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Compute systems

Nvidia pitches repurposing Brightspeed sites for AI compute capacity

Nvidia seeks to convert over 130 telecom buildings into data centers, aiming for 1 gigawatt of capacity to bypass construction delays.

Key points

  • Nvidia pitched converting Brightspeed facilities to Apollo Global Management executives.
  • The plan could yield 1 gigawatt of capacity across 130 U.S. sites.
  • These sites could house over 2,200 Supermicro NVL72 racks.
Nvidia pitches repurposing Brightspeed sites for AI compute capacity
Depth
1 outlet · newest source 1h ago

Nvidia is reportedly in talks to convert telecommunications infrastructure into artificial intelligence data centers. The company pitched the concept to Apollo Global Management, the parent firm of Brightspeed, according to Tom's Hardware citing The Information.Nvidia wants to turn old telephone company buildings into data centers for AI.Nvidia proposes leveraging Brightspeed's 130 facilities for 1GW capacity to mitigate greenfield data center delays.

Evidence: reportedNvidia wants to repurpose over 130 old telco buildings as tiny data centers, report claims

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What was released or claimed

Apollo Global Management asked Nvidia to submit written plans to the internet provider. Nvidia complied with this request and has now asked for additional information and site visits. The proposal involves repurposing existing buildings rather than constructing new facilities from scratch.

Who it affects

Brightspeed, the internet and telecommunications provider, is the primary entity involved. Apollo Global Management, its parent company, is also central to the decision-making process. The plan could impact local governments that issue permits for these sites.

What is still unknown

It remains unclear who will own the AI chips installed in these facilities. The final agreement on terms and ownership between Nvidia, Apollo, and Brightspeed has not been disclosed. Specific timelines for implementation are also not provided in the reports.reported

What to make of it

This strategy addresses delays and community opposition associated with building large data centers. Repurposing existing telecom buildings may face less regulatory red tape. It offers a faster path to deploying compute capacity compared to traditional construction methods.

What buyers should weigh

Buyers should consider the speed of deployment offered by repurposed infrastructure. Market position may shift as vendors seek alternative site options. Vendor choice could expand to include telecom assets for AI workloads. Cost structures may differ from traditional data center builds.

Why it matters

  • Repurposing existing infrastructure could accelerate AI deployment timelines significantly.
  • Telecom assets offer an alternative to facing community backlash against new builds.
  • Apollo's existing GPU orders highlight the urgency of finding rack space.
  • The model may influence how other vendors approach data center expansion.

Topics: Nvidia, Brightspeed, Apollo Global Management, data centers, AI infrastructure

Updated

The strongest doubt

Counterpoint from the sources

The sites require new cooling systems and permits, meaning they are not plug-and-play solutions despite existing power infrastructure.

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Questions readers ask

How many buildings are involved in this plan?

The plan involves approximately 130 Brightspeed buildings located across the United States.

What is the estimated compute capacity?

Nvidia estimates the sites could collectively deliver around 1 gigawatt of compute capacity.

Can the sites run the servers immediately?

No, Nvidia would still need to install cooling systems and other supporting architecture.

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Reading receipt

  • Nvidia pitched converting Brightspeed facilities to Apollo Global Management executives.
  • The plan could yield 1 gigawatt of capacity across 130 U.S. sites.
  • These sites could house over 2,200 Supermicro NVL72 racks.

Still open: Who will ultimately own the installed Nvidia chips?

Still open: Will this model be adopted by other telecom providers?

Time spent: 0:00 · Depth: Full

Sources

  1. Tom's Hardware

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