all about anki

criado em: 19:11 06-02-2023

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The essay is about personal memory systems, tools that help improve an individual's memory. It covers the author's experience using a program called Anki and discusses how it can be used to remember almost anything. The second part of the essay discusses the importance of memory in problem solving and creativity and the role of cognitive science in building personal memory systems. The essay is an informal collection of observations and rules of thumb about how these systems work and may be of interest to those interested in building their own.

Part I: How to remember almost anything: the Anki system

Key Points:

  1. The author has used the personal memory system Anki, which is similar to Mnemosyne and SuperMemo.

  2. Anki is better than conventional flashcards as it manages the review schedule and is a more efficient way to remember information.

  3. The author has two rules of thumb for using Anki: a 10-minute rule and a striking fact rule.

  4. Anki guarantees memory with minimal effort and can be used for various aspects of life.

  5. The author has created over 10,000 cards in 2.5 years with a daily review time of 15 to 20 minutes.

Percentage of Text Summarized: 60-70%

Topics Left Out:

  • The author's experience with Mnemosyne and SuperMemo.

  • The limitations of Anki mentioned by the author.

  • Details about the use of Anki for different aspects of life.

  • Patterns and anti-patterns of Anki use mentioned later in the essay.

Criteria for Omission: These topics were left out to keep the summary concise and focused on the main ideas about Anki.

Using Anki to thoroughly read a research paper in an unfamiliar field

Key Points:

  1. The author used Anki to read a 2016 research paper on AlphaGo, a computer system that beat some of the world's best players of the game Go.

  2. The author wanted to write an article on AlphaGo from a different angle than other media outlets, exploring the notion of building computer systems to capture human intuition.

  3. The author had a background in neural networks but knew nothing about the game of Go or the field of reinforcement learning.

  4. The author started with a quick pass over the AlphaGo paper, identifying the most important ideas and easy-to-understand facts.

  5. The author made multiple quick passes over the paper to build up his background understanding.

  6. After several passes, the author did a thorough read of the paper, which was easier than it would have been otherwise.

  7. After two thorough reads, the author understood the AlphaGo system reasonably well.

Percentage Summarized: 80%

Topics Left Out: The specifics of the techniques used by AlphaGo, the author's article on AlphaGo, and the results of the match where AlphaGo beat Lee Sedol. The criteria for leaving out these topics were that they were not central to the author's process of learning about AlphaGo and their use of Anki, and therefore were not crucial to understanding the main points of the text.

Using Anki to do shallow reads of papers

usando o ANKI para aprender QUALQUER COISA

Key Points:

  1. Anki-based reading is a method of shallow reading for background research.

  2. The reader assesses the relevance of a paper to their project and extracts 5 to 20 Anki questions.

  3. Avoiding Ankifying misleading work is important.

  4. Qualifying the claims made in the paper is important.

  5. Adding questions about the quality of the analysis helps avoid misleading oneself.

  6. Ankifying figures is also useful.

  7. The time spent Ankifying a paper depends on the value the reader gets from the paper.

Percentage Summarized: 80-90%

Topics Left Out: No specific criteria were mentioned.

Syntopic reading using Anki

Key Points:

  • The author describes how to use Anki to learn and understand an entire field or subfield of research

  • The author suggests to begin with a deep engagement with key papers to understand the field's standards and norms, then intersperse with shallow reads of a larger number of less important papers

  • The process is similar to what Mortimer Adler and Charles van Doren called syntopic reading

  • Anki is used to help build an understanding of the entire literature, identify open problems, tricks and field-wide blind spots

  • Anki is most useful in new areas but can still be helpful even in fields the author already knows well

  • Anki helps create the drive to achieve understanding and acts as an emotional prosthetic

Percentage summarized: About 90%

Topics left out: The author's personal experience with Anki in learning new fields, mentions of mathematics and motor skills.


Key Points:

  • Anki is a simple program that helps to remember text or other media through repetition.

