Data centres must up their energy game with the rise of AI
October 25, 2023
Verne Global CEO Dominic Ward speaks about the increased demand for data, the energy impact of generative AI and the importance of choosing the right location for data centres.
It’s no secret that data centres are becoming a bigger strain on energy grids as the world becomes more digitalised.
Their impact has become clear in Ireland, with 18pc of the country’s metered electricity being consumed by data centres last year, according to figures from the Central Statistics Office. The same amount of electricity was consumed by all urban dwellings in Ireland.
Despite the strain on the grid, the desire for more data centres has not gone away. Just last month, Amazon Web Services received approval to build three new data centres in Dublin, despite opposition from environmental groups.
There are clear benefits from data centres, with their ability to store vast amounts of easily-accessible data being vital for various sectors – including research. They are also highly valuable for AI, a technology that has grown significantly in recent years.
Dominic Ward, the CEO of data centre provider Verne Global, told SiliconRepublic.com that power needs in Europe have grown increasingly stretched and that this has been driven “in no small part by the growing demand for AI”.
“Dell’Oro Group predicts that global data centre capital expenditure is set to rise above $500bn by 2027 due to AI infrastructure demand,” Ward said. “The growing demand for AI, alongside the worsening climate crisis, has led to a need for data centres that are specifically designed to handle the heavy compute required by all types of AI.
“At the same time, there’s an imperative to prioritise energy efficiency so that valuable power is not wasted, and the impact on the environment is kept to a minimum.”
When speaking about the impact AI is having on the demand for data centres, Ward said there’s an important difference between traditional AI and generative AI. The latter is the one that has gained rapid attention over the past year, with the rise of certain systems like ChatGPT and a heavier focus by big tech companies.
“Generative AI is more complex and therefore requires more computing power,” Ward said. “As an example, researchers in 2019 found that creating the generative AI model BERT consumed energy equivalent to a round-trip transcontinental flight taken by one person.”
The energy requirements for these systems has grown exponentially as they have become more complex. While Google’s BERT had roughly 345m parameters, OpenAI’s ChatGPT has 1.5bn. The company also claims that its latest large language model, GPT-4, has more than 1.75trn parameters.
“Most of the major generative AI models are generated by hyperscale cloud providers with thousands of servers,” Ward said. “These models run on graphics processing unit (GPU) chips that...
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