol, a PCB Engineer at PCBMASTER with experience in PCB design and manufacturing engineering since 2018. I focus on translating engineering requirements into reliable PCB solutions, with expertise in stack-up design, material selection, and design-for-manufacturing (DFM). I share practical engineering insights from real-world PCB design and production experience.

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