Paid Report: 2025 Annual Industry Deep Dive — Optical Communications and AI Interconnect
The "speed-of-light" rebuild of AI infrastructure: when interconnect becomes the new compute, who wins the next trillion-dollar race?
⚠️ Reading Notes and Copyright
[Not investment advice] This report reflects only the author's personal industry observations and technical analysis. It is intended for research reference and to stimulate thinking, and does not constitute investment, trading or legal advice of any kind. Investors should make independent judgments, evaluate carefully, and bear their own investment risks.
[All rights reserved — no reproduction] This is a paid, subscriber-only article that reflects a substantial amount of industry research and data analysis. Without the author's formal written permission, please do not repost, excerpt, screenshot or publicly distribute any part of it in any form. Respecting original work and intellectual property is the biggest support for continued in-depth content.
[Support the author and follow the trends] If you enjoy this kind of system-level industry analysis, visit my website Simple Tech Trend, or follow me on Instagram and Threads: simple_tech_trend for the latest tech insights and perspectives.
Your support is what keeps this research going. Beyond this article, I also publish other paid deep-dive reports on key technologies and industry trends — learn more and subscribe via the links below:
Executive Takeaway
In 2025, AI infrastructure crossed a critical threshold.
The industry's core constraint is no longer "is there enough compute," but whether that compute can actually be used effectively.
While GPU theoretical performance (FLOPS) keeps doubling, real-world training efficiency is increasingly limited by latency, bandwidth, power and cooling — for the first time, interconnect has replaced compute itself as the first bottleneck of AI systems.
That is why, starting in 2025, the AI narrative shifted from "grabbing GPUs" to "re-architecting the system."
The core thesis of this report: the unit of AI compute has undergone a structural shift.
In the past, the basic unit of compute was the "server"
In 2024, it was the "GPU node"
In 2025, compute was formally upgraded to the "rack and the fabric"
This shift is not a concept — it is a reality already validated in deployment.
NVIDIA's GB200 / GB300 NVL72, Google's TPU v7 Ironwood, and the custom AI racks of AWS and Meta all convey the same message:
A single server can no longer carry AI's performance density; AI systems must be designed starting from the rack, or even the data center.
Under this new architecture, "effective compute" no longer depends on the chip alone, but on three system-level factors:
Whether interconnect can keep pace with rising compute density
Whether power and cooling allow sustained full-load operation
Whether the network topology can be dynamically reconfigured to match AI traffic patterns
This is exactly why 2025 became the turning point for optical communications and advanced interconnect.
In scale-up (inside the rack), copper is still the best answer for latency and cost, but it is clearly approaching its physical limits; optical I/O and CPO have entered real design discussions.
In scale-out (between racks), 800G has become mainstream and 1.6T is sampling; optical modules are no longer just a bandwidth upgrade but part of system power management.
In scale-across (between data centers), Google has already proven with OCS that reconfigurable optical topologies can significantly cut power and capex while raising overall throughput.
Together, these changes point to one conclusion:
Optics is no longer just an I/O component — it is a core variable in system design.
For the competitive landscape, this also means value is being redistributed.
After 2025, the players with durable advantage are not necessarily the chipmakers with the most compute, but those able to:
Define rack and fabric specifications
Control SerDes, switches, DSPs and interconnect protocols
Integrate optics, power and cooling into manufacturable systems
This is why NVIDIA chose to open up NVLink Fusion, Broadcom and Marvell are aggressively positioning for 1.6T and CPO, Astera Labs and Credo are rising fast in the seemingly unglamorous interconnect layer — and why the optical supply-chain bottleneck is shifting from demand to manufacturing and volume-production capability.
Looking ahead to 2026, this report sees three high-conviction trends already taking shape:
AI architecture fully enters "rack-level thinking"
Interconnect and optics penetration will keep outgrowing the overall AI market
The real alpha will appear in the system-level supply chain beyond the GPU
The goal of this report is not to predict that one technology will replace another, but to provide a decision framework that helps readers understand:
how compute, interconnect, optics and cooling are being repriced in the AI factory era — and who is best positioned to benefit from the next trillion-dollar race.
