Rack-scale networking is becoming essential for massive AI workloads, offering significantly higher bandwidth compared to traditional scale-out networks like Ethernet and InfiniBand. Companies like Nvidia and AMD are leading the charge with advanced architectures that facilitate pooling of GPU compute and memory across multiple servers, catering to the demands of large enterprises and cloud providers. These systems, while complex and expensive, are designed to handle increasingly large AI models and their memory requirements.