Rick Larson, PhD - When discussing artificial intelligence (AI), many immediately think of Graphics Processing Units (GPUs) as the critical hardware driving this technology. However, while GPUs play a pivotal role in AI workloads, it’s important to recognize that the infrastructure supporting AI extends far beyond just GPUs. The performance and scalability of AI applications also hinge on factors like data center architecture, which has become increasingly specialized to meet the demands of modern AI. Management and Automation (AI for AI) One of the most exciting developments is the use of AI to manage AI workloads. AI-driven automation tools can optimize data center operations by monitoring system performance, predicting maintenance needs, and dynamically managing resources based on the changing demands of AI tasks
