Inference & Serving is the AI lane for runtime delivery, scaling, latency, and efficient operation of models in production.
Use this category for:
- model serving stacks, inference runtimes, and deployment efficiency
- latency, throughput, batching, caching, and scaling behavior
- operating model inference in production systems
Good topics here:
- serving-architecture choices and tradeoffs
- runtime optimization and inference cost control
- scaling model inference under real demand
If your topic is broader than this subcategory, use AI instead.