Artificial intelligence compute capacity combines the quantity and capability of processors with memory, networking, power, cooling, software, and usable operating time. Capacity is meaningful only when the system can schedule workloads and keep the hardware productively utilized.
Organizations obtain capacity by owning infrastructure, renting cloud services, or signing longer-term contracts. Effective capacity can change as new chips improve performance, models become more efficient, power becomes constrained, or demand shifts between training and inference.
