Not all AI tools work the same way — and NotebookLM is a clear example of why that distinction matters. In this episode, I walk through how NotebookLM works, why its underlying architecture makes it meaningfully different from general-purpose AI assistants, and what that means for how you should use it. We cover the full range of what the tool can produce — from cited Q&A and study guides to AI-generated audio overviews, infographics, and slide decks — and I spend real time on use cases for educators, a group I think has been underserved in some of our earlier conversations. We also get into the privacy and data governance considerations that anyone in academic medicine needs to understand before uploading anything to a cloud-based AI tool. If you've been curious about NotebookLM but weren't sure where it fits in your work, or whether it's appropriate for your context, this episode is your starting point. This episode also serves as an early introduction to Retrieval-Augmented Generation — a concept we'll return to in depth later this season.

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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