'Ultralearning' author Scott Young:
"What I’ve learned in business and in life is you’ve got to be a competitive compromiser. And that requires kindness, empathy, ingenuity but the same level of aggressive, competitive spirit."
Scott Young learned to speak Chinese in 3 months, and passed MIT Computer Science curriculum in 12 months. He then wrote a book called Ultralearning with 9 principles for learning any skill fast.
In this podcast episode, we talk about how to apply the 9 principles to 1) learning a language and 2) learning a tacit skill like marketing or copywriting
Connect with Scott at https://twitter.com/ScottHYoung
Find out more about Superlearning at https://superlearners.traverse.link/
hi today. I'm excited to have Scott Young on the podcast. Scott has learned Chinese in three months and he has done the MIT computer science curriculum. In 12 months. He then wrote a book about it called ultra learning. And in this book, he lays out the principles on how you can learn any skill fast, even if you've never written a single line of code or spoken any word outside of English.
He'll talk about those nine principles in the podcast. So let's jump in.
hi, and welcome to another episode of the podcast today. I'm joined by Scott Young. Scott Young is the author of ultra learning. And he did the MIT CS curriculum, how long was it Scott? Well, yeah, I did th this MIT challenge project that was over 12 months. Yeah. I, and he learned four languages in I think three months, each of as well, which was the first ultra learning project.
Right? Well, the MIT challenge was first, but I did the language learning after that, but yeah, those were two of the projects that I did. Awesome. Yeah, I think we'll have a lot to talk about this. Isn't your learning process in general, maybe? Yeah, maybe you can get a bit of an intro first.
Like what's your background and how did you get the idea of doing those ultra learning projects? Right, right. So I'm a writer I've been writing a personal website and writing essays and books and stuff for about 15 years. And when I was in university, that's when I started, I was writing about studying skills and like how people can learn better. Obviously as a student, this is something that was very relevant to my life. And when I graduated, I was really drawn to some people who were doing these kinds of learning challenges. Like they would take on some skill or subject or something like this, and they would do it in an impressive amount of time or in some sort of unusual way.
So people like Benny Lewis who was doing these experiments were going around to different countries and learning new languages or people like Josh Kaufman had the personal MBA project where it was him trying to like simulate getting an MBA. But just through self study people like Steve Pavlina who he didn't do it a self study, he did go to university, but he took like a triple course load and got a double major in math and computer science in three semesters. And so these examples, I think it really got me interested in this idea. And so the MIT challenge was the first project I did, which as I mentioned briefly in the introduction, the idea was to try to learn MIT's computer science curriculum over 12 months.
And the main sort of thing that made that possible was that MIT posts a lot of their material online for free. So they have lectures and they have a problem sets and solutions. And so there kinda is, you know, not a perfect curriculum, but there's like quite a bit there. And so it was sort of an interesting puzzle to see if you could proceed through it.
And then the 12 month constraint was also. Recognizing the fact that if you're going through it and you're focusing on a sort of narrower set of the objectives and passing the final exams and doing the programming assignments you may not need to have the, the full four years. So, so that was another kind of starting project.
And that kinda got me some attention. And so I decided to follow that with another project. I went with a friend and we went to four different countries to learn four different languages. We learned Spanish, Portuguese, Mandarin, Chinese, and Korean to varying levels of ability. I should add not to say that I'm perfect.
And all of that, maybe we can talk with you about since this map. But the it's a up Portuguese follow-up book with
Oh, you want to continue? I don't know. Let's switch. Yeah, sure. I've always felt drawn. When should that be with the high shirt? Now if anyone here is are broken Chinese and Portuguese conversation.
You're just saying that I think the process of learning languages we can talk about because the method that we used was sort of, when we landed in the country, we only spoke in the language we were trying to learn.
And that allowed us to create a, kind of a social network of people who are, we can practice with and just really added up a lot of practice time. So we were able to get, you know, not perfect, but like fairly good in a short period of time. And And then since then I've done some practice with the languages much more with Chinese than the other ones.
