Boost Your Learning Efficiency with AI Tools

Learn Anything Faster: Save 80% of Your Time with Gemini Deep Research & Obsidian [Guide & Setup]

Estimated read time: 1:20

Summary

In this guide, Tony Huang dives into efficient learning techniques using AI tools like Google Gemini Deep Research and Obsidian. By leveraging these technologies, users can dramatically cut down their study time while creating structured and comprehensive learning maps. The process involves generating detailed research plans and integrating them into a personalized knowledge graph using Obsidian, which helps in understanding and retaining new information quickly and effectively.

Highlights

AI-powered knowledge graphs are game-changers for learning! 🌟
Google Gemini designs a research and learning roadmap just for you! 🎯
Obsidian supports creating networked notes for deeper understanding. 🧠
Tony demonstrates making complex topics fun and fast to learn. 🚀
The setup helps transform study routines with technology and efficiency. 💻

Key Takeaways

Combine AI tools like Google Gemini and Obsidian for rapid learning! 🤓
Save time by creating automatic learning roadmaps and knowledge graphs. ⏰
AI performs deep research and provides structured outputs for easier comprehension. 📚
Obsidian allows you to create personalized knowledge connections. 🔗
This method turns complex research into a fun, manageable task! 🎢

Overview

Tony Huang introduces a revolutionary way to enhance learning through AI tools like Google Gemini and Obsidian. These tools are perfect for anyone looking to save time and supercharge their study process by creating a comprehensive learning guide in minutes instead of days or weeks. The focus is on using AI to perform deep research, create detailed reports, and establish a structured roadmap for learning any new topic.

Tony’s method involves using Google Gemini's deep research feature to gather relevant materials quickly. This method eliminates the tedious task of manual information searching, allowing users to focus more on understanding and comprehending new knowledge instead. The AI provides a cohesive study plan and structured roadmap, tailored to the user's specific learning needs.

With Obsidian, Tony shows how you can build a personal knowledge graph by organizing note cards based on the AI's roadmap. This creates a dynamic learning environment where connections between different concepts are easily visualized. The result is a more engaging and efficient learning experience, perfect for tackling complex subjects with confidence and flair.

