- Applied Digital (APLD, Financial) reveals a potential $2.7 billion in savings over 30 years through strategic site selection and data center design.
- The company secures a significant 15-year, $7 billion lease with CoreWeave for 250MW deployment at their Polaris Forge data center in North Dakota.
- Polaris Forge 01 offers superior efficiency with a projected PUE of 1.18 and near-zero WUE due to innovative cooling systems and favorable climate.
Applied Digital (APLD) has released a white paper showcasing how strategic site selection and innovative data center design can significantly reduce the costs associated with AI infrastructure. The report highlights potential savings of up to $2.7 billion over 30 years, particularly with the introduction of their Polaris Forge data center in North Dakota.
The new data center region is poised to save $50-60 million annually per 100MW campus when compared to traditional locations. These savings stem from North Dakota's unique advantages, such as access to gigawatt-scale stranded power and over 220 days of free cooling annually.
Polaris Forge 01, designed with cutting-edge technology, features a closed-loop, waterless, direct-to-chip cooling system that achieves a projected Power Usage Effectiveness (PUE) of 1.18 and near-zero Water Usage Effectiveness (WUE), marking it as one of the most efficient facilities globally.
Demonstrating market confidence in their AI-optimized infrastructure, Applied Digital has secured a 15-year lease agreement with CoreWeave valued at $7 billion for a 250MW deployment. This deal not only underscores the financial viability of their strategy but also positions the company as a leader in sustainable, AI-focused data center development.
Applied Digital’s choice of North Dakota is driven by the region's cooling efficiency and power availability, which contribute to lower operational costs and enhanced sustainability for AI infrastructures. Their data center model supports a 400 MW critical IT load, with over 1 gigawatt in load study capacity, setting a new standard for AI data center efficiency and scalability.
