# How I Use Obsidian Zettelkasten to Study AI & Tech Topics ![](https://i.ytimg.com/vi/L2z7j7Jho4E/maxresdefault.jpg) ## Processing Notes on Artificial Intelligence - The process of creating [[Zettelkasten]] notes is demonstrated using a practical example of studying [[Artificial intelligence | artificial intelligence]] from a book, with the goal of showing how notes are processed and implemented into the system [(00:00:10)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=10s). - The book being read is used to take notes, which are initially written in a physical notebook and later processed into a digital format using [[Obsidian (software) | Obsidian]] [(00:00:42)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=42s). - The importance of driving home key concepts of artificial intelligence is emphasized, and the notes taken from the book are used to illustrate this process [(00:01:02)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=62s). - Normally, notes are processed on the same day or the next day, but due to a hectic schedule, there has been a backlog of notes to process [(00:01:43)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=103s). ## Capturing the First Thought - The notes are processed using Obsidian, starting with the first scribble, which is about Ray Kurzweil's definition of [[Technological singularity | Singularity]] [(00:02:01)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=121s). - The note is created in [[Obsidian (software) | Obsidian]], and the process of capturing the first thought is demonstrated, with the goal of creating modular nodes that can be used in the [[Zettelkasten]] system [(00:02:31)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=151s). - The note is named "Ray Kurzweil's definition of Singularity," and the process of writing down the note in one's own words is emphasized, even if it contains similar words to the original text [(00:03:02)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=182s). - The original quote from the book is compared to the note written in one's own words, highlighting the importance of processing information in one's own words [(00:04:57)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=297s). - The process of putting information into one's own words solidifies thinking and is a key aspect of the Zettelkasten method, which involves more than just copying information into a system [(00:05:49)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=349s). - A note is created by rewriting information in one's own words, making it valuable for later use in writing, and can be stitched together with other notes to form an essay [(00:06:14)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=374s). ## Connecting Related Ideas - Including a reference to the original source, such as a page number, allows for easy location of the information later [(00:06:33)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=393s). - A link to a related note, such as "[[Technological singularity | Singularity]]," can be created to connect related ideas and make them easily accessible [(00:07:11)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=431s). - Starting with definitions is essential when studying a new topic, such as [[Artificial intelligence | artificial intelligence]], and provides a foundation for further learning [(00:07:42)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=462s). ## Organizing Information with Index Notes - Using index notes, also known as maps of content, helps to organize and structure information, making it easily searchable [(00:08:44)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=524s). - Creating a new heading, such as "definitions," and adding relevant information, like the definition of artificial intelligence, helps to build a comprehensive note [(00:09:03)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=543s). - Adding keywords, such as "AI," makes the note more searchable and easier to find [(00:09:14)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=554s). ## Creating Notes from Daily Notes - Creating notes from daily notes and processing them later helps to structure and connect ideas [(00:09:28)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=568s). - Reflecting on written notes and breaking them down into smaller, more manageable pieces helps to clarify thinking and identify areas for further exploration [(00:10:53)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=653s). - The importance of processing notes on the same day or the day after they are taken is emphasized, as it helps to remember the context, which may be lost over time [(00:11:08)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=668s). ## John McCarthy and the Term "Artificial Intelligence" - [[John McCarthy (computer scientist) | John McCarthy]] is credited with coining the term "[[Artificial intelligence | Artificial Intelligence]]" and organizing a two-month, 10-man study of AI in the summer of 1956 [(00:11:41)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=701s). - McCarthy's invention of the term "Artificial Intelligence" is noted, and it is mentioned that he later founded the Stanford AI project in the early 1960s [(00:12:40)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=760s). - A note about McCarthy might be created, but it is not necessary in this case, as the focus is on capturing who invented the term "Artificial Intelligence" [(00:12:52)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=772s). ## Defining Artificial Intelligence - The definition of AI is provided, quoting a committee of prominent researchers who defined the field as "a branch of computer science that studies the properties of intelligence by synthesizing intelligence" [(00:13:57)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=837s). - The use of quotes is discussed, and it is noted that while they should be used sparingly, it is sometimes necessary to use the specific wording of a definition, as in this case [(00:15:16)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=916s). - The context of the definition is provided, mentioning that it comes from a recent report on the current state of AI by a committee of prominent researchers [(00:16:49)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1009s). - A report by a study committee of prominent researchers defines the field of [[Artificial intelligence | artificial intelligence]], which is a branch of computer science that studies the properties of intelligence by synthesizing intelligence [(00:16:54)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1014s). - The report is from the 100e study on artificial intelligence, and the definition is found in chapter "Definitions and Getting On With It" on page six [(00:18:16)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1096s). ## The Zettelkasten Method and Deep Learning - The definition of artificial intelligence is written in the note in the user's own words, reflecting on the definition itself, where it came from, and how it was phrased [(00:20:31)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1231s). - The [[Zettelkasten]] method is a vehicle to enable deep engagement with the material, allowing for 10 times faster learning than peers, and it involves taking the time to think through the material [(00:21:11)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1271s). - The user has another note that defines [[Artificial intelligence | artificial intelligence]] as a field with the goal of creating machines with intelligence, which is a concise and clear definition of the term [(00:22:15)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1335s). - The user also notes that artificial intelligence is often inaccurately referred to as [[Deep learning | deep learning]] in popular media, but AI is a broad field that includes many approaches, with deep learning being only one sub-approach [(00:23:40)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1420s). - Deep learning is a method among many in the field of machine learning, a sub-field of AI, in which machines learn from data or their own experiences [(00:24:11)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1451s). ## Distinguishing AI, Deep Learning, and Machine Learning - AI is a field with the goal of creating machines with intelligence, and this definition is broken down for clarity [(00:25:01)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1501s). - The goal of the AI