The term \"multimodal embedding spaces\" originates from the fields of Artificial Intelligence and Big Data, as well as Digital Transformation. It involves storing and linking information from various sources \u2013 such as text, images, speech, or even videos \u2013 together in a digital space, known as an embedding space. <\/p>\n
Imagine this embedding space as a huge cupboard, where different types of information are sorted according to a unified system. This allows an AI, for example, to recognise that a dog in a photo and the word \u201edog\u201c in a text belong together. It thus understands the connections between images, words, and even sounds much better.<\/p>\n
A concrete example: In modern product search for online shops, a customer can upload a photo of a trainer and be shown matching results, as if they had written a detailed search query. Multimodal embedding spaces make it possible for artificial intelligence to evaluate different data types together and thus offer more intelligent services \u2013 whether in online shopping, image search, or everyday assistance systems.<\/p>","protected":false},"excerpt":{"rendered":"