Master Notebooklm In 40 Minutes | How To Use Notebooklm | Notebooklm Tutorial | Simplilearn

Every one of us whether we are studying, teaching, building or even leading projects knows how quickly our ideas can outgrow the tools we use. Notes scatter across platform sources pile up and soon we are spending more time managing information than creating impact. That's exactly where Notebook LM steps in. A workplace powered by AI to help you organize, analyze, and create effortlessly. It's built to adapt to you, students sharing lessons, educators designing courses, professionals crafting strategies, and teams building large scale reports. And with Gemini 3 Ultra Engine, Notebook LM takes that ability to an entire new level, offering smarter insights, longer presentation, watermark free exports, and also lightning fast generation across everything you build. In this section, everything you'll see is created using Notebook LM Ultra, the top tier experience made for those who think big and work fast. It's where productivity meets intelligence and where ideas truly come to life. Now, if you want to master the AI systems powering Notebook LM Ultra and take your generative AI skills to enterprise level, check out the advanced executive program and apply generative AI from IITM Parvatak and Simply Learn. This 4month live online program is perfect for students, educators, IT professionals and teams who want to lead in agentic AI and GNAI deployment with 70 plus hours of hands-on labs using tools like Copilot, Azure AI studio, chat, GPT, DALE and hugging face. You'll master agentic AI frameworks, MCP protocols, LLM, prompt engineering, rag application through seven capstone projects and 15 plus realworld case studies. Plus, get a two-day campus immersion at IIT Madras Research Park, exclusive master classes from IITM faculty and alumni and Microsoft badges for Azure AI fundamentals and co-pilot certifications. Similar job assistant includes AI resume optimization, mock interviews, one-on-one career mentoring, and exclusive hiring opportunities from top tier companies. Also, earn allied certification from IITM Parvatak Technologies Foundation plus startup incubation eligibility. Hurry up and enroll now. The link is given in the description box below and in the pin comments. Before we get started, here's a small question for you to answer. What's prompt engineering mainly about? Is it making prompts longer for better results? Crafting specific instructions for an accurate output? Adding more training data to the model? Changing the model's temperature setting only? Let us know your answers in the comment section below. Now, let's get started. Now, how to sign into Notebook LM? It's pretty simple. So if you're having a Google account, you'll have a pretty much free tire to execute in notebook LM. So just type in notebook LM and open the first link that is showing which will show you how to login via your Gmail account which is basically your Google account and then you will see a similar notebook which has been opened. So here you can see all my details. This is a free version and uh here you can create the notebooks. There's option of share settings and normally when you open Google you'll have other details such as documents drive etc here and here is the main thing. So adding sources is the main point of this notebook alm. So it analyzes each and every document whether it's from the internet or you're uploading yourself everything will be here displayed and regarding these documents which are uploaded here you can ask any question here. Now coming to this part you can see an audio overview and create an audio also is available in Hindi, Canada and other languages as well. So you have overview and then you can create a slide and a video overview also which creates a video based on whatever topic you're working on. A mind map is also given reports. You can create flashc cards, quiz, infographics and also data table. All these will be generated according to whatever information or even the links or documents that you are giving to the notebook LM within just one click. Now how do you create new notebook? So starting with you can see a name. This is a new notebook. If you want to create another new notebook just click on create notebook and then you'll see a similar version. Now just cross it back and you can rename it whatever uh notebook you want. Now before we get started, let's see what are the options available for the subscription plan. Now as you can see here there are standard which is notebook LM standard version, notebook LM plus pro and ultra. Now how do you sign up for each of those? We just need a Google account for a notebook standard. We need a Google AI plus plan for a plus notebook version. For a pro again we need Google AI pro plan and for Google AI ultra you will get a notebook LM. Now if you come down you can see the usage limit for each. For a free version it's 100 per user. For a plus version it is 200 per user. For a pro version it's 500. And for a ultra it is also 500. Now how many number of sources or links or documents can you add in your chat? It is 50 for a normal free version 100 for plus 300 and 600 for pro and now we also talked about audio generation video generation. Now the quality and the quantity also a free tire uh audio overviews are only available three per day and for plus user it is six for a pro it is 20 and for a ultra it is 200. So basically you can create 200 videos per day and it is similar to the audio ones as well. Now as you can see for a pro and ultra versions we can create cinematic video overlays but for the rest of the one it's going to be a normal version. Now again reports also we have repeat for reports also we have a certain number of executions which are available quiz mind map deep research data tables infographics etc. Now what are the premium features here? Customer chat analysis