Google’s new NotebookLM update feels like a superpower. The ability to snap a photo of handwritten notes or a complex diagram and have the AI instantly “read” and index it is a game-changer for digital research. But after testing it extensively, I need to be real with you: this tool is not magic, and if you use it blindly, you are going to get burned.
The “Garbage In, Garbage Out” rule applies here more than ever. While the Optical Character Recognition (OCR) is impressive, it has significant blind spots that most users overlook until it’s too late. From misreading crucial data points in blurry photos to the hidden privacy risks of cloud-based processing, trusting this tool without a strategy can lead to inaccurate reports and compromised data. In this post, I’m breaking down the biggest flaws you need to avoid to keep your research professional and secure.
Key Takeaways
- OCR Accuracy is Conditional: Messy handwriting, shadows, and low-resolution screenshots will confuse the AI. Always verify critical numbers and facts against the original image.
- The Privacy Trap: Remember that every image you upload is processed on Google’s cloud servers. Avoid uploading confidential client data, medical records, or sensitive financial documents.
- File Constraints: Be aware of the strict caps on file sizes and the number of sources per notebook—this isn’t an unlimited storage dump.
- The “Verify” Rule: Treat NotebookLM as a starting point, not the final answer. If the source image is flawed, the AI’s summary will be too.
Don’t let these mistakes cost you hours of work—watch the full breakdown below to learn the “Pro” workflow for getting perfect results every time.
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