Google releases EmbeddingGemma 2 and an offline note-taking app

Google released an experimental note-taking app, Google AI Edge Foresight, that transcribes meetings and audio files completely offline. It is free, powered by its on-device EmbeddingGemma 2 model, and currently runs on macOS.

Google released the meeting notes app Google AI Edge Foresight, positioned as a competitor to Granola. It runs entirely offline on Mac and uses the on-device EmbeddingGemma 2 model with 740 million parameters to capture meeting content across apps, including in-person meetings.

EmbeddingGemma 2 uses the Apache 2.0 license. Simon Willison argues that embedding models should not be locked into proprietary hosted services. They often require computing and storing thousands or millions of vectors; if a provider discontinues a model, users may have to pay to recompute them. He would rather pay for a hosted version while retaining the option to run open weights or switch providers if the service shuts down.

Google DeepMind released EmbeddingGemma 2, a 740M-parameter open model based on the Gemma 4 architecture and licensed under Apache 2.0. It maps text, images, audio, and video into a shared embedding space.

Google released EmbeddingGemma 2, an open multimodal embedding model that converts text, images, video, audio, and code into numerical vectors. It has 740 million parameters. Google says it outperforms competitors with more than twice as many parameters on multimodal embedding benchmarks and scores 78.68 on the Massive Text Embedding Benchmark (Code), nearly 10 points above the previous model's 68.76.

Google DeepMind released EmbeddingGemma 2, which it calls the first natively multimodal open embedding model for on-device use. It combines code, images, audio, and video with text in a shared space.