and advanced sharing are the things Gemini models used access to Gemini models all the of them are the accessible to Gemini model but the priority is for ultra models and pro models. Now watermark of videos especially will be available here for only for ultra ones. Rest all versions you can identify this video will be generated by a notebook element. Now here are some applications etc. Now what is the cost of getting this versions? So basically you have to go for the cloud versions. So for a plus version it is costing you around 200 per month for 6 months and then we have pro version which is again with peaks of storage etc. We have to pay,950 per month and also for the ultra people you have to pay 24,500 per month. Again, this is included the storage that you're buying whether it's a big institution, small institution, whichever is suited for you. Choose wisely for your own requirements. Now, this is the basic prompting that I have showed you before. But here I have the ultra model just to see the difference and making more easier for me to explain. So, starting with it starts with the same uh interface as for a free plan also. Now here you can see it has given me is if there is any other better questions you can ask it. Now let's try with the second document. I'm adding one more source upload file. You can upload the website as well which will come to it later. This is about uh computing and AWS as well. Now according to this document let it get uploaded and then I'll be listing five most important AWS features for cloud beginners. So the document is done. So let's just give the prompt for this. I need list the five most important AWS fe for cloud beginners. Let's just give this again. It's a very big notebook that I've given which is in the PDF format. If you're using a free version, you might face a little bit delay in the peak hours and you might have a limit for your number of chats that you're doing etc. So as accordingly plan yourself whether to upgrade it or not. Now here you go top five most important AWS features for beginners you have the top five of them which is from a document which we have uploaded. Instead of just sitting and going through the entire document you can refer to here. Now let's add the third resource. Again it's the same procedure upload and the document whatever you need. Again this is Amazon EC2 user guide. Now from this I need what EC2 is and the main use cases and when to choose it. So let's just type in the question key by the time the notebook will get uploaded. So the question for me is what is EC2 explained? Let's add what EC2 is. Let's say its main use cases and all need to know when to use it. So this is my question. Now how many pages is this one? Let me just check. It's about 3,765 pages. So instead of reading all these things, it is a better option to upload and ask the question. It will take some time for large files to get uploaded and also to read it. By that time, I'll just add the next ones also, next two PDFs also so that it's easier for me to upload. Those are also huge files. So by the time we come to the question, it'll be done uploading. Okay. So the notebook 3 is uploaded which is the EC2 one. So the question that we asked was explain what EC2 is, what is its main cases and when do I need to use it. So this is a question specifically asked for an entire document which is around 3,700 pages. Now let's give it the question. It might take some time because it's a huge file. As you can see it is showing me the steps as well. So composing, expanding instant types etc. And here you go. you have the answer for the question that you specifically wanted from a document of 3,700 pages. Now, Amazon Elastic Compute Cloud Amazon EC2 is a web service that provides secure, resizable and ondemand computing capacity in the AWS cloud. It allows to launch so and so and then you have the main cases which I also used asked for and then there is also main use cases which I asked for. So it is general purpose workloads, compute and memory intensive task, machine learning and AI, graphics and rendering, Apple platform development etc. Now I asked one more question with this which is when to use EC2. Now it is showing me that you should use EC2 whenever you need flexible cloud-based virtual services. Deciding exactly how to use it depends on your words predictability, duration, flexibility. The AWS offers several purchase models and we have the use on demand instance, use spot instance etc. Now coming to the fourth document that we have uploaded it's regarding cloud computing. Now from that document I want to source diversity and general cloud definitions. Now again it's going to go through the entire PDFs and gather the information. Now here's an option of selecting and deselecting. So after upload if you don't want the answer to be from so and so documents you can just untick it and here you go it will process only that specific document now the answer is here cloud computing is broadly defined as an IT parademic that enables on demand delivery of share computing resources such as compute power databases storage application and networking over the internet so we have elasticity and self-service provisioning building and metering resource multiplex texting etc. So we have the answer. So from the fifth notebook which is about IBM database. Let's ask a question. Let's say give beginner friendly explanation and source cards. Again I want it only from the notebook five. So I've just click on it. So it's easy for them to understand from which document should I go through. So here you go. I'm set creating a set of beginner friendly flash cards. You can see study on these concepts. So we have what is cloud computing? You can use this as a flashc card for you to study. Now can I upload all the files and ask all the questions at the same time? Yes, you can. As I showed you before, you can select up