NotebookLM: The podcast we didn’t know we needed.  

8

October

2024

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Recently, while I was scrolling through my Tik Tok app before I went to sleep, I came across a very intriguing video of a woman trying to explain the insights of a new science study. As a physics enthusiast I stopped and watched the whole video. Basically, the study was based on the origin and behavior of plasma, one of the four fundamental origins of matter. As of what I understood, what the researchers were proposing was that plasma could be a form of life and be responsible for some unexplained UFO phenomena, while it also seems to have caused some aircraft disaster incidents, based on astronaut disclosures. However, since the topic was already too hard to conceive, I decided at that moment to turn to NotebookLM and request help. 

NotebookLM is the new Google’s Gen AI tool that, similar to ChatGPT, can summarize any text we feed it with and generate instant insights. Nevertheless, it does not use the Internet’s public data as supplementary input, like most GenAI tools do, but instead only focuses on the data the user has loaded and comes with some predefined questions for better guidance. But this is not its most exciting feature. NotebookLM introduced a podcast feature in September, consisting of two speakers developing a conversation upon the topics addressed in the respective article or information given. The objective is to break down the topic in the simplest way for the listener to get the main idea.  

Back to my experience, after loading the article of the research to the platform, I requested for the podcast to be generated. It was a twelve-minute conversation between a man and a woman talking about what plasma is, how it’s connected to unexplaned phenomena, how it changes shape and the fact that it has curiosity: a basic human instict. The scariest and simultaneously most fascinating thing was their humanlike way of communication. Their voices had nothing to do with Siri or Alexa, but they were convincing enough to make me believe they were actual human beings.

I was pleasantly surprised when I realized I could indeed understand better all the components of the paper. They dived into every single aspect addressed and analyzed briefly all the important parts one would need to gain a high-level knowledge on the matter. The fact that the conversation was developed in a casual way accompanied by humoristic additions was what kept me interested, since I felt like I was also a part of it. I can surely admit that listening to this made the whole process of learning more entertaining.

This quick experience I had with the tool made me think of its potential. In my case, I can already see myself using it for getting a summarized version of the papers I will need to work on for my academic assignments. And besides the podcast feature, it can also optimize notes, divide the paper into its sub-topics, make new idea suggestions and even cite the sources when it adds information (Infosys, 2024). But I recommend it for more than just studying purposes. After all, sometimes we simply need to heal our curiosity about complicated matters, like plasma activity.  

References

Limited, I. (n.d.). NoteBook LM – powered by Gen AI. https://blogs.infosys.com/digital-experience/mobility/notebook-lm-powered-by-gen-ai.html

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6 thoughts on “NotebookLM: The podcast we didn’t know we needed.  ”

  1. First of all, a great article. Great to hear of such an AI tool, which I have never used before or heard about. Just like you it got me thinking about the huge potentials. Definitely in this day and age where people have a shorter attention span. It could really assist with the learning process. You mentioned the use for our studying, which could definitely be helpful. I believe it could also be of good use for younger people to explain difficult topics in high school. Besides that is it even easier to start your own podcast this way and I’m wondering how many businesses are already using it.
    Again great article and I will definitely try it out myself.

  2. Very very interesting. While the novel concept of NotebookLM is definitely at the center of this article, what I found particularly profound is that the GenAI asked follow-up questions before generating its output. It has happened to me too often that my prompts are too short, not detailed enough, or plain stupid. Especially frustrating when you are using a GPT with which you only have limited uses.

    Back to the center of the article. The ability to manufacture a nuanced conversation about a topic of interest offers great possibility. Imagine wanting to learn about ancient Rome on your way to work, being able to interrupt the podcast to steer the conversation into a new desired direction. Give it a few weeks of ‘from and to’ work commute and you’ll already have garnered so much knowledge!

    Amazing, will definitely try it out!

  3. Hi, Eva! Amazing blog! I have never heard of this tool before, but I find it very interesting. The idea of a tool that summarizes complex papers and turns them into engaging podcast-style conversations can appeal to many people, especially because sometimes it is even easier to listen to a podcast rather than read the article itself. It’s impressive how it can make challenging topics, like the one you mentioned, easier to understand while still keeping things engaging. This tool seems like a game-changer, not just for students, but for anyone curious about difficult subjects. I can definitely see it making high-level topics more accessible to everyone.

    1. Thank you Alexandra!
      Hope you find it as useful as I did. Let mw know your thoughts when you try it out!

  4. Great blog! I recently also came across NotebookLM and was completely fascinated by how realistic the podcast feature is. I was expecting it to sound like the usual robotic text-to-speech features that many AI tools use, however, it turns out that it sounds like a very realistic conversation between two people. As you mentioned, I also agree that this tool has huge opportunities to break down complex concepts that some might struggle to understand. This feature is a great example of how we are still at a very breakthrough stage of GenAI and it will be interesting to see how much more can be developed. It is definitely a cool feature that can make learning and productivity even easier to achieve

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