Literary Insights

BOOK LINK:

The author also engaged in intense self-learning through photography and writing to become an entrepreneur. He found Young’s ultra-learning method explained the steps he took to succeed in his own projects.
Key principles of Young’s method include meta-learning, concentration, diligence, practice, and interaction. The author found applying these principles resulted in his own successes like becoming a bestselling author.
The book aims to show anyone can learn quickly through this step-by-step ultra-learning process, not just “geniuses.” Serious learning gives life meaning by developing valuable skills through rapid yet focused practice.
The author wanted to learn computer science and become an entrepreneur, but wasn’t satisfied with his business degree. He discovered that MIT offered many course materials online for free through OpenCourseWare.
This led to his “MIT Challenge” idea - could he learn the equivalent of an MIT computer science degree without attending the university, just by using their open online resources?
Some courses lacked sufficient materials like recorded lectures, so completing every single class as a MIT student would wasn’t feasible. But he focused instead on passing the final exams and completing coding projects as the core elements of “earning” the degree.
By watching sped-up lectures, learning from mistakes on practice problems, and optimizing his studying methods, he found he could master a course in about a week - much faster than a normal semester schedule.
His goal was to complete all the required courses for the degree in under a year using self-study with MIT’s open online resources, at a fraction of the cost and time commitment of a traditional degree program.

So in summary, the author wanted to get an MIT-equivalent computer science education without attending the university, and explored if it was possible solely through MIT’s open course materials available online.

The author began to explore new ways of mastering skills needed for life and work beyond just computer engineering, which was his initial focus.
He recalls how his unusual experiment started after meeting Benny Lewis, an intense Irish polyglot, in Paris three years earlier. Lewis could speak French fluently despite a difficult year working there.
Lewis challenged himself to learn a new language fluently in just 3 months. He shared his approach of starting conversations from day one without fear of mistakes. This inspired the author.
Lewis’ most ambitious challenge was to reach a C2 level in German after 3 months, equivalent to perfect mastery. He fell just short, missing only one criteria around oral comprehension.
The author later realized Lewis’ feats were not unique - he encountered other hyperpolyglots and self-taught experts in fields beyond just languages.
Another example was Roger Craig, who used an innovative web-based approach to efficiently study and dominate the game show Jeopardy!, winning over $177,000 in one day by predicting the questions.

So in summary, the passage recounts how encounters with polyglots like Lewis and strategy experts like Craig inspired the author to explore more effective self-directed learning beyond traditional models.

Roger Craig was determined to break the Jeopardy! single-day record. As an information professional, he took an analytical approach to learn as much as possible.
He downloaded thousands of past Jeopardy! questions and answers and studied them in his free time for months. When he knew he was going on the show, he dedicated himself to studying full-time without rest.
He used data extraction and visualization tools to categorize questions by topic and identify his strengths and weaknesses. This helped him focus his studying.
He discovered some hidden patterns, like locations of higher value “Daily Doubles.” He focused on these rather than rigidly following topic categories.
Through analyzing his mistakes, he saw he needed to study fashion more in-depth.
He used an advanced spaced repetition algorithm to maximize his memorization efficiency from his studies.
Combining unconventional tactics and aggressive analytics, he played to win and broke the single-day record by winning $77,000 over 5 consecutive shows.
Stardew Valley was an indie game developed by Eric Barone as a solo developer. It became a huge commercial success, surpassing sales of many big studio games on Steam. Within the first year across all platforms, it sold over 3 million copies.
The game’s success transformed Barone from an unknown developer earning minimum wage to a millionaire included on Forbes’ list of top 30 gaming entrepreneurs under 30.
Reviews praised the game’s graphics as “incredibly charming and beautiful”. Barone’s commitment to his vision and self-taught skills were richly rewarded.
The story discusses how Barone dedicated himself to mastering the necessary skills through self-learning, which was vital to his success developing Stardew Valley. His self-directed learning approach allowed him to create a highly successful indie game.
The passage discusses the method of ultralearning, which is an intense and self-directed strategy for acquiring skills and knowledge quickly.
It describes how the author drew portraits by guiding himself with photos and comparing his drawings to the real photos on his phone. This allowed him to quickly identify errors in proportions, placement of features, etc. He did this hundreds of times to rapidly improve.
It then talks about various individuals who have used ultralearning methods for different projects, like learning languages intensely, compressing a computer science degree into 1.5 years, or replicating a PhD program independently.
These ultralearners usually work independently for long periods of time, optimize their strategies aggressively, and are highly motivated by their interests even if it means sacrificing traditional credentials.
Though each individual’s project is unique, they share techniques like spaced repetition, interleaving practice, and mnemonic devices. The goal is always intensive learning rather than entertainment or convenience.
While ultralearning requires going beyond one’s comfort zone and is difficult, the author argues it has potential benefits for professionals and students to rapidly learn new skills through self-directed projects.

The author argues that the ultralearning method is important due to changes in the economy and education. They believe that learning new skills quickly will become increasingly crucial for success.

They note that the economy is polarizing, with high and low-skilled jobs growing, but those requiring middle-level skills disappearing. This reduces opportunities for the traditional middle class.

It also indicates that college is becoming more expensive and does not always teach the necessary skills. Ultralearning can help fill these gaps more flexibly and affordably than returning to college.

Additionally, sectors change rapidly and continuous learning is needed. Ultralearning can better adapt to this than prolonged college courses.

Finally, it highlights that technology offers more opportunities to learn for free and effectively. This makes the ultralearning method possible on a scale previously unthinkable.

In summary, it advocates for ultralearning as a useful tool due to changes in the economy, education, and technology, which will require continuously and flexibly learning new skills.

The passage discusses the benefits of translation practice and applications that facilitate language immersion. It notes that technological advancement means many of the best ways to learn old topics have yet to be invented or widely implemented. The possibilities for learning are endless, awaiting ambitious self-learners to develop new approaches.

The method of ultralearning does not require new technology, as practices have a long history and many famous minds applied their own versions. However, technology offers incredible opportunities for innovation. Many ways of learning remain to be developed. Some learning avenues may become easier with appropriate innovations, while others become obsolete. Aggressive and effective autodidacts will be the first to master emerging approaches.

