#01 AI tools | How to use Google's NotebookLM AI - Full Tutorial | 19 Minutes in Tamil

Key Takeaways

Welcome back to another session with your AA coach John. particular document discussion on the particular for the data science machine learning low tools. No code data science machine learning for Monday episode. So in the particular episode Monday to Fridays teaching Monday to Friday. Then I would like every week Saturday real time story one How to build and sell a agent beginner almost 4 hours already. Anyway, YouTube notebook. Okay. Notebook open [Music] mobile demo notebook is a powered research and writing assistant that work best with the sources You type of sources of data research assistant. Research assistant powered research and writing assistant. Create a new notebook. Add sources. Sources let notebook LM base its response on the information that matters most to you. Okay, fine. Yeah, Mark, audio meaningful dat datyp. of sources where this Google can take different sources multiple sources in the particular window in this particular particular audio overview. Mind map right because it's going to be video building and selling a agent beginner's guide the YouTube source title how to The YouTube video source titled how to build and sell agents ultimate guide by in the particular person provides a comprehensive overview. Second question, I just wanted to know what he talked about to explain to a seventh studying student. the YouTube video the source of document. Okay. An expert who taught himself how to build how everything here is here is a breakdown of what he talks about explain to someone. Okay. What are a a agents? An agent is a like a digital worker or a digital employee that can understand how do a agents work? The three ingredients for building. Okay. document. So, but in the notebook topic right for example machine learning machine learning topic machine learning is type of algorithms supervised learning, unsupervised learning, reinforcement learning, semi-supervised learnings, self-supervised learning, different types of machine learning learning connecting dots. Mind building selling agents introduction and motivation foundational different modules end to end agents monetizing and a agents building skills conclusion introduction motation author's background success. Why agents of the next big things? Okay. Why agents target audience aspiring entrepreneurs business owners employ? Okay. Okay. Okay. Done. in the agents foundations and understanding of agents. What is an agent? How agents work? Five key points. Agent in a action customer support. Three ingredients. Okay. Wonderful. What is an agent? Understand? Discuss what these sources say about digital worker in the large context of what is an agent. foreign. Okay. What is an agent? You're able to see So first [Music] mind map concept. Okay. So notebook Number one. Step number two. Okay. Okay. particular topic. So mind concept. Okay. Deep dive conversation. Create an audio overview in more languages. Multiple languages. So top Conversation model to just see me. All right. Close to four minutes because I'm just using this particular tool on a regular basis. full. Welcome to the deep dive. Today we're going to get into something I think is really transforming how work gets done. You know, AI, but not just AI as some uh far-off idea. We're talking about practical tools, right? Exactly. It's about making it accessible. Yeah. And our focus today is NA. It's this open source automation tools all these AI wonderful interactive beta welcome to the deep dive really transform done you know AI but not just AI as some uh faroff idea we're talking about practical tools right now exactly it's about making it accessible yeah and AR connects all the AI services together, right? Think of it as a hub and we're going to unpack how its workflows can really unlock some surprising things strategic. Oh, wait. Someone wants to join. Hey, go for it. Yeah, I want to join your discussion. So, basically, you're talking about this NAT tool and mastering this AI automation. I have a basic question here. I just wanted to understand what is this NAT and what would be this future scope of it. I just wanted to join the discussion. I understand that you will be speaking a lot of this particular topic. You both are experts here. But quickly I just want to know what is the future scope of this NH and what are the new opportunities which is going to grow uh for the young people who are just going to learn this a concepts. Oh we love it when you jump in. That's fantastic. Welcome. Great question. You're absolutely right. We're talking NADN and your question about its future scope and opportunities for young people is super important. It really is. What's fascinating here is that NADN isn't just about current automation. It's building skills for the future. Exactly. Because naden allows you to essentially orchestrate these AI agents and design complex workloads. Yes, the future scope for Oh yeah, let's hear it. One minute. You said about something like orchestration. That is a new term for me. Can you explain what is this orchestration? That's a great follow-up question. Orchestration in this context is really about managing and coordinating multiple AI agents. Think of it like a conductor leading an orchestra. Exactly. Each musician or in our case each AI agent or service has a specific role like one AI might generate an idea another writes a script and another creates a video just like we'll discuss with content creation. So orchestration mobile. 42 minutes 42 minutes. So, it's a kind of personal tutor for you. for join. So notebookant topic. So definitely a is your helpful friend. I would like them help them know let them also try to learn and master this particular see you tomorrow. This is your a John. Let's make a simplified. See you all in the next episode. Bye. Cheers. [Music]