Chapters

00:00 - 00:30: Introduction to Obsidian Knowledge Graph The chapter introduces the Obsidian Knowledge Graph, an AI-generated tool. It highlights that the Knowledge Graph includes not just a visual map but also a clearly explained learning roadmap. This roadmap is sectioned by key concepts, with various articles and reference links provided for further reading. Additionally, the Knowledge Graph offers an index page designed to help users complete notes on each key concept.
00:30 - 01:00: Efficiency with Gemini Deep Research & Obsidian Setup In this chapter, Tony, an engineer and tech enthusiast, discusses efficient methods for learning new topics using tools like Gemini Deep Research and Obsidian. He emphasizes simplicity and efficiency, aiming to provide viewers with a learning roadmap within 10 minutes. Tony acknowledges the common use of GPT prompt tricks but introduces a structured approach to serious topic research and learning without relying on applications such as Obsidian.
01:00 - 01:30: Combining Google Gemini and Obsidian for Learning This chapter discusses the synergy between Google Gemini and Obsidian for self-learning. It highlights two major components that enhance learning efficiency: using Google Gemini for topic research and creating a knowledge graph in Obsidian with AI support. These tools collectively facilitate faster and more efficient knowledge acquisition. The chapter begins with a fundamental approach for learning any topic from scratch.
01:30 - 02:00: Fast Topic Research with Google Deep Research In this chapter titled 'Fast Topic Research with Google Deep Research', we dive into the challenges of conducting research for learning materials. It often involves piecing together fragmented information and can take extensive time—potentially days or weeks—to compile a comprehensive study guide. However, this chapter introduces a solution to expedite this process: 'Google Deep Research'. The concept of deep research is presented as a powerful function within the Google Gemini application that significantly reduces the time needed for research, potentially achieving results in just minutes.
02:00 - 02:30: How Google Gemini's Deep Research Works The chapter delves into how traditional search engines work and introduces a concept of advanced AI-driven research methodology. It begins with the basics of how search engines like Google operate by finding and presenting relevant websites and information based on user queries. The discussion progresses to modern AI search engines, such as Perplexity, which not only identify relevant content but also engage with it to derive meaningful insights. The chapter suggests envisioning a future where intelligent, AI-powered research assistants could play a crucial role in enhancing information retrieval and comprehension.
02:30 - 03:00: Creating Research Plans with Google Gemini The chapter introduces the concept of using Google Gemini, an AI agent, to enhance the process of information searching and research planning. Instead of solely relying on search engines like Google or Perplexity, it emphasizes the importance of planning how to conduct research more effectively. When a user poses a question, such as 'What is artificial intelligence?', Google Gemini first creates a research plan. This plan is then reviewed by the user, referred to as the 'master', to determine its suitability and effectiveness for their needs.
03:00 - 03:30: Conducting Online Research with AI The chapter discusses how to effectively conduct online research using AI tools. It highlights the ease of using AI to streamline the research process: formulating a research plan, searching for information online, reading materials, and compiling a report for review. The text provides a hypothetical example indicating the simplicity of the process by using SpaceX's Starship as a topic of interest. Readers are instructed on initiating a query, such as wanting to know everything about the SpaceX Starship. This illustrates the ability of AI to facilitate comprehensive research inquiries.
03:30 - 04:00: Generating Learning Roadmaps with Google Gemini The chapter discusses how AI is considering a research strategy that could enhance learning. It focuses on gathering information about the SpaceX Starship program, its objectives, and current progress. The AI's first research target is to locate articles and news reports on recent developments related to the Starship, including test flights and future missions.
04:00 - 05:00: Starship Research Example Using Google Gemini The chapter titled 'Starship Research Example Using Google Gemini' discusses the technical specifications of the Starship, including its size and capabilities. It explores potential applications, environmental impacts, and addresses the challenges and risks associated with it. The chapter also includes an AI-generated plan for Starship research, which readers can edit to better suit their needs.
05:00 - 06:00: Understanding Starship with AI Research This chapter discusses recent changes in the research plan concerning Elon Musk's vision for the Starship. The conversation indicates an intent to edit or update the plan, suggesting ongoing developments and considerations in AI research relating to SpaceX's Starship project.
06:00 - 06:30: Importing Research Data into Obsidian This chapter discusses the process of importing research data into the note-taking app, Obsidian. It begins by mentioning updates on Elon Musk's vision for the Starship project, which is an unrelated but intriguing segue likely used to demonstrate the breadth of information that can be incorporated into Obsidian. The main focus seems to be on utilizing tools, such as Google Gemini, to perform deep research online, automatically searching and reading data from the internet to be subsequently organized and presented within Obsidian.
06:30 - 07:00: Using Obsidian for Personalized Knowledge Graphs This chapter discusses the use of Obsidian, a tool that can be used to create personalized knowledge graphs. It highlights the tool's capability to analyze large volumes of content, such as articles up to 60 pages or more, to generate comprehensive reports. The tool is positioned as ideal for anyone looking to explore topics of interest in-depth. The process involves researching and analyzing relevant content and compiling it into a report that the user can review at their convenience, indicating that the tool can work autonomously to some extent.
07:00 - 08:00: Automating Note-taking with AI In this chapter titled 'Automating Note-taking with AI', the focus is on utilizing AI to streamline the process of taking notes. The discussion includes an example on how to create a learning map using AI, specifically through the use of a large language model. The prompt entails asking the AI to create a learning roadmap based on a given topic, demonstrating how AI can generate detailed outlines and insights about subjects like large language models. The example highlights the efficiency of AI in producing structured learning material or research reports, reinforcing the theme of automation in educational or research contexts.
08:00 - 09:00: Creating Index Notes and Backlinks in Obsidian This chapter focuses on creating index notes and backlinks in Obsidian, a note-taking app. It discusses developing a learning roadmap based on research findings, specifically focusing on AI applications. The learning roadmap is structured to guide users from basics to building AI applications. Important concepts to grasp are highlighted, and relevant articles and YouTube videos are suggested for further understanding and engagement with the material.
09:00 - 10:00: Finalizing the Learning Setup in Obsidian The chapter titled 'Finalizing the Learning Setup in Obsidian' appears to focus on concluding the process of setting up an educational structure within the Obsidian platform. It begins with an introduction to large language models provided by Google Cloud and YouTube, suggesting these are key resources within the setup. The transcript encourages readers to watch relevant videos as alternatives to reading articles, enhancing the learning experience. It then proceeds with checking the progress and completion of a report related to SpaceX's Starship, signaling a transition from theoretical learning to practical application, symbolized by the completion of the report.
10:00 - 10:30: Conclusion and AI Tools Review The chapter reviews Elon Musk's vision for space exploration, particularly focusing on Mars and the development of SpaceX's Starship. It highlights the recent developments and test flights of the Starship, specifically flights 5, 6, and 7. The chapter also touches upon upcoming missions, underscoring advancements and challenges in the pursuit of space travel.

