Introducing multimodal Embed 3: Powering AI search

Embed 3 is a multimodal embedding model designed to streamline database management by allowing the inclusion of both image and text data within a single database, thereby reducing complexity. Unlike other models that tend to segregate text and image data, leading to biased search results, Embed 3 focuses on the meaning behind data to provide relevant search results without favoring a specific modality. It demonstrates high retrieval accuracy evaluated through NDCG@10, even when embedding images with multilingual text from various languages like German, Spanish, and Chinese, showing robust performance in real-world noisy data scenarios. Available on platforms such as Cohere, Microsoft Azure AI Studio, and Amazon SageMaker, Embed 3 enables enterprises to create effective search and retrieval applications that extract key data from images, supporting over 100 languages. This new tool is part of an ongoing collaboration with Microsoft Azure AI, emphasizing the commitment to providing diverse AI tools to businesses, with the model also available for private deployment on Virtual Private Clouds or on-premise environments.

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