LLMOPS & AI INFRASTRUCTURE • 275 / 397
Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.
Batching
Batching processes multiple requests or examples together to use hardware more efficiently.
Think of it like
Think of Batching 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 Batching to keep cost and latency under control.
SRE lens
Higher batch sizes can improve throughput but increase waiting time and memory usage.
Remember thisBatching processes multiple requests or examples together to use hardware more efficiently.