The New Features of Google’s NotebookLM: A Critical Analysis

Google’s note-taking app, NotebookLM, has recently introduced new features for users to enhance their research and organization capabilities. These updates include the ability to upload Google Slides and web URLs as sources, an improved Notebook Guide that generates study guides and FAQs, and an increased limit on the number of sources and word count allowed per project. As a reporter covering AI, I had the opportunity to test out these features and assess their functionality firsthand.

One of the key updates to NotebookLM is the expanded range of sources that users can upload. Previously limited to Google Docs, PDFs, and text files, users can now include Google Slides and web URLs in their projects. This allows for a more comprehensive collection of information, making it easier for researchers, students, and anyone in need of organizing data.

The new Notebook Guide feature in NotebookLM is designed to create study guides, FAQs, and briefing documents based on the sources uploaded by users. This tool streamlines the process of summarizing and organizing information, making it easier to grasp key points and facts. Additionally, the inline citations feature enables users to fact-check AI responses, providing up to 50 sources per project.

NotebookLM now runs on Google’s Gemini 1.5 Pro, a large language model that powers the Gemini chatbot. This integration allows users to ask questions about charts, images, and diagrams uploaded to the platform. The model provides accurate information based on the user’s corpus of data, ensuring that responses are sourced directly from the information added to NotebookLM.

During my trial of NotebookLM, I was able to explore the new features in action. While the Notebook Guide was not yet available for testing, I successfully added new data sources and utilized inline citations. Gemini 1.5 Pro proved to be efficient in interpreting graphs and summarizing complex texts. However, I encountered difficulties when trying to upload web URL sources, as the model failed to display them in the list of sources.

Despite the advancements in NotebookLM, there are still areas that can be enhanced. The model’s inability to retrieve web URL sources effectively limits its capability to gather information from external sources. Additionally, while the platform is not intended to write research papers, it could benefit from features that assist in generating coherent narratives based on the collected data.

Google highlighted examples of how NotebookLM has been utilized, citing author Walter Isaacson’s use of the platform to analyze historical journals for his upcoming book. While the platform offers valuable tools for data organization and analysis, it falls short in comparison to other similar tools like Perplexity’s Pages, which aims to simplify data sharing but may have usability issues.

The new features of Google’s NotebookLM present promising advancements for users seeking to streamline their research and data organization processes. However, there is still room for improvement in terms of sourcing capabilities and narrative generation. As technology continues to evolve, it is crucial for platforms like NotebookLM to adapt and enhance their features to meet the ever-changing needs of users in the digital age.


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