The method of ultralearning can accelerate, change, or enhance one’s career. Examples are given of people who used it to get a promotion, change careers, or develop new skills to stay relevant. Beyond careers, ultralearning broadens horizons and reveals new capabilities. Learning difficult things through focused effort expands one’s sense of what is possible.

The passage then considers the role of innate talent, using the example of Terence Tao. While some seem gifted without dedicated study methods, research suggests most attributes can be developed through certain types of practice, with the exception of innate physical traits. Ultralearning may not be universally replicable but still offers insights into more effective learning approaches.

The author met Tristan de Montebello years ago while researching ultra-learning. Tristan reached out saying he’d like to be a “guinea pig” and try out the ultra-learning method.
The author was interested in seeing if the ultra-learning process could be replicated by observing someone learn from the beginning, rather than just interviewing people after they achieved something remarkable.
Tristan and some other interested readers volunteered to try out the method. Tristan originally suggested learning piano but the author encouraged something completely new.
Tristan settled on public speaking as he had some experience performing as a musician but none speaking publicly. He was motivated by a past experience giving a talk that did not go well.
The author was interested in Tristan taking on public speaking because it could be a meta-skill that supports other abilities like confidence, storytelling, writing, creativity, interviewing, selling. Tristan would be one of the first to try applying the ultra-learning process from the start of a new project.

Tristan de Montebello decided to improve his public speaking skills and attended a meeting of Toastmasters International, where he met Michael Gendler, who became his mentor.

He entered the Toastmasters World Championship of Public Speaking with just over a week to prepare. He worked hard, practicing and improving each day with the help of his mentor.

He engaged in various activities to improve, such as taking improvisational speaking classes, receiving feedback from directors and actors, and giving speeches in different venues.

Thanks to his dedication, he won local competitions and made it to the finals of the World Championship in less than 7 months from when he started.

This success allowed him to change his professional career and start a public speaking teaching company called Ultraspeaking along with his mentor Michael Gendler.

Here is a summary of the key points about meta-learning from the passage:

Meta-learning means “learning about learning”. It’s learning how to learn a topic or skill effectively rather than just learning the topic itself.
Dan Everett is able to quickly start communicating in an unknown language through meta-learning. He is able to infer grammar patterns, vocabulary words, pronunciation, etc based on his interactions with the speaker.
Everett draws on his extensive meta-knowledge of languages. For example, he recognizes the language has a subject-verb-object structure and considers whether it uses tone or plural markers based on the responses.
His ability to analyze the language structures on the fly and experiment with new sentences comes from understanding how languages typically work at a broad level. He is not just repeating what he hears.
Meta-learning allows Everett to rapidly gain functional competence in a new language within 30 minutes despite having no common language or reference materials to work with. His understanding of language learning processes gives him a huge advantage.

So in summary, meta-learning or learning about learning allows Everett to efficiently deduce and absorb a new language through applying his conceptual knowledge of linguistics and testing hypotheses based on responses from the speaker.

Dan Everett uses two tools that give him a huge advantage in learning new languages. First, he has developed a detailed mental map of how languages work based on years of language learning experience. This map allows him to form hypotheses and theories about the functioning of any new language.

Second, he employs the method of monolingual fieldwork, developed by professor Kenneth Pike to learn indigenous languages. This method provides a sequence of objects and actions to start unraveling a new language. Everett has used this method to become one of the few non-natives who can fluently speak Pirahã, a language used by an isolated Amazonian tribe.

Everett’s case illustrates the power of using metalearning to learn new things faster and more efficiently. Having a map that shows how something works, what skills and information need to be mastered, and what methods are available for efficient learning is the basis for success in ultralearning projects. Metalearning draws the map and shows the path to the destination without getting lost. It allows one to learn additional languages or skills more effectively by understanding the underlying processes involved.

Before embarking on a new project or goal, it can be helpful to interview experts who have already achieved what you are aiming for. Speaking with accomplished architects before studying design techniques, for example, could validate whether that project will actually aid in becoming a successful architect. Interviewing an expert allows you to get advice from someone with relevant experience and determine if your motivation and plans are properly aligned before investing significant time and effort. Summarizing the expert’s perspective can indicate whether the intended effect of your project or goal is realistic beforehand.

University course catalogs outline the curriculum and individual course details for currently enrolled students.
When learning a non-academic topic or professional skill through self-study, it’s best to search online for resources from others who have acquired that skill, or interview experts. Spending an hour researching available courses, articles and recommendations online should yield good options for learning almost any skill. Investing some time upfront can save dozens or hundreds of hours later.
When adopting a pre-existing study plan, the method of emphasis/exclusion can be used to modify it. This involves focusing on areas that align with identified goals, and omitting or delaying elements that don’t.
Research should take around 10% of the estimated total study time. Longer projects may only require 5% for research. The goal is to avoid hastily choosing the first option without considering alternatives.
Re-evaluating the study plan may be needed mid-project if returns are diminishing or new techniques are identified. Benefits of further research should be compared to benefits of study time.
Meta-learning skills improve over time with each project experience, building long-term confidence and ability to take on ambitious goals. Benefits exceed any single project.

So in summary, the passage provides guidance on effectively researching study plans and resources for self-directed learning through emphasis on goals, estimated research timescales, re-evaluating over time, and how meta-learning skills accumulate with experience.

Mary Somerville was born into a poor Scottish family in the 18th century, when even high society ladies didn’t receive a formal education. Her mother didn’t forbid her from reading, but society frowned upon women engaging in reading.

Despite social obstacles and lack of support, Mary achieved great academic success. She learned several languages, mathematics, painting, and piano. In 1835, she became the first woman to join the Royal Astronomical Society.

Her greatest achievement was translating and expanding Laplace’s “Treatise on Celestial Mechanics,” a five-volume work on gravitational theories and advanced mathematics that was acclaimed. Even Laplace acknowledged that Mary was the only woman who understood his work.

