Here’s everything that happened this week 🚀: — @GoogleMaps released 2 new features, Ask Maps to handle your most complex questions about places and trips and Immersive Navigation for intuitive routes, all with some help from the latest Gemini models — New Gemini features rolled out to @GoogleWorkspace, making @GoogleDocs, Sheets, Slides, and @GoogleDrive more helpful — In collaboration with Imperial College London and the UK’s NHS, we published breast cancer research that demonstrates AI’s potential to detect 25% of interval cancers previously missed by conventional methods — We introduced Gemini Embedding 2 (in preview), our first natively multimodal embedding model, which enables semantic understanding across text, images, videos, audio, and documents inputs all in a single model — We also launched project spend caps for the Gemini API in @GoogleAIStudio, enabling you to set a dollar amount for maximum spend at https://t.co/NApz8LVHll — Gemini in @GoogleChrome began rolling out on desktop to signed-in users (18+) in India, New Zealand, and Canada, with expansions to mobile and more regions and languages coming throughout the year
Google Launches Gemini Embedding 2, First Natively Multimodal Embedding Model
· Updated
Gemini Embedding 2 (
gemini-embedding-2-preview), now in preview, is Google’s first natively multimodal embedding model — accepting text, images, videos, audio, and documents and producing embeddings that capture semantic meaning across all input types in a single model.Most production retrieval and search systems handle modalities separately — text embeddings in one system, image embeddings in another — requiring stitched-together pipelines for cross-modal queries. Gemini Embedding 2 collapses that into a unified representation space, making cross-modal semantic search achievable in a single model.
Access it now through the Gemini API in preview — try it against a mixed-content corpus to test cross-modal retrieval across your existing content types.
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