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zero-shot learning

A type of machine learning training where the model infers a prediction for a task that it was not specifically already trained on.

A type of machine learning training where the model infers a prediction for a task that it was not specifically already trained on. In other words, the model is given zero task-specific training examples but asked to do inference for that task.

Practitioners refer to zero-shot learning when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.