Transfer learning
Also: Transferlernen
An already trained model is used as the starting point for a new, related task.
Instead of training a model from scratch, you take the knowledge of a large, generally pre-trained model and adapt it to your own task with comparatively little data.
This saves time, data and computing costs. Fine-tuning language and image models is the most important form of transfer learning today.
General information, not legal or professional advice.