NotebookLM: A GenAI Summarization Tool
About this resource
NotebookLM is a generative AI tool designed to assist with understanding dense, complex texts, including research papers in machine learning and AI. Developed by Google Labs and powered by the Gemini 1.5 Pro large language model (LLM), NotebookLM leverages advanced AI capabilities to provide summaries, answer questions, and generate audio versions of summaries. This makes it an invaluable resource for practitioners looking to dive into highly technical material.
GenAI use at UW-Madison
UW–Madison faculty, staff, students, and affiliates are required to follow campus policies relevant to AI use. Uses of generative AI that are explicitly prohibited by policy include, but are not limited to, the following:
- Entering any sensitive, restricted or otherwise protected institutional data – including hard-coded passwords – into any generative AI tool or service;
- Using AI-generated code for institutional IT systems or services without review by a human to verify the absence of malicious elements;
- Using generative AI to violate laws; institutional policies, rules or guidelines; or agreements or contracts.
Key features
- Summarization (Text and Audio): Quickly generate concise textual summaries of dense ML/AI papers and convert them into a podcast-like audio summary. As an example, check out this audio summary of the paper, Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters, by researchers at DeepMind.
- Interactive Q&A: Ask specific questions about uploaded papers and receive detailed answers tailored to the content of the document.
- Gemini 1.5 Pro’s strengths: Provides advanced contextual understanding and reasoning across diverse content, making it well-suited for technical and research documents.
- Generative flexibility: Capable of handling complex queries and summarization tasks without requiring fine-tuning for specific domains.
High-level tips & pitfalls
- Iterative interaction: Don’t hesitate to refine questions or dig deeper into concepts for thorough understanding.
- Over-reliance on summaries: While summaries are helpful, always cross-check details in the original document for accuracy.
- Data privacy: Avoid uploading proprietary or sensitive documents, as NotebookLM’s privacy practices are tied to Google’s terms of use.
Questions?
Have questions about using NotebookLM? Join the discussion on the ML+X Nexus Q&A.
See also
- UW Generative AI Services & Policies: Learn about enterprise genAI tools supported by DoIT/UW-Madison.