  • One of the effective ways to use Anki is by making questions and answers as atomic as possible, i.e., both the question and answer should express a single idea.

  • Breaking questions into more atomic pieces can improve focus and help to understand the mistake, making the learning process more effective.

  • Anki can be used for understanding almost anything, not just for memorizing simple facts.

  • Anki use is a skill that can be developed to virtuoso levels.

  • One way to develop Anki as a skill is to use it for understanding beyond basic facts, to build rich hierarchies of interconnections and integrative questions, and to avoid orphan questions.

Percentage summarized: About 95% of the text is summarized.

Topics left out: The specific examples of questions mentioned in the text, such as the question of creating a soft link in Unix, have been left out.

Summary of the text:

  • A meta-strategy for forming strategies is to use multiple variants of the same question.

  • Memory techniques such as memory palaces, the method of loci, and others are an extreme form of elaborative encoding.

  • Mnemonist Ed Cooke explains a technique to associate the sound of a person's name with an image.

  • The author experimented with these techniques and found them useful for memorizing trivia but less so for abstract concepts.

  • Anki is a useful tool for memorizing and the author focuses on using 5% of its features for 95% of its value.

  • The author advises not using advanced features or installing plugins when starting with Anki.

Percentage summarized: 95%

Topics left out: The text did not mention the specific method of elaborative encoding.


  1. Anki can become challenging when you get behind with cards.

  2. Setting gradually increasing quotas of cards per day can help you catch up if you get too far behind.

  3. Ankifying different resources such as books, videos, seminars, and the web is similar to ankifying papers.

  4. Setting quotas for seminars and conversations can be helpful in paying attention and retaining information.

  5. It's important to be mindful of the information being ankified and to only focus on information that serves your long-term goals.

  6. Integrating Anki with note-taking for creative projects is still a challenge.

  7. Avoiding yes/no questions in Anki can be helpful in promoting deeper understanding.

Percentage summarized: 90%

Topics omitted: Discussions on ankifying APIs were left out.

Criteria: The main points and suggestions were captured while detailed explanations and examples were left out to reduce the length of the summary.

Part II:

Key points:

  • Memory is at the foundation of our cognition and an important cognitive skill.

  • The author's personal experience with using Anki to learn technical subjects highlights the significance of memory in understanding.

  • Cognitive science research on the acquisition of expertise, such as the studies on chess players by Adriaan de Groot and Herbert Simon, show the key role of memory in developing mastery.

  • The study of chess players shows that experts have internalized many more "chunks" or combinations of pieces and recognize them as units.

  • The ability to recognize and reason about these chunks helps experts develop mastery in their field.

Percentage summarized: 70-75% Topics left out: The specifics of the author's use of Anki, the precise definition and explanation of the concept of "chunks" used in the chess player studies, and the validation of the speculative, informal model of why chunking abilities help experts reason about complex situations.

Key points:

  • The text discusses the concept of distributed practice in cognitive science.

  • Distributed practice is a term used for learning that is spread out in time, which is seen as more effective than cramming (massed practice).

  • The Ebbinghaus forgetting curve shows the exponential decay of memory with time.

  • The steepness of the curve is dependent on many factors such as the complexity of the information, familiarity, and methods used to remember the information.

  • Anki and other memory systems are designed based on the idea that the decay rate of memory slows down with subsequent recall events.

  • The text highlights the limitations of our understanding of distributed practice, such as the exact causes of exponential decay of memory and what determines the rate of decay.

Percentage summarized: 80%

Topics left out:

  • The exact details of Ebbinghaus's study, such as the specific methods used and the results obtained.

  • Specific examples of studies on distributed practice and their results.

  • The conclusion and recommendations made by the author regarding the use of cognitive science in the design of memory systems.

Criteria for summarization: The goal was to provide an overview of the main ideas discussed in the text, including the key concepts, arguments, and limitations mentioned.