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Google AI Edge Foresight is an experimental Mac meeting companion that uses meeting conversation to add context to shorthand bullets you type. Google says it processes audio on-device and can work offline. The feature is not described as handwriting recognition: “scribbles” here means manually entered shorthand, not handwritten pages scanned into text.
How Foresight turns shorthand into fuller notes
During a video or in-person meeting, you type brief bullets about the points you want to remember. Foresight listens through the Mac’s system audio and microphone, then uses details from the current conversation to enrich those notes. Google describes this as retrieving meeting details in real time; it is not simply a tool for converting handwritten pages into text. (Google’s announcement; 9to5Google’s account)
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That distinction matters: the workflow starts with shorthand you enter, while the conversation provides context. The available descriptions do not establish how accurately Foresight transcribes speech, how it handles overlapping speakers, or how complete its generated notes are.
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Google says Foresight processes audio and other personal information on the device, and that its integration with system audio and the microphone lets it work offline. Google also says it works with any meeting platform. These are claims in the October 6, 2026 announcement, not independently verified test results. The available reporting does not establish the app’s transcript accuracy, battery impact, or end-to-end response time.
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Search across a personal knowledge library
Foresight is also presented as a natural-language search and recall tool for personal materials. Google says it can retrieve information across images, documents, transcripts, and notes. 9to5Google reports that users can point it to project folders, reference materials, diagrams, calendars, local files, and Google Drive. That reporting is not a complete list of supported formats or proof that every source works in every setup.
What the model figures do—and do not—tell you
Google describes EmbeddingGemma 2, the multimodal model associated with this announcement, as having 740 million parameters. The company reports visual-embedding latency of 37.3 milliseconds per image, or 26.9 images per second, on a MacBook M5 Pro GPU. This is an image-embedding benchmark, not a measure of how quickly Foresight produces meeting notes.
Rank #2
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- 【High quality and long time】 uses DSP noise reduction technology to filter out environmental noise, has high-quality recording, 【1536kbps】to restore the real scene. It can continuously record for more than 30 hours and play for 7 hours.
Google also gives memory examples for a Google Pixel 11 Pro after quantization: about 191 MB of active RAM for text-only weights and about 567 MB for the full multimodal model. Those figures describe the model on that named Pixel device; they do not specify Foresight’s Mac requirements. Google’s announcement does not provide a minimum macOS version, supported Mac models, or a Mac memory requirement.
What is still unclear
Foresight was announced as an experimental Mac app on October 6, 2026. The available descriptions explain the intended workflow, but do not establish independent results for note quality or transcription, detailed compatibility requirements, or the full range of supported file formats and integrations. Google says there are no cloud subscription costs; the announcement does not establish a paid tier.
Quick Recap
Best Value
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Rank #4
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