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    Can Notebook LM read Images inside a PowerPoint

    Ajay Sai

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    Ajay Sai

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    Published On

    November 12th, 2025

    Reading Time

    3 min read

    Notebook LM doesn't read images directly, but you can extract text and use it for analysis

    Notebook LM (Language Model), often used for processing text-based content, is not specifically designed to read or interpret images inside a PowerPoint presentation.
    It’s primarily used for analyzing and understanding textual data. However, there are workarounds that can help extract image information or convert the content into a readable format.
    This blog post will guide you through these methods and explain how to work with images in PowerPoint files.

    Can Notebook LM Read Images Inside a PowerPoint? Steps to Read Images Inside a PowerPoint Using Notebook LM

    Step 1: Understand the Limitation of Notebook LM

    Notebook LM cannot directly interpret or process images within a PowerPoint file.
    The model works with textual data, so extracting content from images requires additional steps.

    Step 2: Extract Text from PowerPoint First (if needed)

    Open the PowerPoint presentation.
    If you need to extract text associated with images, manually select and copy the text, or use PowerPoint’s "Export" feature to save it in a readable format, such as PDF or plain text.

    Step 3: Convert the Image to Text Using OCR

    If the image contains text that you need to analyze, use OCR (Optical Character Recognition) software or online tools to convert the image to text.
    Once the text is extracted, it can be processed by Notebook LM for analysis.

    Step 4: Extracting Image Information

    If the image is just a graphic or visual element, you cannot extract direct information from it.
    You can, however, describe the image manually or use image recognition tools to gather data and convert it into text form for Notebook LM processing.

    Step 5: Manually Provide Context for the Image

    Since Notebook LM cannot view images, you can manually describe the image’s context or relevance.
    For example, if an image is related to a specific topic, provide a description or keywords that explain its contents.

    Step 6: Use Image to Text Conversion for Analysis

    Once you have transformed the image content (either through OCR or description), input the text into Notebook LM for further analysis.
    Use the model to extract insights or summarize information based on the extracted text.
    While exploring how Notebook LM handles images in PowerPoint, consider automating your presentations by learning how to make PowerPoint slides automatically flip on a timed sequence.

    Conclusion

    While Notebook LM is not designed to read or interpret images inside a PowerPoint, there are ways to extract and convert the content of these images into a format the model can process.
    By using OCR for text within images or describing the visual content manually, you can make use of Notebook LM’s capabilities for analyzing and processing the extracted data.
    Although it's not a perfect solution, it offers a practical workaround for getting insights from images in PowerPoint presentations.

    FAQs on Notebook LM and Images in PowerPoint

    Can Notebook LM analyze PowerPoint files directly?

    Notebook LM cannot directly analyze PowerPoint files, but you can extract the textual content for analysis.

    How can I extract text from an image in PowerPoint?

    Use OCR tools to convert text within images into a readable format that can be processed by Notebook LM.

    Is there an easy way to analyze visuals in PowerPoint using AI?

    Yes, using image recognition software or APIs alongside Notebook LM can help analyze visual content in PowerPoint.
    By following these steps, you can effectively process text from PowerPoint images and use Notebook LM to gain insights!

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    About the author

    Ajay Sai profile photo
    Ajay Sai— writer at MagicSlides.app

    Ajay have been a techincal writer for more than 2+ years. from coding tutorials to using day to day apps he have helped 100k+ visitors with their various queries

    More from Ajay

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