Despite her genius, Mary doubted her abilities and claimed to have a poor memory. However, she excelled in her immense capacity for concentration, enabling her to study despite distractions and domestic obligations.

Her ability to deeply concentrate and resume studies after interruptions was crucial in overcoming obstacles and achieving her significant scientific contributions in a challenging environment for women.

Maintaining concentration is important for learning difficult things, but it’s essential to understand what type of concentration is most effective beforehand.

The state of “flow,” where the mind fully immerses itself in the task, may not be ideal for rigorous learning practices requiring self-assessment and correction.

Studying in prolonged blocks isn’t as effective as dividing study time into shorter sections alternating between different topics.

However, study periods also need to be long enough to achieve real learning (between 50 minutes to 1 hour).

To maintain concentration, it’s crucial to eliminate environmental distractions such as phones, the internet, noise, etc. Attention should also be paid to mental distractions like thoughts and emotions that divert attention.

Finally, it’s important to find a study method and pace that suit each individual, considering their schedule, personality, and learning style. There’s no one-size-fits-all formula that works for everyone.

The text discusses various causes of lack of concentration and distraction when trying to learn or be productive. The three main causes discussed are:

Environment - Things like having the TV on in the background or needing to search for supplies can break concentration. While a perfect environment is not always possible, being aware of your best environment can help.
Task - Some tasks are inherently more difficult to focus on, like reading vs watching a video. Modifying the task, like taking notes while reading, can sometimes help focus.
Mindset - Negative emotions, restlessness, and wandering thoughts make focusing hard. While emotions can’t always be controlled, recognizing them and returning focus to the task can help. Taking breaks when truly blocked may aid creativity.

It also discusses how optimal concentration depends on the right balance of arousal/stimulation and task complexity. Simple tasks benefit from high focus, while complex tasks requiring creativity benefit more from a relaxed focus. Modifying arousal levels through things like sleep, noise, etc. can help maximize concentration based on the task. The key is finding an arousal level that suits the complexity of what you’re working on.

The importance of finding the right environment to concentrate and be productive is discussed. Simple activities may work well in noisy environments like a café, while for complex tasks, a quiet place like a library is preferred.

It’s essential to try different environments to discover what works best for each person and type of task. What benefits concentration varies from one individual to another.

Improving concentration requires starting gradually, with short goals, and gradually increasing the time. With patience and perseverance, significant achievements are possible, as demonstrated by Mary Somerville.

The next principle discussed is diligence, which means learning in a context linked to how those skills will be applied. The example of Vatsal Jaiswal is presented, who improved his portfolio to focus specifically on the skills required for architecture studies, ultimately securing him a job.

In summary, the importance of adjusting the learning environment to each person and task is highlighted, as well as approaching learning diligently and linked to how it will be applied in real practice.

Traditional learning is characterized by studying data, concepts, and skills in isolation, without contextualizing how they will be applied. Formulas are memorized without understanding the problems, and vocabulary without intending to use it.

This indirect approach is also common in self-teaching. Apps like Duolingo use multiple-choice instead of real conversations, making language practice difficult.

Learning by doing is more effective, as demonstrated by Benny Lewis with languages or the author with MIT problems. However, it’s not always possible, as experienced by Roger Craig for Jeopardy! or Vatsal Jaiswal for architecture.

The transfer from the classroom to real life is a significant challenge in education. Research shows few changes after teaching, even in graduates.

This raises doubts about theories like studying Latin improves thinking. Learning programming or critical thinking doesn’t necessarily extend those skills to other areas.

In summary, direct learning through practice is more effective, but not always feasible. Traditional education has a long-standing problem in failing to achieve knowledge transfer to the real world.

Transfer of learning has been a holy grail in education for 100 years, but has proven difficult to demonstrate empirically. However, transfer does occur in everyday life, like using an analogy or skill from one area in another.
The disconnect may be because transfer is harder with limited knowledge. Deeper knowledge in a field makes ideas and skills more flexible.
Traditional learning is indirect - learning in an abstract classroom versus a real context. Diligent learning solves this by connecting learning directly to the field of application.
Practice and experiential learning are direct ways to avoid needing significant transfer. Projects can also directly simulate the skill context.
While past research on transfer is discouraging, deeper understanding does make future transfer more flexible. Experts like Dan Everett demonstrate this by easily learning new languages.
In summary, diligent learning connects acquisition and application more directly to overcome the limitations of indirect, traditional learning. Deeper knowledge also facilitates transfer by building flexible understanding.
Learning through projects is an effective tactic because it guarantees you will learn the skills needed to complete the project. For example, creating your own video game is a great way to learn programming.
Immersive learning involves surrounding yourself with the context where the skill will be used. This ensures much more practice than typical learning and exposes you to a variety of situations to hone the skill. Learning a language through full immersion is very effective.
For skills that cannot be practiced directly like flying a plane, high-fidelity simulation can be as effective as real practice if it faithfully replicates the cognitive aspects of the task.
The “crash course” approach involves taking on challenges significantly above your current level to maximize learning. For example, public speaking to challenge yourself more than easier practice opportunities.
Learning directly from the source, whether through immersion, projects or simulation, helps bridge the gap between learning and real-world application compared to more passive learning styles. But direct practice is also needed to truly master a skill.

Benjamin Franklin possessed talent for writing and persuasion, which helped him contribute to the drafting of the United States Declaration of Independence.

In his autobiography, Franklin describes how he developed his writing skills from a young age through practices such as imitating essays he read and reconstructing them from memory, practicing word substitution to expand his vocabulary, and learning rhetorical techniques like the Socratic method of asking questions rather than arguing directly.

These early practices allowed him to master the art of writing and then successfully use it for business, science, and political matters. He demonstrated a unique ability to write persuasively by adopting different perspectives and using pseudonyms.

Franklin’s careful analysis of writing as a skill and his intensive practice of its components exemplify the fourth principle of “ultralearning”: focusing on deliberate practice to effectively improve a skill.

The final step is to return to direct practice and integrate what we have learned. This serves two purposes. The first is that even in well-designed intensive practices, there will be problems of transfer due to an isolated skill now being applied in a much more complex context. We should see it as developing the tissue that connects the muscles we exercised separately.

