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The data center’s role in delivering sustainable AI


At the intersection of artificial intelligence (AI) and sustainability, data centers serve as the backbone for hosting and processing AI workloads. These facilities are tasked with handling the immense computational demands of AI algorithms and applications, which often require vast amounts of energy. As a result, AI data centers have emerged as focal points for addressing AI’s environmental footprint and promoting sustainable practices within the industry. 

One of the primary challenges associated with data centers is their substantial energy consumption. AI workloads, particularly those involving deep learning and training large neural networks, demand significant computational power, leading to heightened energy requirements. These requirements have made headlines around the world as governments begin to realise the impact AI’s energy consumption will have on local power grids.  

There is also growing concern about carbon emissions and environmental degradation. To combat the environmental impact of AI workloads in the data center, industry leaders are increasingly implementing strategies to enhance energy efficiency and reduce carbon emissions. These efforts encompass various initiatives, ranging from optimizing hardware utilization to adopting renewable energy sources. 

Optimizing hardware utilization involves maximizing the efficiency of computing resources within AI data centers. Through techniques such as workload consolidation, resource scheduling, and hardware acceleration, data center operators can minimize energy wastage and improve overall efficiency. By streamlining computational processes, AI data centers can achieve higher performance levels while consuming fewer resources, thereby reducing their environmental footprint. 

Another key aspect of promoting sustainability in AI data centers is the adoption of renewable energy sources. By transitioning to clean energy sources such as solar, wind, and hydroelectric power, data centers can significantly reduce their carbon emissions and reliance on fossil fuels. The Nordics, with their abundant renewable energy resources, have become attractive locations for AI workloads due to their commitment to sustainability and environmental responsibility. 

The next wave of innovation will focus on cooling technologies. Traditional air-cooled systems account for up to 40% of a data center’s energy consumption. While the Nordics have easily been able to harness free cooling to improve energy efficiency and reduce environmental impact, rising rack densities will require even more cooling capability. Liquid cooling will enable data center operators to cool up to 200kW per rack to accommodate the most advanced AI workloads in the future. With this surge in AI, machine learning and high-performance computing amplifying the need for robust data center cooling solutions, Verne is already enabling the potential of liquid cooling technologies at our Pori data center campus in Finland.  

As organizations continue to navigate the complexities of AI sustainability and carbon footprint reduction, Verne is here to help. Sustainability and efficiency have been at the heart of Verne’s mission since we first opened our doors more than a decade ago. We deliver sustainable data center solutions from our 100% renewably powered data center campuses in Iceland and Finland. With multiple sites delivering unmatched specialised data center services for AI workloads, we’re helping organisations – like Hugging Face, Peptone, and Wirth Research – cost-effectively scale their digital infrastructure while reducing their environmental impact. 

Contact us today to learn more about how we can help you with your AI data center needs.