Deep Transfer Learning (Glossary)

The term Deep Transfer Learning belongs to the categories Artificial Intelligence, Digital Transformation and Industry and Factory 4.0.

Deep transfer learning describes a modern method of machine learning. Here, an artificial intelligence (AI) first learns a task, such as recognising images, using large amounts of data. This knowledge is then transferred to a new but similar task so that the AI can learn much faster and with less data.

A simple example: an AI is trained to recognise cats in photos. This AI can then use its "knowledge" to identify dogs in photos. The basic techniques of image recognition - such as recognising fur or ears - remain useful, even if the tasks are different. This saves a company a lot of time and expensive data.

Deep transfer learning thus simplifies the introduction of artificial intelligence into new business areas and production processes. Companies benefit from this because existing models can be reused and the effort required for new AI applications is significantly reduced. This makes the technology particularly interesting for companies that want to react quickly and flexibly to trends.