LLMOPS & AI INFRASTRUCTURE • 303 / 397
Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.
Cache
A cache stores reusable results or intermediate data to avoid repeated computation.
Think of it like
Think of Cache 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 Cache to keep cost and latency under control.
SRE lens
Caching can reduce model calls, latency and spend.
Remember thisA cache stores reusable results or intermediate data to avoid repeated computation.