Transfer learning across domains primarily belongs to the fields of Artificial Intelligence and Digital Transformation. The term describes a method where knowledge learned by Artificial Intelligence in one specific area (domain) is successfully applied to another.
Imagine a computer program that has learned to recognise animals from many photos. Now it is to identify plants. Using transfer learning across domains, the program uses the knowledge it has already acquired about shapes and colours from the animal domain to recognise plants more quickly and with fewer new examples.
For businesses, this means that instead of starting from scratch for every new problem, existing knowledge can be used by AI to speed up solutions and save costs. In practice, this could be used in the area of Industry 4.0, for example – such as when a machine has first been trained for the quality control of car parts and can then be used to inspect other products without much effort.
This is how transfer learning across domains ensures that artificial intelligence can be used more flexibly, efficiently, and economically.
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