Multitask describes a model, system, or training setup designed to handle multiple tasks rather than a single narrowly defined objective. In machine learning, multitask approaches often share representations so learning on one task can support performance on others.
A machine learning technique in which a single model is trained to perform multiple tasks. Multitask models are created by training on data that is appropriate for each of the different tasks. This allows the model to learn to share information across the tasks, which helps the model learn more effectively. A model trained for multiple tasks often has improved generalization abilities and can be more robust at handling different types of data.