WHAT IS INSIDE AI INFRASTRUCTURE?
AI infrastructure is not one server, but several layers, each critical.
The compute layer — GPUs and specialized accelerators (TPU, NPU, tensor chips). They do the main work: matrix operations on which AI is built.
Memory — video memory (VRAM), RAM, storage. The model must be loaded, data must be instantly accessible. Memory often becomes a bottleneck faster than the processor itself.
Network — internal channels between chips and external channels between nodes. Throughput determines how quickly tasks are distributed and results returned.
Energy — power supply. Data centers consume megawatts. Power stability is a condition for continuous operation.
Cooling — air or liquid. Thousands of chips at their limit generate heat, and without heat removal they will burn out or lose performance.
The management layer — software that distributes tasks, balances load, monitors node status.
All these layers work together. Weak in any of them — weak in the whole system.
September 26, 2026 66
