Multi-Head Attention is a term from artificial intelligence and is primarily used in big data and smart data, as well as digital transformation. It is a special technique that artificial intelligence models utilise to better understand large amounts of data simultaneously.
Imagine Multi-Head Attention as a team of experts simultaneously looking at different parts of a text, each with a different focus. Each expert draws their own conclusions, and these are ultimately combined to grasp the bigger picture. This way, the system can, for example, identify what the customer initially said in a long customer dialogue, but also how the conversation developed later – all information is kept in view.
The main advantage of multi-head attention is that machines and programmes can analyse information much more accurately, recognise connections better, and provide more relevant answers. For example, this helps to make chatbots more intelligent, improve automatic translations, or analyze and understand large volumes of text in businesses more quickly.
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