scalable AI infrastructure

https://mag-wiki.win/index.php/Why_Smart_Teams_Choose_AI_without_Vendor_Lock-In

Scalable AI infrastructure means designing data pipelines, compute clusters, and model serving systems that can grow seamlessly as workloads increase. It involves balancing cost with performance, often using cloud-native tools like Kubernetes and distributed storage. The goal is to avoid bottlenecks when training larger models or handling more inference requests, so teams can iterate faster without rebuilding everything from scratch.