to 50 sources which is including your PDFs, your online links, etc. and upload it in a free version, but it goes up to 200 in an ultra version. Now check that out. It was a breeze through the documents for the exact question to be answered within a few minutes. Now next we will check out how we can add links. So first let me search on web as Amazon EC2 user guide and add it. So let's create another notebook for this. Again it's showing whether to apply website etc. So here itself you can start and I need links to Amazon EC2 user guide. So let's just type in Amazon EC2 user guides. I want it from the web and you can search it from your drive also and then go for it. So here you can see it will search the links according to the topic that I've given and list out the links that is available. So you don't need to physically go online copy and paste the link from there to here. It searches on its own. So as you can see we have 1 2 3 and seven more. So out of like 10 resources. So how do you get this into the chat? We can just say import. So these links will be read by notebook LM. Now after this based on whatever information has been provided I'll be asking a question in the chat itself. So as you can see one by one all the sources have been imported. Now here the basic question will be to explain EC2 versus lambda as of teaching for a beginner. So let's just say explain EC2 versus lambda as if teaching a beginner. Two more sources are left. It'll take few minutes. So I think the answers will be available in the other document. So I'm just clicking it go and it will start its result. So here you go to understand the difference between Amazon EC2 and AWS Lambda. It helps to look as much as control you want versus how much your underlying work you want in Amazon to handle. So here's an explanation that you can go through and understand is as simple as possible. Now let's starting the question. How you can can you create a table or not? So I'll just say create a comparison table of computer let's say compute versus. So let's see if it can create. So as you can see there is a comparison table for EC2 and AWS lambda that you can get it. So core concept it's a virtual server in the cloud whereas this is a service that runs small piece of code and you have different categories and what are the major difference. Now what about any questions say interview preparation something like that. So let me ask give three questions let's say interview questions based on this sources. Let's see what and how it can help us crack any interview based on the same concept. Now here you go. The first question is storage optimization and EBS volume selection. What is the answer for it and expected question regarding this topic? And then we have topic two again question and expected answer from it. Question three question and answer from it. Now there you go. You can add resources from directly from the web to this and then generate as number of questions you want as number of learning you can want can be generated within just a small click. Now how about creating a podcast and other things as I mentioned earlier we'll get into that. First let's see how if we can create a audio overview which is basically a cloud career path. Now again I'll start with a new notebook and then name it cloud career and then here I'm going to add resources regarding the path for cloud career. I'm just giving the keyword not much. I'm going to search in the web and go for it. Now what is the prompt that I should give? I should create a small podcast. So regarding that we should create a proper prompt. Now again we have various 10 of the first appearing sites. So let me just import it. Take some time to import all these sites. Before that let's create a prompt. Now as you can see all the sites have been uploaded and you can see here. Now let's say create a short podcast summarizing summarizing my notebook for a tech learner. And let's just create it and see what appears. So as you can see it is first reading through all the websites that we have uploaded. Now here for 8 minute postcard for a free version we get three per day. Now here whatever audio or video we are generating it will appear in the studio version. Now what is a studio? This entire thing is a studio. We can create audio video which I'll talk about it later. So as you can see we are generating audio overview. It'll take a few couple of minutes to make me. Now I also need a video on let's say the same thing. Let's create a video on the same topic. Let's say also create a video overview and let's just say go for it. Now as we all know we have mentioned about automatic narration visuals and ideal use for YouTube shots. So you can just answer it and create YouTube shots as per your needs. Oh, audio is still generating and we'll put in video also. It'll take some time to generate but then it'll be good. Excuse me. Now, I'll come back to that. In the meantime, let's create a study guide. Cut that part and um so in the meantime, I'll tell you what are the things actually we can create. So, I'll just here for example take about notebook LM itself and I'll do the web research and I'll just say go. I'll be creating for the same topic. I'll have a audio overview, slide deck, video overview, a mind map, reports, flashcard, quiz, infographics and data tabs. Now, how do I do that? I'll just as usual import all the necessary links which has the information and then as you can see it's all done. Now, in the studio itself firstly, we can create an audio overview in different languages. So, I'll do this at the last. So, I need a audio overview. So, instead of typing the prompt, there is an option to click on it. So just click on it and as you can see it will start generating an audio overview. Now I need a slide deck. So just click on slide deck and slide deck also will start to create that means actually with a click you can