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OpenAI-Linked Data Center in Australia Scraps Water Recycling Plan, Opts for Energy-Intensive Cooling

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Jul 23, 20261 min read
OpenAI-Linked Data Center in Australia Scraps Water Recycling Plan, Opts for Energy-Intensive Cooling
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Background

Developers of a large-scale data center in Australia intended for use by OpenAI have reversed plans to cool the facility with recycled water, shifting to a more energy-intensive method, Reuters reported on Thursday. The change highlights the logistical and regulatory challenges facing the development of power-hungry artificial intelligence infrastructure.

Change in Cooling Strategy

OpenAI's Australian partner, NEXTDC, confirmed to Reuters that it had ended discussions with utilities for the project. The decision was made after the company was unable to obtain the necessary planning permission for a pipeline that would have transported recycled water to the data center site.

The original plan for the 612-megawatt S7 facility, outlined in planning documents from April, involved using treated sewage from Sydney to cool its servers. This approach was designed to conserve drinking water and minimize the facility's strain on the local energy grid.

Implications and New Approach

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With the water recycling plan now off the table, NEXTDC will implement a different cooling system. The company told Reuters it will use a process that circulates liquid coolant directly around the server chips to dissipate heat.

While this direct liquid cooling method consumes no water, it is more energy-intensive than the originally proposed system. This presents a trade-off, shifting the environmental impact from water resources to energy consumption—a critical consideration for investors and operators focused on the sustainability of AI operations.

Context: AI's Growing Resource Demands

The S7 facility is set to be one of the largest data centers in the world, underscoring the massive computational resources required to power advanced AI models. The pivot in its cooling strategy illustrates a key operational hurdle for the rapidly expanding AI industry, which faces increasing scrutiny over its substantial energy and water consumption.

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