---
格式版本: 2
标题: "Big Fiber’s $250M Signals an AI Dark-Fiber Land Rush"
原文链接: "https://www.datacenterknowledge.com/infrastructure/big-fiber-financing-signals-ai-s-next-infrastructure-land-rush"
发布日期: "2026-08-11"
发布时间校准状态: "found"
发布时间需复核: "否"
发布时间来源: "llm:local:strict_original_body"
发布时间证据: "Aug 11, 2026"
发布时间校准原因: "多个原标题附近候选日期中，Aug 11, 2026 为最晚且明确标注于正文，符合发布规律。"
发布时间校准置信度: "1"
发布时间候选数量: 48
发布时间严格候选数量: 4
发布时间原页读取状态: "source template page reused from URL open"
发布时间未找到原因: ""
发布时间校准时间: "2026-08-12T03:57:33+08:00"
发布时间仲裁状态: "confirmed"
发布时间仲裁尝试次数: 2
发布时间仲裁耗时毫秒: 94360
发现时间: "2026-08-12T03:53:36+08:00"
入库时间: "2026-08-11T19:59:08.390Z"
来源平台: "Data Center Knowledge 搜索"
搜索渠道: "source_template"
搜索词: "https://www.datacenterknowledge.com/search?q=latency"
匹配关键词:
  - "latency"
  - "AI"
  - "GPU"
  - "Scale-up"
  - "Liquid Cooling"
  - "deployment"
  - "bandwidth"
相关厂家:
  - "NVIDIA"
  - "AWS"
  - "Google"
相关专家:
  []
内容类型: "网页"
抓取工具: "Jina Reader"
清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取"
原始附件:
  []
AI优质: "否"
AI打分: 35
AI分档: "非优质"
AI质检状态: "不通过"
AI打分理由: "讨论AI数据中心暗光纤投资，未涉及超节点/AI Rack/机柜级系统、核心部件、供电、散热、高速互连等任何项目核心主题，属于泛泛行业新闻。"
AI质检模型: "ali-deepseek-v4-flash"
AI质检时间: "2026-08-12T03:59:15+08:00"
AI主题相关性: 5
AI来源权威性: 12
AI新颖性: 5
AI技术细节: 0
AI商业部署信号: 8
AI完整性: 5
采集批次: "2026年8月12日2点04分20秒"
采集批次ID: "20260812-020420-289"
去重键: "https://www.datacenterknowledge.com/infrastructure/big-fiber-financing-signals-ai-s-next-infrastructure-land-rush"
---

Title: Big Fiber’s $250M Signals an AI Dark-Fiber Land Rush

URL Source: https://www.datacenterknowledge.com/infrastructure/big-fiber-financing-signals-ai-s-next-infrastructure-land-rush

Published Time: 2026-05-19T08:00:00.000Z

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# Big Fiber’s $250M Signals an AI Dark-Fiber Land Rush

Financing will add dark fiber routes and capacity as hyperscalers build distributed AI campuses in power-rich regions.

[![Image 17: Picture of Shane Snider](https://eu-images.contentstack.com/v3/assets/blt8eb3cdfc1fce5194/blt68d42dde3032e1e9/67212dce29bb88408c6ac9be/Shane_Snider_Profile.webp?width=100&auto=webp&quality=80&disable=upscale)](https://www.datacenterknowledge.com/author/shane-snider)

[Shane Snider,](https://www.datacenterknowledge.com/author/shane-snider)Senior News Writer,Data Center Knowledge
May 19, 2026

3 Min Read

![Image 18: networking cord with a glowing tip inside a data center](https://eu-images.contentstack.com/v3/assets/blt8eb3cdfc1fce5194/blt350cc08e129ac2c0/6a0c9423d32eb0a817ab65eb/2J2HJ1T.jpg?width=1280&auto=webp&quality=80&disable=upscale)

Alamy

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Private capital is moving deeper into the physical network layer underpinning the AI buildout. Big Fiber has secured $250 million in financing from Stonepeak and Caisse de dépôt et placement du Québec (CDPQ) to expand its dark fiber footprint and network capacity as hyperscalers and large-scale data center operators push into new AI markets.

BIG Fiber Chief Commercial Officer Patton Lochridge told Data Center Knowledge that the company is seeing strong AI-related demand in the San Francisco Bay Area, Hillsboro, and Atlanta, where it is building new routes tied to AI and data center expansion. “We’re seeing customers require extreme route diversity, often moving toward tri-versity or quad-versity networks to connect metro assets and long-haul routes,” Lochridge said.

He added that inference workloads are increasing the demand for dense metro connectivity: “Traditional telecommunications networks are often too congested or lack the latency and loss tolerances required for stringent AI workloads, making purpose-built metro fiber essential.”

Related:[Networking Strains Under AI’s Scale Demands](https://www.datacenterknowledge.com/networking/the-breaking-points-networking-strains-under-ai-s-scale-demands)

Sterling Perrin, senior principal analyst for optical networks and transport at Omdia, told Data Center Knowledge that new AI campuses are spreading beyond traditional connectivity hubs such as Ashburn, Dallas, and Northern California into power-rich regions, including West Texas, Ohio, Tennessee, Louisiana, and Georgia. “They all require massive fiber optic connectivity,” Perrin said.