create a slide about notebook element. Next we have a video overview. So you can just again click on it and it'll be generating. So you here for video generation we have three moders which is cinematic, explainer and brief. So since this is a kind of a tutorial to explain notebook LLM which is an explainer we can choose the language auto select custom whiteboard etc classic etc. Now we can hit on generate now it'll start generating the video as well. So we have audio slide deck and a video which is starting to create. If I want to study the best thing to go by is a mind map which is like a flashcard kind of a situation. So just click on it and you'll be ready to go. Sorry. So the mind map is ready. We'll take a look into that. We can generate reports also in one click. Now it is creating create report. What format? What format do you want? Do you want as a briefing document, study guide, blog post, etc. So let's say study guide and it'll start generating reports as well. Now I need flashcards to study about this particular topic. Now click on this and your flash card will start generating in a few seconds. I need a quiz just click on quiz. Infographics again click on infographics. If you want and also if you want any kind of data table according to the notebook LLM whatever you uploaded just click on data table and it will start generating a data table as well. All are generating within few seconds or few minutes based on what audio and video will take a huge amount of time since there needs to be a processing time as well. Now coming back to the previous one whatever we have generated here the audio is done. So let's listen. So let's just listen. This is the brief on launching a cloud computing. The cloud market is absolutely booming with lucrative fast growing opportunities. But breaking in actually requires a strategic mix of specific technical skills and proven hands-on experience rather than just a traditional IT degree. First, you've got to pick a specific career path. You could be a cloud engineer building out infrastructure, an architect designing the overall framework, or even a security analyst protecting data. For any of these, you need foundational skills. Linux scripting languages like Python and basic networking like firewalls and TCP which is basically just how computers talk to each other. Honestly, learning a major cloud platform like AWS, Azure or GCP is exactly like learning your first programming language. Once you So this kind of audio can be used in your editing profiles or to create a short or to create a podcast shot etc. In so many ways you can use this. Audio books can be uploaded regarding each topic and you can literally start using this and make money as usual. Now still the video generation is in process. We'll come back to this. Let's go back to all the things that we have created regarding the notebook LLM. The first thing was audio. I think audio is still generating. Video and slide dig. These three things are still generating. It'll take a while. So let's just start with mind map the next thing. So it has created a mind map. So as you can see we have LM 2026 features and workflows interfaces etc. Now you click on I want to study this. So it gives another huge page where core advantages can be studied etc. So every topic has its own branching. So you can tick mark after studying each of the topics. This is a very useful tool for students who are actually studying. they usually go for mind maps because it's easier for them to follow up and finish the topic. So let's go back to the studio and uh since mind map is done let's check the reports now let's check at the reports that is created which is a study guide so as you can see part one we have short question and answers then we have key answers to the questions that is there up etc. So this can be your Q&A session and this could be only reason required for you to prepare. You can just copy this paste it and study in a Q&A format which is much easier for studying. So go back and then what is the next one? We need flash cards. I think flashcards yes flash cards is also created. So let's just look into that. So as you can see what is the primary functions of revised interfaces in notebook LLM in 2026 slide upgrade. So you can just see and then use the flashcards to learn and study about the important topic. Now let's go back to the studio. After flashc card what is there? A quiz is there. So let's take a look at the quiz. So here is the quiz. So according to the cand university study or external cervical recept option ECR which is a primary reason notebook LM was hypothesized to outperform Google Gemini. So here are your options. You can just randomly click on it and then get if it is right or wrong. And then coming to infographics. Now here you can see just click on infographics and you'll have a infographics available. So as you can see you can use this as your entire way of studying phase one research and synthesis phase 2 this is the thing. Basically if you look at this you'll understand what notebook LM in 2026 does. So this is also very pretty important tool for students especially who are learning concepts etc. Now after infographics we have data table. So let's see if the data table is ready. Yes. So let's just open that and you can see data table which is feature name. What are the features available in notebook description primary use cases user category key benefits accuracy and reliability and the source. And we have prompt based data tables, mind map, c cinematic videos, pptx, export, artgraph creations from chat etc. So many in one data table. Now left is audio slide deck and video. Let's check if I think the slide deck is ready. So let's just check that. Basically a presentation. So let's just play the entire presentation. So as you can see you have good images, good quality and then a definitions a synthesis engineing master notebook