Research Uses AI to Raise Data Center Utilization

According to AI TIMES, a research team led by MIT Professor Christina Delitrou is working on using AI to optimize the allocation of server and network resources in data centers, extracting more computing performance from existing hardware. The research, introduced on October 8, targets the problem of low utilization, where large-scale systems operate at only about 15% of capacity. Its core approach is to reduce power strain and environmental impact at the same time by redesigning software and resource management methods instead of continuously adding new infrastructure. The team is also using machine learning to analyze workload characteristics and system conditions, automate resource allocation, and prepare responses by identifying possible performance degradation or bottlenecks in advance. In addition, it is using AI to rework systems to fit the changed structure of cloud applications, while expanding the scope of its research to include security and explainability. By also building a verification system to narrow the gap with real commercial environments, the research shows that data center competitiveness is shifting from simply adding equipment to how much operational efficiency can be improved.