Autoscaling

A system that automatically adjusts computing resources based on workload demand to maintain performance, availability, and efficient resource utilization.

The practice of reducing response latency in AI systems to improve responsiveness, throughput, and user experience.

The process of improving an AI system's speed, resource efficiency, throughput, or responsiveness by adjusting its implementation and runtime configuration.

The process of running model inference on multiple inputs together to improve throughput, resource utilization, and overall serving efficiency.

The practice of deploying AI models or applications on graphics processing units (GPUs) to accelerate inference or training by leveraging massively parallel computation for high-performance workloads.