LLMOPS & AI INFRASTRUCTURE • 265 / 397
Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.
GPU
A GPU is a highly parallel processor well suited to large matrix operations used by neural networks.
Think of it like
Think of GPU like familiar infrastructure capacity and traffic engineering, except the scarce resources are often tokens, GPU memory and model latency.
Real life
High-scale AI services depend on GPU to keep cost and latency under control.
SRE lens
Large-model inference capacity is often constrained by GPU memory and compute.
Remember thisA GPU is a highly parallel processor well suited to large matrix operations used by neural networks.