Information comes in many forms. Some information is unstructured—like text documents, rich media, and audio—and some is structured—like application logs, tables, and graphs. Innovations in artificial intelligence and machine learning (AI/ML) have allowed us to create a type of ML model—embedding models. Embeddings encode all types of data into vectors that capture the meaning and context of an asset. This allows us to find similar assets by searching for neighboring data points. Vector search methods allow unique experiences like taking a photograph with your smartphone and searching for similar images. 

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