GoKawiil
Tech News
Google has introduced a new AI-powered note-taking application for Mac that operates entirely offline using on-device models. The app, named Google AI Edge Foresight, allows users to record, transcribe, and review meeting notes across various apps, supporting manual input and AI-generated summaries. It also enables document uploads to build a knowledge base for real-time question answering during meetings.
Google has released an experimental app called Google AI Edge Foresight that transcribes meetings and audio files entirely on-device, using its EmbeddingGemma 2 model. The free app turns shorthand notes into polished summaries and includes a built-in assistant that can answer questions about meetings or connected local files, with Google saying data never leaves the user's computer. It currently only works on Macs with Apple Silicon.
Google unveiled EmbeddingGemma 2, a multimodal on-device AI model that can process text, images, video frames and audio locally. Alongside it, the company released AI Edge Foresight, a macOS app that expands shorthand bullet points into polished meeting notes and answers questions live during meetings, all without sending data off the device.
Google introduced EmbeddingGemma 2, a 740M-parameter embedding model that maps text, code, images, video, and audio into a single unified embedding space. It supports flexible output dimensions from 768 to 128 via Matryoshka Representation Learning, offers an 8K context window—four times larger than the text-only EmbeddingGemma—and is released under the Apache 2.0 license.
Google unveiled EmbeddingGemma 2, a 740-million-parameter multimodal AI model built on the Gemma 4 architecture and released under an Apache 2.0 license, designed to run locally on devices like Pixel phones using minimal RAM. The company also launched Google AI Edge Foresight, a Mac app that uses the model to transcribe meetings, expand shorthand notes into polished text, and answer questions by searching local files, calendars, and Google Drive content—all processed on-device.
Google launched EmbeddingGemma 2, a follow-up to its original EmbeddingGemma model that reportedly surpassed 20 million downloads. The new 740-million-parameter model is built on the Gemma 4 architecture, released under an Apache 2.0 license, and extends beyond text to embed code, images, video, and audio in a single shared space for on-device inference.