AI Is Running Too Fast for Fiber? CPO Is the Lifeline of Data Centers

Why Is AI Too Fast for Fiber to Keep Up?

When you ask ChatGPT a question, the AI model behind it is running a “data relay marathon” across thousands of GPU chips. During training and inference, these AI models transmit massive volumes of data back and forth—imagine a torrent of information flowing through countless compute nodes. Every bit of delay and loss could slow down overall system efficiency and become a bottleneck.

This type of chip-to-chip data exchange has far surpassed the limits of traditional electrical transmission. It’s as ridiculous as expecting a mailman to keep up with a supercar. As AI models reach the scale of hundreds of billions of parameters, data transfer isn’t just large—it’s explosive. This creates an urgent need to fundamentally reengineer the underlying transmission infrastructure.

In fact, the issue isn’t just insufficient speed, but whether the entire system can continuously scale and remain stable. Many data centers now face hidden challenges like complex wiring, overwhelming power consumption, and module interference—all of which ultimately manifest as service delays and rising operational costs.

This is why Co-Packaged Optics (CPO) has become the new darling of data centers. It’s a solution that brings light directly into chip packaging, allowing signals to race through without detours. More than just a technological upgrade, it’s a survival tool for managing AI’s data deluge.

What Is CPO?

CPO refers to the integration of optical components (like silicon photonics chips) and switch ASICs into a single package, reducing transmission distance and signal loss. This integration represents a new-generation mindset: instead of assembling modules later, all high-speed transmission components are designed as a unified system from the start.

Traditional optical modules are pluggable, like inserting RAM into a motherboard. CPO, on the other hand, is like having RAM soldered directly to the board—it boosts space efficiency, reduces power consumption, and minimizes latency. Crucially, it also lowers optical-to-electrical conversion loss, ensuring signal integrity and maximizing data throughput—vital for AI-scale computing.

CPO’s architecture enables designers to create denser, lower-loss transmission links within the chip itself, bypassing traditional I/O bottlenecks. This means future chip communication could function like high-speed neurons, supporting more powerful and intelligent AI applications.

First proposed by giants like Intel and Broadcom, CPO is now on track to become the standard for high-end data center design—especially for AI workloads. In addition to hyperscalers like Google, Amazon, and Meta, chipmakers such as NVIDIA and AMD are actively developing CPO-enabled packages. This race isn’t just about bandwidth; it’s about seizing control over the future of computing ecosystems.

Why Data Centers Need CPO

1. Explosive Bandwidth Growth

With the rise of large AI models like GPT-4, Gemini, and Claude 3, individual training tasks require hundreds of terabytes of data, with real-time transfer speeds exceeding hundreds of gigabytes per second. These models are not only massive in parameter size but also demand huge training datasets, exponentially increasing internal data center communication.

AI training and inference bandwidth demands double almost annually. According to internal reports from Google and Meta, internal traffic within data centers has already surpassed external connections—and accounts for the largest share of total energy consumption. This forces data centers to find more efficient alternatives than copper wires or standard optical modules. CPO fits the bill.

2. Copper Wire Transmission Has Hit Its Limit

Once data rates exceed 100 Gbps, copper wires suffer severe signal degradation—even with top materials and shielding, the issue cannot be fundamentally resolved. Adding more copper lanes to server motherboards also introduces routing complexity and interference, increasing both design difficulty and cost.

Optical fibers, in contrast, offer low-loss, long-distance high-speed transmission. However, traditional optical modules are mounted on system peripheries and still rely on electrical intermediates, causing additional latency and power loss. CPO solves this structural flaw by bringing light transmission directly into the packaging core—enabling true low-latency, high-bandwidth transmission.

3. Optical Transmission Is Efficient, But Modules Are Bulky

Although optical transmission dramatically improves power efficiency, traditional optical modules are bulky, hard to assemble, and require significant cooling—posing serious space and thermal challenges. In data centers, every square inch must be maximized for performance, and oversized modules prevent optimal scalability and compute density.