element in 2026 a defining guide to transform a basic AI chat to enterprise grade production synthesis and even cloud universe reasoning. Now go for next we have other things. So basically you can start presenting your entire presentation without even typing one single letter. So as you can see prom based step one it's onp point presentation if you ask me it's very crazy it's good in colors and legal terms notebook gemini etc the master playbook a fivestep methodology etc so many things into one slide without even typing one single letter this is a pretty good slide now let's head back to the two most important which is the audio and the video so still video is generating and audio is generating I think The previous ones audio should be done by now. Video should be done. So let's just see. No, it is still taking time. So let's get back when both of these are done. Now the video and the audio for notebook lm is ready. So let's just play it. So let's start with the audio one. I want you to imagine just for a second staring at your computer screen on a Friday afternoon. Oh, we've all been there, right? You have this absolute mountain of reading material open. There's a dense 30-page PDF report, a messy spreadsheet with like hundreds of rows of data, and maybe a long rambling video interview. It's a classic end of the week pileup. Exactly. And you need to pull a single coherent accurate insight out of that chaotic pile in exactly 5 minutes. Now, as you know that here, it's like a audio based on two people conversing. So, you can just listen to that and understand the entire concept. Now, coming to video, let's open the video up. Now, this is a 7 minute long video which I'll display it. We keep hearing about these giant do everything AIs, right? Well, today we're looking at something different. A tool that's designed to do just one thing, but do it incredibly well. So, the big question we're going to tackle is this. Is Google's Notebook LM actually the future of how we do research? Look, we've all been there. Whether you're a student, a lawyer, a researcher, you know the feeling. You're just buried under a mountain of digital documents. It's totally exhausting and it feels impossible to find that one key piece of information you need. Okay. So, what if you had an AI that hadn't read the whole internet? Instead, it's meticulously studied only the documents you gave it, the research papers, the case files, your project notes, an expert that is grounded entirely in your world. That's the whole idea behind Notebook LM. So, here's how we're going to break it all down. First, we'll talk about that problem of drowning in documents. Then, we'll dive into the source grounded AI that makes this tool tick. After that, we'll see how people are actually using it, run a much needed reality check, and finally look at what this all means for the future. All right, let's get into the nuts and bolts. What really makes Notebook LM different from say a regular chatbot? It all comes down to one core concept, being source grounded. The secret sauce here is a technology called retrieval augmented generation or just rag for short. Now, instead of just making up an answer from its giant brain, a rag system does something smarter. It first goes and searches your documents for the most relevant facts. Only then does it actually generate an answer using your stuff as its foundation. And this image really shows you what's going on. A standard model, you ask it a question and it just pulls an answer from its massive general knowledge. But Notebook LM takes this crucial extra step. It first looks at your sources, your research, your files, and then it puts together a response. It's basically a closed universe analysis tool, which is super powerful. And this gets us to the main benefit, which attorney Ernest Spencson sums up perfectly. You get fewer hallucinations. You know those times AI just confidently makes stuff up. And because every single answer is tied back to a specific source with a citation, you can check its work in seconds. For professionals, that level of trust is a total game. Okay, so the theory sounds great, but how does this actually play out for people who are, you know, in the trenches doing research and analysis every day? Let's take a look. So meet PhD students Aer Atalai. For her, everything comes down to credibility. You just can't build a thesis on an AI that might be pulling from some random blog post. She calls Notebook LM her anchor because she knows every single insight comes directly from the academic papers she's already vetted. And this is where it gets really cool and practical. She can upload dozens of super dense scientific papers and just ask Notebook LM to organize them into a table like this one. It pulls out the key findings, the methods, and this is the golden part, the limitations and gaps in the research. A task that used to take weeks of painstaking reading can now be done in a matter of hours. It's incredible. Now, let's switch gears to the legal world. Someone came up with this fantastic metaphor for it. A small hammer for big document problems. See, it's not trying to be some super AI that replaces a lawyer. Not at all. It's a precise, focused tool for a very specific and very painful job, making sense of thousands of pages of case files. And the use cases here are seriously powerful. It can digest an entire litigation file and cut through what they call the paper fog. It can take a bunch of scattered emails and transcripts and stitch them into a story that actually makes sense. And for witness prep, it can turn a mountain of claims into a sharp, concise battle card for cross-examination where every single point is cited back to the evidence. So, what we're seeing is this clear workflow emerge for power users. You start by ingesting everything you've got. Then you explore it all with questions, capture the