Our goal from the beginning with NotebookLM has been to create a tool to help you understand and explore complex material, make new connections from information, and get to your first draft faster. You can upload sources — your research notes, interview transcripts, corporate documents — and instantly NotebookLM becomes an expert in the material that matters most to you. Today’s upgrade introduces several new features:
Thanks to Gemini 1.5 Pro’s native multimodal capabilities, you can now ask questions about images, charts and diagrams in your sources. NotebookLM will even include citations to images as supporting evidence when relevant.
We’ve been amazed by the range of uses that people are finding for NotebookLM. Because the product was developed in close partnership with authors, students and educators, we’ve seen many early adopters integrate it into research and writing workflows. Best-selling author Walter Isaacson has been working with NotebookLM to analyze Marie Curie’s journals for research on his next book. We’ve seen similar enthusiasm from documentary and podcast researchers who need to sift through complex archives to generate scripts or story ideas. But the combination of Gemini 1.5 Pro’s advanced reasoning abilities and NotebookLM’s source-grounding architecture has unlocked many other potential applications:
We’ve also noticed some unexpected and playful use cases with the help of our 14,000 member Discord community, including novelists and fan-fiction authors managing complex storylines using NotebookLM, and our favorite: role-playing game enthusiasts consulting detailed descriptions of fantasy worlds for games like Dungeons and Dragons.
If you’re new to NotebookLM, getting started is easy: When you first access NotebookLM, you’ll create a notebook and upload documents for a specific project or deliverable. At that point you can read, take notes, ask questions, organize your ideas, or ask NotebookLM to create automatic overviews of all your sources — a study guide, for example, or a table of contents. And with NotebookLM, the sources you upload are not used to train the model.
Whether it’s being used to build imaginary worlds, write bestselling biographies, or help salespeople find new customers, NotebookLM has given U.S. users powerful tools for making connections and generating insights out of large collections of documents. We can’t wait to see what the rest of the world does with it.
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