Preface: AI's Second Movement — From "Stacking Compute" to "Re-architecting the System"
0.1 Core View: Why Is 2025 the Watershed for AI Infrastructure?
If the theme of 2023 and 2024 was "buying up GPUs," then in 2025 we formally entered the second movement: "the system re-architecture of the AI factory."
In the past, the unit of data-center compute was the "server"; now it is the "rack," or even "the entire data center." The root cause is that single-GPU compute (FLOPS) is growing far faster than interconnect bandwidth, so interconnect has replaced compute as the biggest bottleneck to AI training efficiency.
In 2025, we witnessed three major structural changes:
.....
0.2 Key Numbers at a Glance: Capex "Arms Race 2.0"
Chapter 1: The Architecture Revolution — The Rack Is the Computer (System Architecture)
1.1 NVIDIA NVL72 / GB200: 120 kW of Extreme Electromechanical Engineering
1.2 Google Ironwood TPU Rack: A 3D Torus Built for Long-Term Scaling
Unlike NVIDIA's pursuit of maximum density in a single rack, the Ironwood TPU Rack (TPU v7) Google showed at Hot Chips embodies a different design philosophy: system predictability and long-term scalability.
Sticking with 3D Torus: Google continues its signature 3D Torus interconnect topology. One Ironwood rack holds 64 TPUs forming a 4x4x4 cube. This lets chips talk to each other directly (ICI, Inter-Chip Interconnect) without relying on a single layer of giant switches (such as NVSwitch), natively supporting model parallelism.
1.3 Meta Catalina: The Pragmatist's AI Rack
1.4 The Endgame of Cooling: Liquid Cooling Reshapes the Power Structure
Chapter 2: The Optical Explosion — Breaking Physical Limits (Optical Interconnects)
This chapter analyzes the structural turning point of the optical communications industry in 2025. As the reach of electrical signals over copper shrinks to under 1 meter, optics is being forced from "data-hall connectivity" into "chip packaging," triggering the route battle between CPO, LPO and OCS.
2.1 The Three Battlefields of Interconnect: Scale-Up, Scale-Out, Scale-Across
In the AI era, the concept of the "network" has been redefined. According to the latest classification from NVIDIA and the OIF (Optical Internetworking Forum), interconnect is split into three battlefields with very different bandwidth, latency and reach requirements — and each has a different technology winner.
....
2.2 The Key Technology Route Battle: CPO vs. LPO vs. OCS
In 2025, the three technology routes are no longer theoretical debates; they have entered real-world validation of "which problems they can actually solve."
.....
2.3 The Last Mile of Silicon Photonics (SiPh)
Chapter 3: The Giants' Chess Game — Alliances in Chips and Connectivity (Company Strategy)
As the unit of compute moves up from the "chip" to the "rack" and the "fabric," the nature of competition changes too. Whoever controls the system's "entry points" and "highways" gets to define the specs of the AI factory.
3.1 NVIDIA: From Chip Vendor to the AI Factory's "General Contractor"
3.2 Broadcom: The Confidence of a $73B Backlog
3.3 Marvell: The Disruptor in Optical Interconnect
3.4 Connectivity Enablers
3.5 The Two Optical Component Leaders: Lumentum & Coherent
Chapter 4: Key 2025 Milestones (Company Milestones)
This chapter compiles the technical breakthroughs, strategic pivots and product launches completed by key players in 2025. These are not just headlines — they are the foundations defining the 2026 competitive landscape.
4.1 AI System Architects
4.2 Connectivity & Custom Silicon
Broadcom: The "Arsenal" of the Non-NVIDIA Camp
Broadcom's $73 billion AI backlog represents not demand hype, but system-level dependency.