The second purpose is to check if the intensive practice was well-designed and appropriate. Many attempts to isolate an intensive practice may fail because that practice does not get to the root of what was difficult in the real practice. No problem, this information is important to help us not waste time learning things that do not help us achieve our goals.

The less we have advanced in the learning process, the faster this cycle should be. Changing between direct practice and isolated skill practice, even within the same learning session, is a good idea at first. Later, as we improve in what we are trying to do and need to work harder to visibly improve overall performance, it becomes more acceptable to distance the practices. As we approach mastery of the subject, we may end up concentrating almost entirely on practices, as we will have refined our knowledge of how complex skills are divided into individual components and improving an individual component will become increasingly difficult.

Traditional learning focused on passive reviewing of material, but recall testing (examining to learn) is more effective for long-term retention through active retrieval of information from memory.
Experiments showed students who took self-tests to try recalling information without their notes outperformed those who repeatedly reviewed material or created concept maps. Active recall is a powerful learning tool.
Ramanujan, an Indian math genius, largely taught himself advanced math from a textbook listing theorems without proofs. This forced active recall and problem-solving, developing deep understanding through repeated self-examination.
Retrieving information through testing or self-quizzing strengthens memory better than passive studying. It provides feedback on knowledge gaps and requires generating answers instead of just recognizing them. This active engagement makes information more learnable.
While challenging, practices that push through difficulty like rigorous self-testing ultimately benefit learning more than easy repetition. Examining material to retrieve it from memory is an effective practice principle.

Data retrieval, attempting to recall information on one’s own, is more effective for learning than passive methods like reading or reviewing.

However, students tend to prefer passive methods because they mistakenly believe they are easier and help them learn better in the short term.

This is because students’ learning judgments are based on how fluent they find it to process information, not on their long-term retention. Active retrieval is initially more difficult.

Students may also avoid active retrieval because they believe they are not sufficiently “prepared.” But in reality, it works better even before being fully prepared.

The difficulty of active retrieval, such as recalling without hints, makes the retrieval effort greater and more beneficial for long-term memory.

Even attempting to recall information that is not yet known can improve future learning, through mechanisms such as attention or the development of search strategies.

It is not feasible to remember everything, so it is necessary to focus on retrieving the most relevant information for each purpose. Direct testing also helps prioritize this information.

Retrieving information from memory (also known as retrieval practice) is an effective way to learn and retain knowledge. Simply re-reading or passively reviewing material is less effective than actively trying to recall it without cues.
However, retrieval practice requires having the foundational knowledge in the first place to recognize when a certain concept or function could help solve a problem. Simply being able to search without that base knowledge doesn’t help much.
For programmers, the ability to solve problems in multiple efficient ways distinguishes great programmers from mediocre ones. This breadth of skills requires passive exposure, which benefits from retrieval practice.
Some tactics for effective retrieval practice include flashcards, free recall (writing down everything you remember without prompting), transforming notes into question format, creating self-challenges to solve based on material, and practicing with materials closed to avoid cues.
Great historical figures like Ramanujan effectively used intensive practice and retrieval tactics to develop their exceptional skills and mental “catalog” of techniques to draw from. Retrieval practice, while not the sole factor, seems to feature prominently in the development of many geniuses and ultralearners.
Interaction is an important part of the deliberate practice theory of skill acquisition. Getting immediate feedback is key to improving and reaching expertise.
However, interaction can also be counterproductive if the feedback attacks the person’s ego or is not useful for guiding future learning. Praise and criticism of the person themselves rather than their skills/performance can have a negative impact.
Comedians like Chris Rock deliberately test out new material in small clubs before large audiences. This allows them to get useful feedback to improve their jokes from a wide range of perspectives. Rock warns audiences he may not be very good to avoid ego-boosting praise.
Research shows around 38% of studies found interaction had a negative effect. The type of criticism matters - it needs to provide constructive information on how to improve, not personal judgments, for it to aid learning. Learners need to filter criticism for what’s useful versus discouraging.
Too much positive praise can also be counterproductive to learning by lowering standards and motivation. Learners should aim for feedback at their current learning level.

So in summary, interaction and feedback can greatly boost learning but only if it is constructive, focused on performance not the person, and at an appropriate level for the learner’s current skills. Learners need to actively filter what criticism is useful versus harmful to their motivation or vision.

Criticism can be an powerful comparative tool for ultra-learning students who want to learn more and faster. Criticism is uncomfortable, it can be harsh and discouraging, and does not always feel good. Standing on stage to do a comedy monologue is surely one of the best ways to improve your style, but it can be terrifying because awkward silence hurts.

The fear of criticism is usually more uncomfortable than experiencing criticism itself. Therefore, it is not so much the negative criticism itself that can prevent progress, but the fear of receiving a criticism that completely destroys you. Sometimes the best thing is to dive headfirst into the most hostile environment, because although the criticism may be very negative at first, it can reduce the fear of starting a project and allows for adjustments if it turns out to be too harsh to be useful.

This requires a good dose of self-confidence, resolve and persistence, which is why many self-taught projects reject the interaction that can generate the harshest criticisms. Instead of going to the source, receiving direct criticism and using that information to learn quickly, people tend to dodge blows and move away from a source with great potential for learning. Ultra-learning students acquire skills very quickly because they seek out that aggressive criticism when others opt for practices that include soft or no criticism.

Three types of criticism are analyzed: generalized criticism, informative criticism, and constructive criticism. Generalized criticism is the most common but least elaborate - it only indicates if something is good or bad overall without specifics. Informative criticism tells you what is wrong but not how to fix it. Constructive criticism is the most useful as it tells you what is wrong and how to improve, but is the hardest to obtain without a mentor. While all criticism can aid learning, constructive criticism accelerates the process the most when available.