Power constraints are also reshaping network design. Ron Westfall, vice president and analyst at HyperFrame Research, said that grid limitations are pushing hyperscalers toward distributed regional AI campuses connected via metro and long-haul dark fiber. “Power grid constraints have forced a material shift toward metro and long-haul dark fiber infrastructure to stitch together distributed regional data center campuses,” Westfall said. “Because this relentless GPU-to-GPU communication demands near-zero latency and unprecedented bandwidth, infrastructure planners are prioritizing the deployment of ultra-high-strand dark fiber corridors that directly link distributed, power-rich data centers.”

## AI Traffic Begins to Reshape Fiber Demand

The surge in demand is already hitting the optical supply chain. In an April market analysis following OFC 2026, CRU Group said AI-driven data center demand “has overtaken traditional telecom as the primary growth engine for optical [fiber] and cable,” tightening supply for high-density fiber products and upstream preforms.

Related:[Hollow-Core Fiber: Faster, Greener, but Is It Worth the Cost?](https://www.datacenterknowledge.com/networking/hollow-core-fiber-faster-greener-but-is-it-worth-the-cost-)

Most AI traffic still remains inside the data center – Omdia estimates suggest as much as 90% of AI traffic never leaves the facility during GPU cluster operations – but larger [distributed AI environments](https://www.datacenterknowledge.com/infrastructure/equinix-unveils-distributed-ai-infrastructure-to-link-data-centers) are beginning to increase pressure on interconnect infrastructure.

Speaking at the Optica Executive Forum, Cisco SVP and Fellow Rakesh Chopra said AI “scale-up” traffic inside data centers can generate 504 times more traffic than traditional data center interconnect (DCI) flows, while “scale-out” traffic can produce 56 times DCI bandwidth requirements, according to Perrin.

“With AI training models at the limits of what can be processed within a data center, distributed AI clusters are inevitable,” Perrin said.

Nvidia’s AI factory architectures reflect this shift by separating east-west GPU compute traffic from traditional north-south enterprise flows, using low-latency leaf-spine topologies designed for continuous GPU communication.

Westfall noted that those traffic patterns are forcing operators to redesign networks around persistent machine-to-machine synchronization rather than traditional enterprise traffic.

## Fiber Joins the AI Infrastructure Stack

The financing for Big Fiber aligns with broader AI-driven infrastructure investment trends. Utilities are expanding transmission, power developers are pursuing generation near AI hubs, and infrastructure funds are assembling portfolios spanning energy, land, connectivity, and digital infrastructure.

Related:[AWS Networking Boss on Hollow-Core Fiber, AI, and Data Center Innovations](https://www.datacenterknowledge.com/networking/aws-networking-boss-on-hollow-core-fiber-ai-and-data-center-innovations)

Westfall said infrastructure investors increasingly value fiber routes based on proximity to power-rich AI markets rather than traditional telecom demand metrics.

“Infrastructure monetization is shifting away from historical metrics such as per-megabit pricing toward asset-level valuations built around proximity to power-rich data centers,” Westfall said.

Lochridge said most of the new financing will support greenfield construction and overbuilds of “exhausted legacy telecommunications corridors that need more scale.”

If realized, the result will be a growing web of high-capacity fiber routes linking new AI campuses in power-rich regions back into hyperscale cloud and interconnection networks.

Editor's note: Omdia is a part of Informa, the parent company of Data Center Knowledge.

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## About the Author

[![Image 19: Shane Snider](https://eu-images.contentstack.com/v3/assets/blt8eb3cdfc1fce5194/blt68d42dde3032e1e9/67212dce29bb88408c6ac9be/Shane_Snider_Profile.webp?width=400&auto=webp&quality=80&disable=upscale)](https://www.datacenterknowledge.com/author/shane-snider)

[Shane Snider](https://www.datacenterknowledge.com/author/shane-snider)

Senior News Writer, Data Center Knowledge

Shane Snider is Senior News Writer at Data Center Knowledge, covering AI infrastructure, hyperscale data centers, cloud platforms, and the power and energy systems driving modern compute expansion. His reporting focuses on the operational, economic, and environmental forces reshaping digital infrastructure, including AI factories, utility constraints, liquid cooling, renewable energy procurement, and next-generation data center architectures. He has won recent Azbee awards for news series and government reporting. Based in Raleigh, North Carolina, Snider covers how hyperscalers, utilities, chipmakers, and infrastructure providers are responding to the rapid rise of AI workloads and global compute demand.

You can reach Shane at [shane.snider@informatechtarget.com](mailto:shane.snider@informatechtarget.com) or on [LinkedIn](https://www.linkedin.com/in/shane-snider-1727755/).

[See more from Shane Snider](https://www.datacenterknowledge.com/author/shane-snider)

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