Inference
In one sentence
Running a trained model to produce an output — as opposed to training it.
In more depth
During inference the weights are fixed. Input flows through the network once and an output comes out; nothing is learned and nothing is stored in the model.
This is why a model does not remember your last conversation unless the product around it saves that text and supplies it again.