Google may soon let Gemini read your NotebookLM files and answer related queries

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    Google


    What’s happened? Google’s conversational AI model, Gemini, is reportedly getting a new interoperability feature with NotebookLM.

    • According to a report by Testing Catalog, Google is developing a new NotebookLM button or attachment option in the Gemini app.
    • The addition will allow users to import entire NotebookLM notebooks directly into Gemini chats as attachments.
    • In addition, users should also be able to import Gemini chats about a particular topic into NotebookLM for archiving or further analysis.

    Google / Google

    Why is this important? Although the feature is currently under development, it promises a deeper link between two of Google’s most popular AI tools: Gemini and NotebookLM.

    • For users working with copious amounts of data, such as researchers, engineers, or other professionals, the ability to move chats between Gemini and NotebookLM will save a lot of time.
    • From a competitive standpoint, this kind of interoperability gives Google a potential edge by offering “one workflow” rather than separate tools.

    Why should I care? The news should be of utmost importance for you if you’re a NotebookLM user.

    • Instead of manually searching for information in NotebookLM, the feature lets you import notebooks into Gemini and ask the AI chatbot your related queries.
    • If you’re a professional or a student, you should be able to upload a quarter’s financial results or a semester’s worth of notes into NotebookLM and then ask conversational questions via Gemini AI.

    Google

    OK, what’s next? We’ll likely see Google formally announce this interoperability feature once it’s ready for a full release for the general public.

    • The rollout could include different tiers (free vs. Workspace or enterprise users).
    • Keep an eye out for settings related to permission, import/export, and how Gemini uses NotebookLM content.
    • Moreover, the update unifies the user experience across two different AI-based products.

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