Marvell: The Disruptor in Optical Interconnect
In 2025, Marvell clearly bet its future on "in-package optical interconnect."
4.3 Interconnect Specialists
Astera Labs: The Signal Guardian of the AI Rack
Astera Labs' value lies in controlling the parts of the AI rack most prone to failure.
Credo: The Last Line of Defense for Copper
Credo proves that under physical limits, precise positioning matters more than chasing bandwidth.
4.4 Optics & Manufacturing
Lumentum: Capacity Is Firepower
Chapter 5 | 2026 Outlook
From "Building" to "Operating": The AI Factory's First-Year Stress Test
5.1 The First Year of 1.6T — More Than a Bandwidth Upgrade
5.2 Scale-Up Optics Formally Enters Package Design Discussions
5.3 The Spread of OCS Will Redefine the "Network"
5.4 448G Electrical Interfaces: The Engineer's Real Nightmare
Chapter Summary | The Real Litmus Test of 2026
2026 will no longer reward "the most aggressive architecture," but "the system that runs most reliably over time."
This year, the market will clearly distinguish for the first time:
Which architectures can merely "run a demo"
Which architectures can actually run for one, three, or five years
And this will directly determine the redistribution of capital, orders and supply-chain bargaining power.
How to Read This Report
This is not an article for a quick skim.
It is a system-level analysis report, designed not for you to "finish," but to use repeatedly in different situations.
To help you grasp the key points quickly and return to the core judgments when needed, we suggest reading it as follows.
1. If you only have 10 minutes
👉 Build the overall decision framework
Read these three parts first:
Executive Takeaway (summary)
→ This condenses the report's core conclusions and reasoning.
The strategic summary at the end of Chapter 3
→ Helps you understand who is taking control of the AI factory's system entry points.
The one-line conclusion under each company heading in Chapter 4
→ Even without the details, you can quickly scan the winners and positions validated in 2025.
After this, you should be able to answer three questions:
What is the real bottleneck of AI infrastructure
Which technology routes have already moved beyond the slide deck
Who is in the right position ahead of 2026
2. If you care about technology and architecture
👉 Understand industry change through engineering reality
Focus on:
Chapter 1 | The Architecture Revolution
→ Understand why the server is no longer the unit of compute — the rack is.
Chapter 2 | The Optical Explosion
→ Clarify the differences between the scale-up / scale-out / scale-across battlefields, and the physical limits of optics and copper.
When reading these two chapters, pay special attention to the recurring keywords:
latency, power, reach, stability, serviceability
These are precisely the real design constraints of the next few years.
3. If you care about company strategy and competitive position
👉 Look at companies by system entry points, not product lines
Focus on:
Chapter 3 | The Giants' Chess Game
→ This chapter does not compare product performance; it compares "who controls the system's critical nodes."
Chapter 4 | Key 2025 Milestones
→ Lists only facts that "have already happened and are irreversible," to help you separate strategy from track record.
4. If you care about 2026 and investment decisions
👉 Look for structural, not cyclical, opportunities
Read in full:
Chapter 5 | 2026 Outlook
This chapter is not about forecasting market size; it answers:
Which technical pressures will be amplified in 2026
Which bottlenecks will be the first to turn into orders
Which supply-chain roles will create alpha beyond the GPU
Reading Chapter 5 alongside Chapter 4 works best.
5. How to use this report repeatedly
This report is suited to the following situations:
Evaluating next-generation AI architectures or product directions
Understanding the real meaning behind optical / interconnect news
As background material for investment, strategy meetings and internal briefings
When market narratives diverge, coming back to check "what has been validated by engineering"
If over the next year you find yourself reading this more than once, it has done its job.
A final note
This is not a report that asks you to agree with every view; it is a method to help you build your own judgment.
If this report helps you, when facing the next piece of AI infrastructure news,
tell "noise" from "structural signal" faster,
then its value has already been realized.
Comments