Paying a tutor can be useful in situations where identifying the exact nature of an error requires expertise. This helps correct mistakes with little effort.
Self-learning through ultralearning should not imply learning must be a solitary goal. Interacting with others for feedback can aid the process.
Different types of criticism have their uses depending on conditions. General criticism is less useful than specific, informative criticism. Constructive criticism requires expert input/a correct approach.
It can be counterproductive to push for more specific criticism if feedback is only general. Similarly, suggesting improvements without a valid alternative risks bad advice.
Immediate feedback is generally better, as it quickly identifies mistakes. However, receiving criticism too soon may inhibit learning by discouraging problem-solving attempts.
Strategies like filtering feedback channels to reduce noise, targeting an appropriate difficulty level, and evaluating one’s learning strategy/speed can help maximize the benefits of criticism.
The article discusses Nigel Richards, a champion Scrabble player known for his prodigious memory. He has won multiple world championships, including in French even though he doesn’t speak the language.
Scrabble requires memorizing valid words to form plays on the board. Top players memorize thousands of words, including rare short words that are valuable. Richards amazes other players with his ability.
Richards is very private and mysterious. He refuses interviews and seems indifferent to fame or money. He defeated a French speaker from Gabon to win the French championship.
While impressive, others have won championships in languages they don’t speak fluently by memorizing letter patterns rather than meanings. Scrabble relies on letter combinations, not language skills.
Richards also has an intense passion for cycling. He has cycled through the night to compete in tournaments, showing great dedication and stamina outside of Scrabble as well.
The article intrigues about Richards’ secret and theorizes his intense memorization abilities come from applying the same dedication to Scrabble word memorization as he does to cycling training. His success suggests applied focus and memorization through intense immersion.
The article discusses Richards, a champion Scrabble player known for his intense memorization abilities. He memorizes lists of words, reading dictionaries non-stop while cycling for hours to recall the words.
His obsessive intensity mirrors other “ultralearners” who intensely dedicate themselves to learning. Cycling helps Richards mentally review word lists. He focuses on visual recall and goes through words forwards and backwards.
While his techniques aren’t novel, his total domination of competitions suggests his intensely compulsive personality enables extreme dedication to practicing recall through cycling. His normal intelligence may be average, but his Scrabble skills represent extreme focus on the game.
The article then broadens to why memory is difficult. Three main theories for why we forget are decay over time, interference from new learning conflicting with old, and lost cues making recall harder. Memory erosion in professionals also shows knowledge deteriorates with experience.
The case of Richards and memory challenges more broadly illustrates the importance of memory for learning and the need to develop strategies to retain knowledge rather than let it fade, as memory underpins many skills and professions.
Negative reinforcement, like thinking of something as “bad”, can make it difficult to remember the new meaning and associate new learning with punishment.
Retroactive interference is the opposite - when learning something new “erases” or represses a previous memory. Anyone who has learned Spanish and then tried to learn French knows how problematic retroactive interference can be as French words come out when trying to speak Spanish again.
The third theory of forgetting is that many memories are not forgotten, but inaccessible. We can only say we’ve remembered something if we can retrieve it from memory. But since we can’t experience all long-term memories at once, there must be a process to retrieve information with the right cues. However, links in the retrieval chain may break from decay or interference, making the memory inaccessible.
This explanation has some advantages - it fits with experiences of something being “on the tip of your tongue”. Relearning is also often faster than original learning. However, some argue recall is a creative reconstruction process, so “lost” memories retrieved through new cues could be inventions. This seems true for “recovered” traumatic memories.
Spacing, proceduralization, overlearning and mnemonics are four mechanisms used to avoid forgetting things learned through ultralearning methods. Spacing involves spreading out study sessions over time for long-term retention, though the spacing interval is important to find. Other methods like repetition, practice and memory aids are also used.

The passage discusses three mechanisms of memory that can be leveraged for learning:

Spaced repetition - Practicing skills or knowledge regularly over spaced intervals of time. This is more effective for long-term retention than cramming.
Proceduralization - Skills transition from declarative to procedural knowledge as they are practiced more. Procedural knowledge is more strongly retained in memory over time. Focusing practice on fully automating core skills and concepts can aid retention.
Overlearning - Practicing a skill beyond the point of mastery. Additional practice of a few hours or days can extend the period of retention of memories by a couple weeks. Overlearning as part of long-term projects involving spaced repetition and proceduralization may lead to even longer-term retention.

The key strategies discussed are ensuring some knowledge is fully proceduralized before ending practice sessions, focusing effort on proceduralizing core skills, and leveraging overlearning as part of diligent, long-term practice to deeply engrain important foundations. This combines cognitive mechanisms to optimize long-term memory retention for self-directed learners.

The two main methods for applying overlearning that I have encountered are practicing fundamentals and advanced practice. Practicing fundamentals involves refining the basic elements of a skill through extensive practice over a long period of time. This approach works well in combination with an extensive project after the initial ultralearning phase. Advanced practice involves raising the level of difficulty above basic skills so that lower-level skills are overlearned by applying them in a harder environment.

A study of algebra students showed this second method is effective. Most students who took algebra classes years ago had forgotten much of what they learned, perhaps due to complete loss of information or cues making it inaccessible. Interestingly, the rate of forgetting was the same regardless of the student’s initial performance - better students retained more but the proportion forgotten was the same. However, one group did not show as steep a decline in forgetting: those who had studied calculus. This suggests increasing difficulty to a more advanced skill allows previous skills to be overlearned, avoiding some forgetting.

Mnemonics is another common tool used by many ultralearning students. Mnemonic strategies translate abstract information into vivid images or spatial maps. When effective, results can seem incredible, like records for memorizing digits of pi. However, mnemonics have some disadvantages. Most impressive systems require significant upfront investment for tasks that may not be very useful. Also, recall through mnemonics is not usually as automatic as direct memory. Mnemonics can help bridge gaps but do not create lasting memorization on their own. Therefore, mnemonics are a potent but fragile tool, better used to augment other strategies than form the basis of learning efforts.

Feynman possessed an astonishing ability to solve math and physics problems quickly and intuitively, earning him the reputation of a “wizard.”

However, his measured intelligence (with an IQ of 125) was not extraordinarily high. He also had gaps in other areas such as history and literature.