field is to create machines with intelligence, and this is a key concept to understand [(00:25:32)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1532s). - In popular media, the term AI has become synonymous with [[Deep learning | deep learning]], which is an unfortunate inaccuracy [(00:26:06)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1566s). - Deep learning is only one approach or method among many in the field of machine learning, which is a subfield of AI [(00:28:30)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1710s). - Deep learning is a type of [[Artificial intelligence | artificial intelligence]], but it is not AI itself, and it is a method that is part of machine learning [(00:29:20)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1760s). - Machine learning is a subfield of AI in which machines learn from data or from their own experiences, and this concept will be added as a new note and index in the system [(00:30:11)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1811s). ## Writing Notes for Publication and Avoiding Copyright Infringement - When writing notes in a [[Zettelkasten]], it's essential to write as if they are going to be published, and to carefully balance attributing meaning to the original author while avoiding copyright infringement [(00:27:32)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1652s). - The author's words can be paraphrased and rewritten in one's own words, and this process helps to clarify understanding and create original content [(00:25:15)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1515s). - The concept of AI and its relationship to [[Deep learning | deep learning]] and machine learning are important distinctions to make, and understanding these concepts is crucial for clarity in the field [(00:25:55)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1555s). ## Refining Notes and Using Synonyms - When refining notes, using a thesaurus or AI to find synonyms for words can be helpful, especially when [[English language | English]] is not the first language, to rephrase and better understand concepts like "subfield" or "branch of a domain within AI" [(00:31:45)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1905s). - A subfield of AI is a branch within AI, and machine learning is a branch of AI where machines learn from their own data or experiences [(00:32:21)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=1941s). - Refining notes by rephrasing and reflecting on concepts helps to better understand and remember them, making it essential to take time and deeply reflect on the information [(00:33:22)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2002s). ## Machine Learning as a Subfield of AI - Machine learning is a type of [[Artificial intelligence | artificial intelligence]] and can be a separate note, with its definition being a branch of AI where machines learn from their own data or experiences [(00:33:53)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2033s). - The relationship between machine learning and AI is reflected in the notes, showing that machine learning is a subfield of AI [(00:34:36)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2076s). ## The Concept of "Experience" in Machine Learning - The author's use of the word "experiences" in quotes implies that machines' experiences are not the same as human experiences, but rather statistical pattern recognition and input data points [(00:36:05)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2165s). - According to [[Claude (language model) | Claude]], the quotation marks around "experiences" signal that the term is an analogy or approximation, and machines' learning is fundamentally different from human learning [(00:37:12)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2232s). - Machines' experiences are not conscious or phenomenological, but rather input data points, training examples, and recorded interactions or outcomes [(00:37:51)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2271s). - The use of quotation marks around "experiences" serves as a kind of epistemological humility, acknowledging that terms from human cognition and consciousness are being borrowed to describe mathematical and computational processes [(00:38:11)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2291s). - The distinction between actual knowledge and processing information is important in AI ethics and philosophy of mind discussions, as AI systems can process information and adjust their behavior based on data, but it's still unclear if they can have genuine experiences or consciousness like biological entities [(00:38:40)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2320s). ## Using AI as a Mentor and Avoiding Plagiarism - [[Claude (language model) | Claude]], an AI system, is used as a kind of mentor or teacher to learn about AI, and its responses are often used as notes, with proper attribution, to avoid copying text straight from AI [(00:39:12)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2352s). - The book "[[Artificial Intelligence: A Guide for Thinking Humans]]" puts "learn" and "experiences" in quotation marks to signal that machines do not actually learn or experience, but rather gain more accurate statistical data through machine learning [(00:40:01)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2401s). - The author rephrases the AI text to create their own notes, acknowledging that machines do not actually learn, but rather recognize statistical patterns [(00:41:13)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2473s). - The notes are then used as data for later reference, and the link to the original AI response is included for easy access [(00:42:45)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2565s). ## Structuring Notes and Creating Input Nodes - The notes are structured by creating input nodes, such as a note representing the book "[[Artificial intelligence | Artificial Intelligence]]: A Guide for Thinking Humans", which is moved to the "input" folder and linked to other relevant notes [(00:43:36)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2616s). - The notes are then turned into a bulleted list for easier reading and organization [(00:44:32)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2672s). ## Building a Network of Interconnected Notes - The goal of this note-taking system is to create a network of interconnected notes that can be easily referenced and built upon in the future [(00:44:42)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2682s). - The note-taking system allows for tracking the origin of notes, enabling the user to go back to the definition of a term, such as artificial intelligence, and view its backlinks to see where it comes from [(00:44:57)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2697s). - The local graph feature provides a visual representation of linked notes, showing how they are connected and allowing the user to see the creation date of a note and other related notes [(00:45:09)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2709s). - The index node feature groups related notes together, such as those related to [[Artificial intelligence | artificial intelligence]], making it easier to see the connections between them [(00:45:40)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2740s). - The Excalidraw plugin provides an additional way to visualize note connections, making it clearer how notes are related and which notes spawned from others [(00:46:10)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2770s). - The plugin also shows the parent notes of a particular note, such as the daily note and book note, and how they are connected to other notes [(00:46:25)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2785s). - The system allows for tracking the origin of a book note, including the date it was started, and seeing how it relates to other notes [(00:47:16)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2836s). - The visual exploration feature enables the user to see which notes are related to each other and expand the number of branches to explore further connections [(00:48:17)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2897s). - The system is useful for creating a network of connected notes on a particular topic, such as artificial intelligence, and for visually exploring these connections [(00:48:34)](https://www.youtube.com/watch?v=L2z7j7Jho4E&t=2914s).