Google Shrinks Multimodal AI Search for Phones and Laptops
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Google DeepMind wants your phone to understand your videos, voice notes, and photo library without sending everything to the cloud.
The company launched EmbeddingGemma 2 on Tuesday, a 740 million-parameter open-weight model that maps text, code, images, video, and audio into a shared embedding space. The model is designed to let developers build multimodal search and retrieval features that run directly on consumer devices.
Google said the first EmbeddingGemma has passed 20 million downloads since its 2025 launch, with developers using it for local search and retrieval-augmented generation (RAG). The second generation moves beyond text while keeping the model small enough for edge hardware.
Its modular design lets developers use a 270 million-parameter text component independently, while optional...
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