I’m working on keeping things simple in my life and business right now.
What do you all mainly use NotebookLM for? How does it compare to tools like Claude?
Quick guidelines for posting here
Share your resources clearly
Here are some tips for your posts:
- Posts should have at least 100 characters. Add as much detail as you can.
- When asking for help, explain your needs fully.
- When sharing resources, make them easy to understand for everyone.
- Include helpful links like videos, notebooks, repositories, etc.
Let the mods know if you need any help or have feedback.
I’m a bot, and this action was performed automatically. Please contact the moderators of this forum if you have any questions or concerns.
I use it for medical research. I’m dealing with cancer, and it helps summarize studies that are hard to read. I can also ask questions and explore the info further.
I’ve used it to help my son with his thesis by turning it into a podcast so I can understand it better. He even used it to prep for a visiting professor by summarizing their work into a podcast.
Other uses: summarizing scripts for a show I’m working on, creating podcasts about them, and translating historical documents. I combined a 16th-century document in German and Latin with some related info, and it explained the motivations behind it all.
It’s also great for things like summarizing union contracts or local building codes—quickly finding answers like the minimum railing height for a balcony.
I mostly use it for organizing academic knowledge.
NotebookLM is more for research. It lets you search through multiple documents and ask questions about them. If you need something to write essays or generate content, tools like Claude are better for that.
So they’re pretty different. NotebookLM is great for info retrieval, but it won’t replace tools like Claude.
@Riley
Claude’s projects can handle document-based queries too.
@Riley
That makes sense. I only mentioned Claude to compare it with NotebookLM. Thanks for explaining.
Colby said:
@Riley
That makes sense. I only mentioned Claude to compare it with NotebookLM. Thanks for explaining.
There’s no such thing as a ‘standard LLM.’ They all work differently depending on the scale, training, and features they include.
@Juneta
If you’re interested, Lex Fridman had a great interview with Dario Amodei where they talked about how small changes to models can make a big difference. Worth checking out.
It’s not like the usual chatbots. But it’s fantastic for handling huge amounts of text. Imagine 400 pages of documents—you can just ask questions and get answers fast. I use it all the time.
I use it to make worksheets for my kids based on YouTube videos. They watch the video, listen to a podcast summary, and answer the worksheet questions.
I upload my lecture slides, reading materials, and sometimes audio transcripts. It’s awesome for making study guides, and I listen to the podcasts just because they’re cool.
I turn documents and videos on a subject into a podcast that I listen to on my commute. Saves so much time.
How do you make sure the summaries aren’t full of errors or hallucinations?
Merrick said:
How do you make sure the summaries aren’t full of errors or hallucinations?
Aren’t the main points sourced? You can check the cited material to verify.
I uploaded company earnings call transcripts into NotebookLM and used it to track their growth over time. It’s great for focused research, and it helps me stay updated on their progress.
It’s great for summarizing long papers, articles, and videos when you just need the key points.
I’ve tried it out for content creation, and I was surprised by how well it worked with minimal input. The new features for scriptwriting are promising, though I hope they add more variety, like having multiple characters in discussions.
I used it to summarize ballot measures I was undecided on. The PDFs were super dry, so I had it turned into a podcast and listened while making dinner. Really helpful.
It’s really good at breaking down complicated ideas. I use it to analyze my campaigns, but you have to double-check its work—it sometimes compares things that don’t go together.