His apparent “magic” in calculation stemmed from an excellent memory for formulas and numerical values, as well as the ability to break down problems quickly.

His skill in picking locks came from a detailed study of their workings, not supernatural powers.

The key to his physical intuition lay in imagining concrete examples representing each theory or principle, enabling him to quickly spot conceptual errors.

Studies show that experts like Feynman tackle problems by first identifying the fundamental principles involved, unlike novices who focus on external details. This more conceptual approach is more effective.

In summary, Feynman’s “magic” had a rational basis in his memory, abstraction ability, and conceptual problem-solving method, rather than supernatural skills, although his level of skill remained astonishing.

The simplest answer is that intuition cannot be developed directly. It is the problem-solving experience that helps build a mental model to explain how problems work. Intuition seems magical but is actually the product of long experience dealing with problems.
A study comparing novice and expert chess players found that experts can remember more board positions because they have stored around 50,000 “chunks” of common board configurations in their memory. This allows them to analyze complicated positions intuitively rather than piece by piece like novices.
However, experts’ facility is limited to positions from real chess games. If given a randomly arranged board, experts have no advantage over novices and must treat it like novices do by remembering individual pieces.
Richard Feynman’s intuition also came from an immense library of physics and math formulas stored in his memory from years of experience. He could solve real problems intuitively but intuition failed for contrived issues outside his knowledge base.
To develop intuition like Feynman, one must spend significant time studying a subject, avoid superficial learning, persevere through difficult problems, and understand things by reproducing results rather than just accepting others’ work. Demonstrating ideas for oneself builds deeper comprehension.

In summary, the passage discusses how expertise and intuition develop through extensive experience solving real problems over time, not from superficial or shortcut learning methods. It uses studies on chess players and Feynman’s approach to illustrate how properly challenging oneself leads to intuitive understanding.

During her study, Rebecca Lawson asked participants to explain how a bicycle works by connecting each part to the next. However, most participants had no idea how the parts were connected, even though they used bicycles regularly and thought they understood how they worked. This “illusion of understanding” is a common barrier to deeper knowledge because it’s easy to think we understand more than we actually do without testing our knowledge.
Feynman’s approach of demonstrating theories to understand them avoids this problem of self-deception that other approaches have difficulty achieving.
Using concrete examples forces a deeper process of assimilating material. Studies show it’s not just time spent on information that determines what’s retained, but also what we think about it. Thinking about meaning and concepts results in better retention than just surface-level details.
Feynman’s habit of developing a concrete example for a problem can be interpreted as a deeper form of assimilation that increases long-term retention and intuitive understanding. It also encourages interaction and feedback to catch gaps in understanding.
“Don’t deceive yourself” was one of Feynman’s most famous aphorisms. He demonstrated a profound skepticism of his own comprehension to avoid issues like the Dunning-Kruger effect where those with less knowledge overestimate their understanding.
A way to avoid self-deception is to ask yourself many questions, as Feynman did, even “dumb” ones. This can reveal implications you hadn’t considered. Avoiding questions to seem more informed comes at a huge cost.
Vincent van Gogh is now considered one of the greatest and most famous painters of all time, but he started painting rather late at age 26 after failing in other careers.
He lacked natural artistic talent and drawing ability compared to his peers. His early sketches were rough and childlike. It took him many attempts to draw something resembling his subjects.
He struggled in art school and left after less than 3 months, as his work was seen as too crude and his peers did not get along with his intense personality.
Van Gogh was largely self-taught due to difficulties maintaining personal relationships and friendships. He had only brief periods of formal education.
Despite his late start, lack of talent, difficult temperament, and mental health struggles, Van Gogh developed one of the most recognized artistic styles in history through relentless experimentation outside of formal learning.
His short but prolific career was tragically cut short by his death by gunshot wound at age 37, though it is unclear if it was suicide or accident.

So in summary, Van Gogh contradicted expectations by becoming one of the greatest artists ever through determined experimentation beyond his early abilities and challenges.

Van Gogh experienced several professional failures before turning to painting, despite his family connections.

His approach to painting involved identifying a learning source (method, style), studying it passionately to create dozens of works, and then switching to another source to improve.

This method of intense and repeated experimentation allowed him to mature as a painter until he became unforgettable and unique.

His early attempts included home courses copying exercise books and Millet’s painting “The Reaper.” He also sketched models.

He studied other artists like Van Rappard and Mauve, experimenting with new techniques, though sometimes unsuccessfully.

He experimented with materials, methods, and even the philosophy of his art, transitioning from muted tones to vibrant colors.

His variety of approaches and intense experimentation helped him overcome obstacles and develop a unique style, despite criticism.

In summary, experimentation was key for Van Gogh to find his own path as a successful and original painter, through continuous testing of new resources, techniques, and ideas.

Experimentation plays an important role in learning and skill development. It allows one to try different resources, techniques, and styles to see what works best for them.
When starting out, experimentation often focuses on resources and materials. But as one’s skills develop, the options for what to learn next expand quickly, so experimentation also helps decide what to learn.
Languages are a good example - there are many possible areas like literature, conversations, comics, etc. to specialize in after initial vocabulary. Experimenting helps choose a direction.
Once basics are mastered, there are usually multiple valid styles rather than one “correct” way. Experimenting helps identify individual strengths and weaknesses.
Artists like Van Gogh experimented with different styles, from traditional artists to friends’ techniques. This helped develop their own unique style.
Experimentation requires openness to many possibilities rather than dogmatism. Using tactics like copying masters first, comparing methods side-by-side, and introducing new limitations helps structure experimentation effectively.

The key message is that experimentation is important for skill development as it helps identify what works best for the individual by trying different resources, techniques and styles through structured experimentation.

