Inference

Inference is the stage when a trained AI model uses new input to produce a prediction, classification, recommendation, or generated response. Training may take days across specialized hardware, while inference happens whenever a user submits a prompt, a camera captures an image, or an application requests a score. Production systems optimize inference for latency, throughput, memory use, energy consumption, and cost without degrading output quality. The model may run in a cloud service, data center, phone, vehicle, or edge device. Monitoring remains necessary because real-world inputs change, hardware can fail, and a model that performed well during evaluation may behave differently under live traffic.