Feb 18
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We explore the potential of AI embeddings, explaining how unstructured text and imagery can be converted into numerical vectors to enable semantic search. Showing how FME acts as the central orchestration engine, managing data extraction and communicating with open-source models to generate embeddings without the need for complex infrastructure. Concluding with practical examples, including a multi-lingual data search and an image-based property finder, illustrating how organisations can easily implement sophisticated AI capabilities with FME.