The passage discusses adding limitations or constraints in order to avoid falling into routines and to come up with innovative solutions. Imposing specific limitations on how we can act encourages us to explore less known options.
One powerful technique to avoid routines is to introduce new limitations that prevent the use of old formulas, even if habit encourages us to use them.
It is presented as an axiom in design that the best innovations emerge when working with limitations. Giving designers absolute freedom usually leads to chaotic solutions. Limitations force us to explore less known alternatives and improve underlying skills.
Some ways to add limitations to develop new skills include mixing unrelated skills, exploring extremes, and experimenting instead of relying on old routines. Experimentation is key to learning, applying feedback, and identifying what works best for each individual. It encourages going beyond one’s comfort zone to try new approaches.
The main point is that limitations and constraints, while uncomfortable, can drive innovation by pushing us out of routines and default ways of thinking. Limiting ourselves strategically encourages exploration of unknown options and helps improve and discover new skills. Experimentation is presented as crucial for continuous learning and improvement.
Projects that require more planning and care tend to be those that are most successful when approached systematically. A solid, well-organized and implemented plan can give you the confidence to take on harder challenges in the future.
The first step is to research thoroughly. Planning in advance avoids problems and having to make drastic changes later. Research is like packing for a long trip - you want to have the right materials and be prepared.
The second step is to plan your time. Decide how much total time you will dedicate, when you will study each day/week, and how long the overall project will last. Schedule specific times to increase commitment and reduce procrastination.
The third step is to implement your plan. Track your progress and be willing to modify your approach if needed. Ask yourself questions to check if you are truly following principles of ultra-learning or getting off track through passive reading instead of active recall/practice.
Periodic evaluation allows for course corrections to stay on track. An initial trial week can show if your time commitments are realistic before fully starting the project.

The key takeaways are that thorough upfront planning, a dedicated schedule, and on-going self-evaluation are important for long-term learning success when using an ultra-learning approach. Being flexible to modify the plan is also important to keep yourself motivated and progressing effectively.

The passage discusses several principles for effective learning: concentration, diligence, practice, data recovery, interaction, retention, intuition, and experimentation. It analyzes each principle and provides questions to self-evaluate one’s approach.
It recommends interviewing other successful students to get learning resources and advice. It also says to invest 10% of the total project time in planning.
After finishing a learning project, it’s important to evaluate what went well and what didn’t in order to avoid mistakes in the future. Even successful projects can be improved.
After learning a skill, one must decide whether to maintain the knowledge through regular light practice, or let some fade but relearn more efficiently if needed in the future. Both maintenance and relearning have merits depending on the skill.
Proper evaluation and long-term planning helps optimize the learning process through multiple projects over time using ultralearning principles. The goal is continually refining one’s approach, not just acquiring individual skills.

In summary, the passage provides a framework for self-evaluating one’s learning approach, planning projects effectively, and strategizing how to maintain or relearn skills after completion. The ultimate aim is perfecting the learning process itself.

The fundamentals (concrete knowledge) are more important than the details necessary to solve a problem, as the latter can be relearned more easily. However, forgetting the fundamentals will hinder solving problems completely.

The third option for continuing learning is to specialize in the skill that has been learned. This requires constant practice at a steady pace or engaging in another intensive learning project.

Specialization requires a long-term process that goes beyond a single project. Sometimes, overcoming initial barriers helps clear the way and accumulate knowledge gradually until reaching specialization.

Some projects may stagnate, requiring unlearning what has been learned and facing frustration again before continuing. These projects benefit from intensive methods to achieve mastery.

Alternatives to intensive learning include low-intensity habits (when learning is spontaneous and passive) and formal education (for the credentials and communities it provides).

The goal is not to reject other options but to recognize that the possibilities for learning are more abundant than they seem. The intensive method expands opportunities, rather than limiting them.

Judit Polgár is considered one of the greatest chess players of all time. She achieved worldwide success at a very young age, setting many records.
Her success challenged preconceptions in the male-dominated world of chess. Some players, like Kasparov, were dismissive of her abilities due to her gender.
Polgár’s talent was not a result of natural genius but rather the result of an experiment by her father László Polgár to prove that genius can be created through education and hard work from a young age.
He educated his three daughters intensively in chess from a young age, starting with the oldest Zsuzsa. All three daughters became chess masters to varying degrees.
Polgár had a controversial early match against Kasparov where he allegedly made an illegal move change but was not penalized. This caused tension between them.
Eight years later she got a second chance to face Kasparov head-to-head in a rapid match, challenging preconceptions of women’s chess abilities against one of the game’s legends.
The trincantes (opponents) only had 25 minutes each. Judit played the Ruy Lopez (or Spanish Opening), named after the 16th century Spanish priest who wrote a book about it. This is one of the most common openings and involves quickly moving the pieces on the king’s side - knight, bishop.
Kasparov countered with the Berlin Defense and moved a second knight, overlooking the potential threat from Judit’s bishop. This strategy is very solid and often leads to draws. Kasparov did not want to take risks. After a quick exchange of pieces, both players were well-matched. Judit, playing white, had her king well defended. Kasparov, with black, did not have the same security, so he kept both bishops, a combination that can be decisive in winning a match.
Judit continued pressuring calmly and cornered one of Kasparov’s bishops, neutralizing his advantage. Slowly but steadily, Judit’s moves consolidated her position while Kasparov’s became more questionable. Finally, the advantages Judit had accumulated became a real danger. After losing two more pawns and facing the threat of several checksmate options, Kasparov resigned.
After this defeat, Kasparov amended his view of Judit’s abilities and the idea that women could compete at the highest level of tournaments. “The Polgars have proven there are no intrinsic limitations in their skills, an idea many male players refused to accept until a twelve-year-old girl with pigtails crushed them.”
László Polgár established very good principles of positive feedback from the beginning with his daughters’ chess learning. Initially when he was a better player, he would adjust his strategy so they felt threatened but could win enough to enjoy the game.
He ensured he didn’t always win against the girls so they felt capable of thinking. The key early on was sparking interest to the point of obsession.
Imposition of learning was opposed - motivation and commitment had to come from within the girls themselves. Coercion would not lead to serious pedagogical results.
Autodidactic learning was an important goal - not just teaching moves but how to learn on their own as they surpassed his skills.
Beyond principles, László and Klára fully committed to providing opportunities like a large library of games, books, and tutors so the girls could continually improve.
All key principles of ultralearning were present - metacognition, concentration, diligence, practice, retrieval, interaction, retention, intuition, and experimentation.
The Polgár method shows how intensive learning can be applied to many fields when self-driven, enthusiastic and aggressive learning follows core learning principles.

