AI computing demand is growing exponentially, outpacing Moore’s Law, while power consumption and cost pressures escalate, shifting the core metric from individual chip performance to rack-level performance per watt and performance per total cost of ownership. Semiconductor players must evolve from chip suppliers into providers of rack and system-level solutions. At its March 2026 GTC, NVIDIA unveiled seven new Rubin-series chips and five MGX-series racks that integrate these chips into a single rack, with racks interconnectable via switches to form a Vera Rubin POD. NVIDIA has secured talent and technology licenses from Enfabrica and Groq, and invested in quantum computing and optical-communication suppliers. CSPs are designing proprietary AI racks and PODs; Google adopted its ICI scale-up technology in 2017, introduced OCS in 2021, and plans to deploy its Axion CPU and Boardfly network architecture in the TPU v8 series in 2026. AWS plans to deploy its NeuronLink and Graviton CPUs in the 2026 Trainium3 UltraServer.