The rapid expansion of generative AI models require more powerful hardware and with the rise of datacenters with hundreds of thousands of AI GPUs, they are quickly pushing the limits of current datacenter infrastructure and soon they could hit the limit of power grid. While AWS, Microsoft, and Oracle plan to use nuclear power plants to power their datacenters, Microsoft Azure's chief technology officer, Mark Russinovich, suggests that connecting multiple datacenters may soon be necessary to train advanced AI models, reports Semafor.
Modern AI datacenters, such as those built by Elon Musk's companies Tesla or xAI, can house 100,000 of Nvidia H100 or H200 GPUs and as American giants are competing to train the industry's best AI models, they are going to need even more AI processors that work in concert as a unified system. As a consequence, datacenters are becoming even more power hungry both due to the increased number of processors, higher power consumption of these processors, and the amount of power that is required for their cooling. As a result, datacenters consuming multiple gigawatts of power could soon become real. But the U.S. energy grid is already under strain, especially during periods of high demand, such as in hot summer days, there are concerns that the grid may not be able to keep up with the demand.