CPO minimizes module size and brings optics closer to chip cores. It can be integrated with advanced packaging technologies like CoWoS and InFO. Compared to conventional designs, CPO improves overall energy efficiency by 30–50%. As AI models scale further, this efficiency will be the key to sustainable expansion.

Technical Progress: From Silicon Photonics to CPO Ecosystems

CPO’s foundation lies in the maturity and mass production of silicon photonics. This technology integrates light emitters, modulators, receivers, and waveguides directly into a chip using CMOS processes, allowing optical components to coexist with logic circuits. This dramatically reduces manufacturing costs and footprint.

However, this integration isn’t easy. Current CPO challenges include:

• Extremely precise optical-electrical signal coupling—any deviation results in signal loss;

• High-accuracy alignment and bonding during packaging, requiring advanced automation;

• Thermal management for multi-channel high-frequency modules.

The focus today isn’t just “can we build it,” but “can we mass-produce it” while meeting data centers’ strict demands for cost, size, and maintainability. NVIDIA has announced built-in optical modules for its Blackwell architecture, Broadcom has introduced 800G CPO products, and is testing with Microsoft Azure.

Meanwhile, standards bodies like OIF (Optical Internetworking Forum) and COBO (Consortium for On-Board Optics) are drafting multi-vendor-compatible CPO specifications, aiming for commercial readiness by 2025.

Taiwan’s CPO Advantage

Taiwan’s global leadership in semiconductor manufacturing and packaging makes it a natural CPO powerhouse. TSMC has integrated optical interfaces into its CoWoS advanced packaging platform. Through its Photonic IC Program, TSMC is developing its own photonic engine—COUPE—slated for production by 2026, targeting top-tier AI clients worldwide.

Packaging leaders like ASE and Powertech are also investing in optical packaging technologies, creating high-density, low-loss optical connectors for system-level integration. Taiwan’s component supply chain—including Unimicron, Etron, EPISTAR, and Ennostar—boasts mature capabilities in silicon photonics and transceiver manufacturing.

In short, Taiwan is poised to play a full-stack role in the global CPO supply chain—from process to module to system integration. It can serve both U.S. and Asia-Pacific cloud providers and become a strategic hub for AI chip packaging and interconnect innovation.

Market Trends: CPO—Hype or Long-Term Structural Demand?

According to Yole Intelligence, the global CPO market was worth $100 million in 2023 but is projected to exceed $2.4 billion by 2028—with a CAGR of over 80%. Over 80% of demand will come from AI data centers, with the rest from high-frequency trading, military radar, and satellite communications.

This isn’t marketing hype—it’s the result of structural changes. As traditional servers evolve into GPU-centric AI clusters, bandwidth upgrades move from terabits per second to petabits per second, and single-device communication shifts to cluster-wide interconnects. CPO is currently the only technology capable of balancing cost, power, and size at this scale.

Governments are also treating CPO as critical infrastructure: the U.S. CHIPS Act funds silicon photonics and optical module R&D, while China pushes for domestic CPO alternatives. CPO is moving from lab prototype to strategic technology with geopolitical implications.

Conclusion: AI Is the Brain, CPO Is Its Optic Nerve

If AI is the brain of the future, then CPO is its optic nerve—connecting chips like neurons and transmitting not just signals, but the lifeblood of information. It enables seamless operation for large language models, vision AI, and autonomous systems.

In this AI-driven infrastructure race, whoever can transmit data faster, more reliably, and more efficiently will dominate. CPO’s electro-optical integration isn’t just a technical milestone—it redefines industry competitiveness and determines the next cloud superpower.

CPO’s evolution will reshape data center architecture and trigger a new wave of hardware innovation. As optics move from an optional add-on to a design cornerstone, we step into a new era—one where light drives intelligence.

CPO is the key technology that prevents data bottlenecks and keeps AI from waiting on transmission.