In summary, László Polgár established pedagogical principles and provided support and opportunities for his daughters to follow an intensive self-directed ultralearning approach to mastering chess at an elite level.

The social environment is an important factor in learning, as emotions, culture and relationships affect learning in complex ways.
Some suggested starting points for creating an environment that encourages ultralearning include:

Create a stimulating goal or allow people to set their own goals. Inspiration is key.
Be careful with competition, as it can hurt motivation if one compares themselves unfavorably to others. Start individually if needed.
Prioritize learning at work by giving employees projects slightly above their level in addition to work at their level. This fosters a learning culture.

In summary, the social/environmental context is important for motivation and learning. Setting goals, avoiding unfavorable comparisons early on, and prioritizing learning can help create an environment conducive to ultralearning. Both individual and competitive aspects may work at different stages of the learning process.
The author conducted interviews with various researchers to better understand questions about learning such as “Is interaction good?” and “Why do people forget?“.
He read biographies of famous intellectuals, businesspeople, and scientists to see how they approached the learning process. Writing this book was in many ways a reflection on learning and how to learn more and faster.
While he had a deep interest in learning before starting this project, he only dove deeper into research when he had this structured book project.
Writing the book in a suitable tone for the topic was challenging, different from his informal blog style. He wanted to share others’ stories and achievements, not just his own experiences.
Most biographies and stories don’t focus on learning methods, so his research involved digging through long biographies for brief mentions of learning approaches. This pushed him to improve his research and narrative skills.
Through this “ultralearning” project of writing a book on learning while learning more himself, he illustrated that there is always more to learn. Completing a project doesn’t mean learning is complete.
His greatest hope is that readers are motivated to start their own learning projects and push beyond what they ever imagined possible.

It is indeed possible to obtain an education comparable to that of institutions like MIT without physically attending them. Several reasons support this claim:

There is an abundance of free or low-cost online educational material, such as MOOCs offered by top universities. This allows for the study of many university-level topics at no cost.

With self-management and self-discipline, one can design a personalized study plan covering important topics. Additionally, learning can be validated by taking official exams or certifications.

By employing effective learning strategies such as those outlined in the book (fast feedback, simplification, focusing on the essentials rather than details, etc.), it’s possible to learn independently in less time.

There are also alternative programs like intensive in-person courses or boot camps that teach practical skills in shorter periods than traditional university degrees.

With internet access and online learning communities, a motivated individual can overcome the limitations of not attending a specific institution. The key is to focus on continuous learning.

In summary, while universities offer value for reasons beyond purely academic ones, the learning itself depends more on the individual than the institution when resources are utilized effectively.

Here are the key points summarized from the sources provided:

Source [1] discusses Steve Wozniak co-founding Apple computers and his views on the future of technology from an 2008 Wired article.
Source [2] is a 2011 YouTube video interview between Thanh Huynh and Roger Craig discussing knowledge tracking tools.
Source [3] is a 2016 article from Destructoid reviewing the farming simulation video game Stardew Valley.
Source [4] is a Reddit post about a student who completed a 4-year computer science degree in 1 year using free online courses from MIT.
Source [5] discusses a student who graduated college in 3 semesters by taking more courses per term.
Source [6] describes someone pursuing a “personal PhD” by self-studying various topics without a degree program.
Source [7] is a 2017 self-published book called “The STEMpunk Project” by Trent Fowler.
The sources provide examples of individuals completing academic programs faster than usual through self-directed learning using online resources, taking more courses concurrently, and customized study without traditional degree paths. They illustrate different approaches to learning more quickly and efficiently.

Here is a summary of the sources provided:

The origin of the quote “In theory, there is no difference between theory and practice. In practice, there is.” has been attributed to different people over the years, but it is believed to originate from 1882 when a Yale student named Benjamin Brewster wrote it in the Yale Literature Magazine.

Paul Graham discusses changing expertise in an article from 2014 titled “How to Be an Expert in a Changing World.”

Cal Newport first coined the term “ultralearning” in the title of an article written by Scott Young about his experiments mastering linear algebra in 10 days for Newport’s website.

During Scott Young’s polyglot experiment, he discovered the language a woman was speaking was a Hmong dialect used in parts of China, Vietnam and Laos.

For the purposes discussed, the terms “meta-linguistic awareness” and “meta-learning” can be used interchangeably. There is research on related topics that uses prefixes like “meta” dealing with knowledge, cognition, memory, and more.

Phone calls can avoid potential unwanted effects of an in-person meeting when conducting certain types of discussions.

Here are the summaries:

(7) This method for improving time management was developed by an Italian consultant named Francesco Cirillo. It’s called the Pomodoro Technique because pomodoro means “tomato” in Italian and the timer he used had the shape of a tomato.

(8) The diligence referred to here is intimately related to the concept of appropriate processing transfer, using psychological terminology.

(9) To be fair to Duolingo, there are more direct ways of learning within the app, but they ultimately become repetitive because the number of lessons on the mobile app is limited.

(10) Modal logic is an extension of propositional logic that allows expressing ideas like “should”, “normally” or “possibly”.

(11) I should note that not all researchers agree with the “chunks” theory. K. Anders Ericsson, the psychologist who supports deliberate practice, prefers an alternative model called “Long-term memory”. The differences are merely technical, and both models defend the idea that mastery is achieved through intensive practice in the appropriate context.

(12) Calling this the Feynman Technique may not have been accurate. It’s not clear that Feynman used this specific method, so perhaps I unwittingly gave the technique a notoriety it may not deserve. Also, one of Feynman’s great contributions to physics were the Feynman Diagrams. So the Feynman Technique could lead us to make diagrams, although they don’t have to be the actual Feynman Diagrams!

(13) The book Raise a Genius! was originally published under the title Neveli zsenit! I’m indebted to blogger Scott Alexander and his readers for providing an English translation.

#book-summary

Ultralearning (Spanish Edition) - Young, Scott H_