If you’ve been following AI infrastructure development, you’ve likely heard some version of this prediction: “Copper is hitting its limits. The transition to optical is inevitable. It’s happening now.”
There’s truth in that statement—but the reality playing out in data centers is more nuanced than a simple technology replacement cycle. Having spent my career in connectivity, working with hyperscalers and system architects, I can tell you that the more interesting question isn’t whether optical will displace copper, but rather where, when, and for which applications each technology makes the most sense.
The Pattern We’ve Seen Before
Throughout every major speed transition in my career, I’ve heard the same refrain: “This is it. This generation has to go optical. Copper can’t possibly keep up.”
And yet, copper continues to evolve and persist—not because it’s universally superior, but because it remains the optimal choice for specific applications, particularly short-reach, high-reliability connections where cost and complexity are critical considerations.
The copper-to-optical transition has never been a cliff. We’ve seen instead a continuous evolution in how we deploy these technologies based on the specific demands of each layer in the infrastructure. Copper dominates certain distance ranges, optical handles others, and the boundary between them shifts with each generation of technology.
Understanding the Critical Threshold
Here’s what’s actually happening: as we push data rates higher, we face a decision at each protocol upgrade—do we double the speed, or do we double the quantity of lanes?
This tick-tock progression means that for a time, copper can handle increased bandwidth by scaling up lanes. But eventually, we hit a frequency threshold where copper’s physical limitations become prohibitive. Based on current industry trajectories and discussions with infrastructure architects, 400 gigabits per lane appears to be that critical transition point where copper faces significant challenges within the rack.
Let me illustrate where we are today:
- Within the rack: Passive and active copper remain dominant for server-to-switch connections
- Rack-to-rack: active copper is the workhorse solution
- Row scale and beyond: Optical takes over
The physics are straightforward: as insertion loss increases with frequency, maintaining signal integrity over even modest distances becomes exponentially more difficult. At some point, the cable becomes too thick, too heavy, or requires too much power to be practical. Copper excels where the distance and frequency allow it; optical becomes necessary when those limits are exceeded.
The Workload Factor: Why Training and Inference Tell Different Stories
What makes this conversation particularly nuanced—and often overlooked—is how different AI workloads drive fundamentally different connectivity requirements.
For training clusters, we’re talking about interconnecting hundreds of thousands, potentially millions, of GPUs. These massive scale-up fabrics need to maximize both intra-rack connectivity and cross-data-center reach. As these clusters grow in density and scale, the portion of connections that copper can reliably serve shrinks, driving faster adoption of optical solutions for longer reaches within increasingly dense rack configurations.
For inference deployments, the picture looks quite different. Inference is fundamentally a memory-bound problem that typically requires connecting 8 to a few hundred accelerators—or up to 1,024 with emerging fabrics. Because these clusters are smaller and often deployed closer to end users rather than in massive centralized facilities, copper remains highly viable for the majority of connections. You’ll see more active copper, more retimers, and more PCIe-based architectures optimized for these moderate-scale deployments.
This workload-driven differentiation is critical and often missed in broader technology discussions. The optimal solution isn’t universal—it’s application-specific.
This workload-driven differentiation is critical and often missed in broader technology discussions. The optimal solution isn’t universal—it’s application-specific.
Active Electrical Cables: The Middle Ground
One technology gaining significant traction as a bridge solution is Active Electrical Cables (AECs). AECs integrate signal conditioning electronics—equalizers, amplifiers, and retimers—directly into the cable assembly, enabling reliable high-speed transmission over distances where passive copper fails but optical would be overkill.
AECs are experiencing dramatic growth driven by hyperscale deployments. Industry observers note that multiple cloud providers have standardized on AEC technology and are moving away from traditional direct-attach copper cables, particularly as AI infrastructure moves away from fully integrated vendor solutions toward more flexible, customer-designed networks.
AECs offer several compelling advantages:
- Extended reach: 5-7 meters compared to 2-3 meters for passive copper
- Substantial power savings: Industry observations indicate approximately 25% to 50% lower power consumption compared to active optical cables. With the increasing number of lanes in modern deployments, this can translate to multi-kilowatt power savings per rack—a significant reduction from both cost and rack power constraint perspectives.
- Reduced latency: Significantly lower than optical solutions requiring full DSP processing
- Cost efficiency: Positioned between passive copper and optical on the price spectrum
The technology is particularly valuable for medium-distance connections in distributed architectures where computational density is lower than in tightly-packed clusters. Major cloud providers are deploying AECs at scale for 400G and 800G connections within and between racks, particularly as infrastructure design prioritizes flexibility and cost-optimization alongside performance. How these get deployed—through front-panel pluggables, cable backplanes, or hybrid approaches—introduces additional design variables worth examining in depth, which we’ll explore in a future post.
Looking Ahead: Coexistence, Not Replacement
So where does this leave us?
The copper-to-optical transition isn’t happening uniformly—it’s progressing across a spectrum of applications with different timelines. Over the next several years, we can expect:
- Copper maintaining dominance for short-reach connections (sub-5 meters), cost-sensitive deployments, and inference-focused infrastructure—with architecture choices between front-panel pluggables and cable backplanes introducing their own performance and cost tradeoffs
- AECs becoming the preferred solution for up to7 meter connections, particularly as active copper scales to support 200G and eventually 400G per lane rates—performance characteristics and deployment strategies we’ll examine in a future post
- Optical expanding its footprint in training clusters, long-reach applications (beyond 7 meters), and increasingly in rack-scale architectures where hundreds of accelerators need tight coupling
- Hybrid architectures becoming the norm, where system designers strategically deploy copper, AECs, and optical based on specific connection requirements
The questions you should be asking aren’t “When will optical replace copper?” but rather:
- What workloads am I supporting?
- What are my cluster size requirements?
- What distances am I spanning?
- What’s my power budget?
- How important is cost optimization versus performance maximization?
The Value of Flexibility
The most capable connectivity partner isn’t one who pushes a single technology solution. It’s one who understands the full spectrum of options and can help you navigate the tradeoffs specific to your infrastructure needs.
At Astera Labs, we’re committed to supporting the entire connectivity spectrum—whether you’re deploying copper-based AECs for inference infrastructure, planning for optical scale-up networks in next-generation training clusters, or implementing hybrid architectures that leverage both. Our recent strategic investments position us to deliver purpose-built solutions across this technology continuum, from signal conditioning for high-speed copper to innovations enabling the next generation of optical connectivity.
The future of AI infrastructure isn’t binary. It’s a carefully orchestrated blend of technologies, each optimized for its ideal use case. And that’s exactly the Astera Labs approach.