good stuff right from the chat, refine it with some smart prompts, and then you export it. This turns the whole thing from just a research tool into a full-on content creation pipeline. All right, it's really easy to get swept up in all the hype. So, let's just pump the brakes for a second and do a proper reality check. How does this thing actually perform when you put it under a microscope? and what are its real world limits? So, check this out. A really interesting study put Notebook LM head-to-head with its underlying model, Gemini, using very specific clinical questions. The results, Notebook LM was more accurate. It got 96% of the answers right compared to Gemini's 89%. That seems like a pretty clear win for the source grounded approach, doesn't it? Well, not so fast. Here's the twist. The researchers pointed out that for this specific test, that 7% difference wasn't actually statistically significant. And that brings up a really important question for simple fact-based questions. Is all that extra rag technology really giving you a big enough advantage? And then the plot thickens a little bit when you look at consistency. Both models were incredibly stable. They gave the exact same answer over 93% of the time. Now, on the surface, that sounds amazing. We want our tools to be reliable, right? But hold on. Is consistency always a good thing? Other researchers have pointed out that base models can sometimes be consistently incorrect? The key difference is if a rag model like notebook LM is wrong, it's because it misread a source that you can go and check. If a base model is wrong, it can be a lot harder to figure out why. And outside of the lab, real users have pointed out some of the practical trade-offs. Look, it's absolutely brilliant at retrieval and synthesis, but it's not a great all-purpose note-taking app. People have noted that it's missing some key organization features. And until recently, it didn't even save your chat history, which made it feel a little incomplete. So, with all those strengths and weaknesses in mind, where is this technology headed? What does the future actually look like for Notebook LM and tools like it? Well, things are moving fast. It's becoming so much more than just a research assistant with new features letting you ingest entire ebooks, create video summaries, and even generate and export slide decks straight to PowerPoint. It's becoming a full stack content machine. And this really hints at Google's bigger strategy. They're starting to build Notebook LM's powers right into Gemini itself. This is huge because it bridges the gap between two very different ways of thinking. that open web anything is possible brainstorming you do in a chatbot and the focused evidence-based analysis you do with your own private sources which brings us to our final big question as we see more of these specialized tools maybe the future isn't about one giant all- knowing super AI after all maybe just maybe the future of knowledge work belongs to a whole toolbox full of expert small hammers each one designed to do its job perfectly what do you think now Again coming to downloading there are limits for the free version and there are limits for the ultra version as well. So here you go this is the entire video created by notebook LM. So there you go this entire presentation or whatever things that we have generated which includes a video audio slide mind map reports flashcard quiz infographic data table it's just in your fingers with just one click and that's the specialtity of notebook LM. So now that you have seen everything in action on Notebook LM Ultra, from faster processing and watermark free exports to those beautiful long slide decks, let's put all this into perspective. Every version of Notebook LM serves a purpose. It really depends on who you are and what kind of content you're creating. The free plan is ideal for students, hobbyist, or even early educators. Basically, anyone working on smaller research or study projects. If your goal is to make quick summaries, short notes or two to three video outlines, it does the perfect job. It's great space to start experimenting and understanding how notebook LM works. But it also comes with limits around 50 sources per notebook, daily overview caps and those watermark exports. It's good for learning, not built for scale. Then there is plus or pro, the middle tire for professionals with steady workloads. This plan fits freelancers, solo educators, or even creators, producing mid-scale tutorials, and ongoing video series. You're looking at roughly 100 plus sources per notebook, about 20 overviews a day, and faster generation with cleaner exports. It's worth it if you're regularly hitting free plan limits. For over $20 per month, you get a workflow that doesn't slow your work when ideas are flowing. And finally, what you have been watching is the ultra version. This is a enterprise tier design for high volume creators and fulltime teams. Here's where everything changes. Smarter reasoning powered by Gemini 3 ultra watermark free outputs, ultimate slide decks, and 3x faster generation speeds even during peak hours. If you're producing daily content, managing large notebooks with hundreds of sources, or even running collaborative courses, builds, and reports, Ultra simply makes sense. It's the difference between waiting for results and instantly creating, refining, and publishing professional material. At $250 per month, it's definitely premium, but for creators who rely on AI everyday, it's not a cost, it's an ROI multiplier. So, that was it for this video on Notebook LM. If you like this video, do hit the like button and subscribe to Simply Learn for more such content. If you have any doubts or queries, please let us know in the comment section below and our team of experts will get back to you as soon as possible. Thank you and keep learning with simply learn.