SoftBank to open battery production for AI data centers at Sharp plant

SoftBank is launching battery production for energy-intensive AI data centers at a former Sharp plant in Osaka. The target is 1 gigawatt-hour of batteries annually. Korean companies Cosmos Lab and DeltaX are involved in the project. The first batteries will begin production in April 2025, with zinc-halogen technology due in 2027.

AI-processed from TNW; edited by Hamidun News
SoftBank to open battery production for AI data centers at Sharp plant
Source: TNW. Collage: Hamidun News.
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Article Fact Sheet & Key Figures
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Primary sourceTNW ↗
Editor-in-Chief
Key metric #1Cosmos Lab from South Korea — battery system development
Key metric #2DeltaX — battery integration into complex networks
Key metric #3SoftBank — manufacturing base and financing

SoftBank has announced the launch of its own battery production for AI data centers at the former Sharp site in Osaka. The Japanese company views batteries as a strategic asset in the era of energy-intensive artificial intelligence.

New Life for Sharp's Factory

The factory in Sakai, Osaka, once produced electronic components for Sharp. Now it is being retooled for battery manufacturing. SoftBank has set an ambitious production target: 1 gigawatt-hour of batteries per year. This means the factory could power a small data center for a full day of operation. The production line is scheduled to launch in April 2025. The company has already planned for expansion: in 2027, battery production based on zinc-halogen chemistry will be added, which promises better characteristics in terms of energy density and cost.

International Partnership

SoftBank did not pursue this alone. The project has brought in two companies with deep expertise:

  • Cosmos Lab from South Korea — battery system development
  • DeltaX — battery integration into complex networks
  • SoftBank — manufacturing base and financing

This partnership allows each party to focus on their core competence and accelerate the time-to-market for a competitive product.

Energy for AI Becomes Critical

Data centers training large language models consume megawatts of electricity. A single training run of a GPT-scale model can consume as much electricity as a city does in a month. Batteries are needed for several purposes:

  • Peak load smoothing — during peaks, batteries are used instead of requesting power from the grid
  • Backup power — in case of failure of the primary power source
  • Reducing electricity bills — batteries reduce peak demand

SoftBank, as a cloud services owner and investor in AI companies, understands this need from the inside. Owning its own battery production will give it a competitive advantage and a new revenue stream.

What This Means

Batteries for data centers are transitioning from niche equipment to strategic infrastructure. SoftBank's investment signals that this is a market with potential in the tens of billions of dollars. Expect other major cloud providers to begin investing in their own battery production.

Key Questions Answered

What are the key details on New Life for Sharp's Factory?

The factory in Sakai, Osaka, once produced electronic components for Sharp. Now it is being retooled for battery manufacturing. SoftBank has set an ambitious production target: 1 gigawatt-hour of batteries per year. This means the factory could power a small data center for a full day of operation. The production line is scheduled to launch in April 2025. The company has already planned for expansion: in 2027, battery production based on zinc-halogen chemistry will be added, which promises better characteristics in terms of energy density and cost.

What are the key details on International Partnership?

SoftBank did not pursue this alone. The project has brought in two companies with deep expertise: Cosmos Lab from South Korea — battery system development DeltaX — battery integration into complex networks SoftBank — manufacturing base and financing This partnership allows each party to focus on their core competence and accelerate the time-to-market for a competitive product.

What are the key details on Energy for AI Becomes Critical?

Data centers training large language models consume megawatts of electricity. A single training run of a GPT-scale model can consume as much electricity as a city does in a month. Batteries are needed for several purposes: Peak load smoothing — during peaks, batteries are used instead of requesting power from the grid Backup power — in case of failure of the primary power source Reducing electricity bills — batteries reduce peak demand SoftBank, as a cloud services owner and investor in AI companies, understands this need from the inside. Owning its own battery production w

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Zhemal Khamidun — CPO at Alpina Digital, product manager of AlpinaGPT. Building AI products since 2019. Hamidun News is a pet project that grew into a production aggregator with 6,000+ readers.
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