Learn Anything Faster: Save 80% of Your Time with Gemini Deep Research & Obsidian [Guide & Setup] Transcription

00:00 - 00:30 okay this is an Obsidium Knowledge Graph automatically created by AI and the map is not the only thing you get we also have a clear learning road map clearly explained section by section with key Concepts and various articles and their reference links as well addition to that you will also have an index page that for you to complete the notes of each key Concepts
00:30 - 01:00 for me personally I cannot think of any other ways simpler than this for you to learn a new topic in this video let me show you the simple setups that could help you get the similar learning road map within 10 minutes Hi friends my name is Tony. I'm an a engineer and tech nerd enthusiastic in productivity hacks I guess you may have seen prompt tricks and tips to ask GPT to teach you something new but how about serious topic research searing and structured learning process with no applications like obsidian recently I found
01:00 - 01:30 that combining Google Gemini deep research and obsidian you can save loads of time to teach yourself any topic today's sharing will include two major parts that can help you learn anything faster topic research with Google Gemini building obsidian Knowledge Graph with AI in cursor okay if you want to learn anything from scratch the first thing you will do is
01:30 - 02:00 research relevant learning materials from online then trying to piece together various fragmented information to create your study guide this will take you days or even weeks of effort to research but what if I'm telling you that this can be done in minutes with Google Deep Research so what is deep research? Deep research is a function that supported in Google Gemini application
02:00 - 02:30 it is hidden below here okay let me explain in a slide so traditionally when we um search uh anything online and search engine like Google will help us search relevant website or if you use perplexity an AI search engine it will look for website and read relevant materials and picked up for you but that is only the start so imagine um that you have a smart research assistant that they
02:30 - 03:00 do not only use Google or Perplexity to complete their research they also plan how to do the job better so here comes the Deep research it is an AI agent in information searching so as a user you will ask a question say what is artificial intelligence then Google Gemini will create a plan first and you as the master will review the plan to see whether it is good for you or not
03:00 - 03:30 If you think the plan is good enough it will follow the research plan search online read the materials and write a report for you to review so let me show you how to do it say I would like to know everything about the Starship you can simply ask "I would like to know about Starship of spaceX..."
03:30 - 04:00 okay so currently the AI behind this is thinking of a research plan could help you better so oh so we find information about the SpaceX Starship program including its goals and current status so this is the first research Target then they will find articles and news report on recent Starship development including test flights and upcoming Mission then finding
04:00 - 04:30 information of the technical specs of Starship the size the capability and find information about potential applications as well and last but not the least the environmental impacts the potential challenges and risks associated with Starship as well so the AI create a plan for us if you don't like this plan you may be edit it as well
04:30 - 05:00 so I say I will like to edit the plan about so I would like to know about the Elon Mask's Vision on Starship as well all right so we have an updated the research plan so at the I think at the last re
05:00 - 05:30 at the last action point it added fin information about Elon Mask's vision on Starship the uh the six task above is the same all right okay now we can click the start so while the Google Gemini is doing deep research for us it will search online read all
05:30 - 06:00 the relevant articles and analyze the content then we'll get back to you a full report for you to review so seeing it's researching for 49 pages okay 60 Pages or even more so if you want to learn any area, any task, any topic you are interested in this is the perfect tool is that I will let you know when the resch sear is finished you can leave this chart in the meantime so okay
06:00 - 06:30 so let's have a quick look at the example I will use later so if you want to create a learning map from Google Deep Research this is the prompt I use if I want to learn what is large language model and how can I use large language model be AI explication would you please create a learning road map for me okay so under this prompt Gemini's task is not only create a research report but also
06:30 - 07:00 to write a learning road map for you based on the research result so at list a research plan for me then write this learning road map. It is called The Learning road map from Basics to building AI applications it was separate into sections introduction to large language model there are key Concepts you should know and the articles that it found relevant and you can definitely click the Articles including YouTube videos as well you see the videos
07:00 - 07:30 introduction to large language model Google cloud and YouTube let's click this see hello and welcome to introduction to large language mod great all right so if you don't want to read articles you can definitely check those videos later let's check whether our Starship report is completed okay it's really close great it has been completed okay let's check the report SpaceX Starship reaching
07:30 - 08:00 for the stars and Mars with Elon musk's Vision wow the title is attempting all right say Starship development and test fly um I will leave uh the link to this article below and you can definitely check this out so let's check how many sections it have Starship development and test flight recent development uh flight 5 6 7 and upcoming missions as well so take an example um SpaceX are
