The term embeddings is particularly at home in the fields of artificial intelligence, big data, smart data and digital transformation.
In artificial intelligence, embeddings describe a method of converting information such as words, images or products into a special numerical form - so-called vectors. These numbers help computers to better understand and compare meanings and relationships. Embeddings can be thought of as translators: They convert complex content into a form that a machine can continue to work with.
An illustrative example: If an online shop wants to make product recommendations, an AI learns which products are similar through embedding. The computer recognises that the trainers are "red" and "sporty" and recommends similar models, even if not all the data matches exactly. Embeddings therefore make relationships visible that are hidden at first glance.
This makes embeddings an important building block for smart search functions, chatbots or personalised recommendations and thus make a significant contribution to digitalisation and automation in many companies.
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