08:00 - 08:30 outlined several key missions for Starship: Orbit Refueling Demonstration wow Uncruited Lunar Demo wow W this is exciting too all right and you will have uh those specs of Starship and uh internal designs structure features a lot lot of detailed information all of this information was actually
08:30 - 09:00 not make up from um Google's Gemini. it was from reliable sources you can take a quick look at this they are Wikipedias they have informations from Starship official website they also use uh Reddit as information Resource as well and of course we got YouTube videos and NASA report so I I
09:00 - 09:30 would say um if I when I was a student if I have a tool like this I would definitely have higher marks of my assignment because this is amazing you have those multimedia resources from different uh information source and combine together to create you this single report in just few minutes additionally if you have Google uh drive you can open in uh docs and you can edit you can export
09:30 - 10:00 the report as well uh since obsidian use Markdown format we can you can choose download with markdown okay it is downloaded let's open it and we have markdown file okay I have already import the learning road map as a markdown file to the obsidian as you can see that we already have a well researched learning road map but having a road map is only the beginning that's
10:00 - 10:30 why we need to use obsidian to help us to learn so the major reason why I love obsidian is that you can write your note cards each time by focusing on one concept then you can easily find and build connections between your new nodes and existing one with time you will have your own personalized Knowledge Graph like this on any topic you are interested in this idea was made
10:30 - 11:00 Popular by book "How to Take Smart Notes": Learning by Writing there are loads of great videos on YouTube right now talking about this so I will not explain that in details but focusing on one paino SLOW yes it works but it will take you a lot of time to build it up and sometimes when you are facing a sometimes when you are facing a strange topic or an area you will feel very uncomfortable
11:00 - 11:30 but you just don't know where to start the best way is to buying a textbook in our case what we need to do is to extract those knowledge point from the learning road map and make each one into note cards for us to write learning notes now this process can be fully automated by AI okay now we use cursor to open up obsidian file folders Regarding why and how we use use cursor
11:30 - 12:00 to operate obsidian files you can refer to the link below you can see that this is the markdown file from obsidian and uh for each section we will have an Index Note introduce the concept and provide the links to the note card we need to fill but how can we create it automatically this is the part we need to involve AI all right so the process is very simple it only involves two steps the first step is to create index notes and the second step is to create a back
12:00 - 12:30 link from index noes to the road map what I will do here is that I will clean I will delete all the files and remove those back links okay uh now now we only have one road map nodes um in my obsidian
12:30 - 13:00 folder let's use my prompt to try again this is a learning road map report I need you to do the following step one based on the learning road map create a list of markdown files for each topic for each topic file write an introduction and a list of knowledge Points each knowledge points title should be written in double square bracket uh you can simply use cloud Sonet 3.5 then
13:00 - 13:30 submit okay now we have an AI is creating each note files for you okay we have the ethical part the introduction part this is the file created by AI okay it has
13:30 - 14:00 been completed we already have those uh notes created with introduction and uh note card link listed inside uh what you need to do is simply accept all right you already have those files the next step is to add a back link on the road map file so we can use it conveniently this is the prompt add your created file name list in road map file place them under each topic
14:00 - 14:30 related remember use double pret to quote the file name okay submit let's see how it works okay it seems that it got run to create new file for me no worries let's update the prompt all right let's submit again so in this case you will
14:30 - 15:00 click continue and revert so it will undo the previous task AI agent did and try again all right it is working great it even add an emoji here related detail notes cool good job so what
15:00 - 15:30 you do accept it and everything is done so this can be down in couple of minutes let's track the obsidian file see how it goes in obsidian this is the original node llm learning road map and uh here's the link edit we can jump to the index note where uh it introduced the concept here and have all those key concept knowledge for you to fulfill we can try our graph view as well so this
15:30 - 16:00 graph view only uses notes in my notes folder so what I do I will move those index notes into notes see how it goes great we have our road map now if you want to learn any New Concept about the large language model you could have a quick look around that if you have read something about testing autom you could simply click it and write your learning notes Here step by step
16:00 - 16:30 with a clear road map you can learn anything faster okay this is today's sharing so we do an AI deep research with Google Gemini then we use cursor AI to build obsidian Knowledge Graph thank you guys for your time if you like my video please hit the Subscribe button and click the thumbs up if you don't like tell me how to improve that thank you very much for the time