And we can talk about that too, that like maintaining, speaking multiple languages when you don't actively use them, as it turns out is like, it's quite challenging. But I think there's still a lot of value in this approach simply because I think that for a lot of people, the idea of learning a language when you only have a relatively short opportunity for using it, like you're going somewhere for two weeks.
Most people will be like, well, there's no point, like I'm not even gonna get close. And I think, you know, two weeks is a short time, so you're not going to be conversational, but I think. What I've learned in this process is that it's possible to get not bad at a, at a reasonable rate and in ways that you can do a lot of stuff that is actually useful and fun in a way that maybe, you know, yeah, you're, you're going to definitely, if you want it to work and live in that country, your whole life, then it's going to take you maybe a couple of years, at least.
But I think that this project kind of showed that, that sort of low end of getting into speaking the language is, is more doable than most people think. Especially given their kind of background, maybe with like, you know, you do a couple hours a week of a French class, or you play with Duolingo and you're like, oh man, I'm still terrible.
So I think there's, there's a lot of benefits to that kind of immersive approach, especially with language learning. Yeah, definitely. And then yeah, so I think it would be very interesting to talk to like two specific things which you'll learn, which has both like, well, Chinese, as we mentioned, and then you've also been fighting online, been an online entrepreneur for like forever and yeah.
Like way ahead of your time, I guess. And I think a lot of people are interested like myself. I'm an online entrepreneur in learning those skills as well, like writing, marketing, but they are very, very abstract and it's very hard to find a good way to write, to learn those effectively. So I think, I think you've talked about it in your last newsletter as well.
There's like more knowledge like things to learn and more skill like friends to learn. So , this is well, you're, you're kidding. Getting me on my, like I have, I'm currently deep in this sort of research process of like sorting. All these different viewpoints of like, some people say this and some people say the total opposite of that, and I'm trying to like, read all the evidence.
So there's still a lot that's going to shake out, but I can give some just general basic ideas that I think are broadly true. Whereas the details and specific sequencing and a favored pedagogical approach, that there's still some controversy about that. But, but I would say that when you're dealing with let's, let's use the example of marketing, I think because marketing is one of those things that it's not something you practice in the way that like you practice a language like marketing is like, well, you have marketing projects that you work on and they're kind of big, but there's no like, okay, you're just getting lots and lots of feedback.
And so I think the there's a couple ingredients that go into learning any kind of skill like this. Well, one is you need to have background knowledge with marketing. I don't think that's such a big problem. It's not quantum mechanics, but you know, still, you need to know like basic ideas of like, if you were to learn marketing in a specific area, let's say like, you're doing Facebook ads or something.
You need to understand how Facebook ads work. So, you know, reading some articles and understanding the basics is important. The second is that you need to have some kind of activity, I think, where you can test what you know, and where you can apply it. And so I think that's also something that's important.
And so I tend to be in favor of a kind of I'll call it like a practice centric view of learning because. There's ample evidence that when we just read a book, for instance we don't remember a lot of what we read. A lot of it gets forgotten and a lot of it doesn't get applied when you're in situations that actually need it.
So what you need to do is you need to be able to read the book, but then have a lot of experience applying it in the kinds of situations that you want to do. So for me, I tend to view learning in that lens of that. If you wanted to learn marketing the right way is to kind of pick off a particular section of marketing.
You want to learn read some books that advocate for some sort of exercises or practice, and then do the practice. And I think if we're talking about like online business, obviously the practice you want to do is applying it to your actual business. And so I think working on sort of small-scale projects where you can test out your understanding of these concepts is really important.
Now, if we're talking about like the sort of education. I want to understand marketing and go back. That can be a little trickier, right? Because now you're not just learning it to apply to a particular problem that you have, but you're learning it to try to have, you want to understand all there is about marketing.
And so I think, again, you can, you can do this, you can break it down into some books and read some concepts. I still feel like the the practice approach needs to be there, but what the practice is might change depending on how you want to use it. So, you know, the classic approach is just to do like find problem sets with solutions that you can practice marketing.
You can write essays, you can work on things. I think the doing part of it is, is something that's often neglected that we, we focus on learning just as I'm going to read this book. And then there is a kind of gap between that. And when we actually want to apply it, when we actually want to use it doing the real thing.
So I think that that practice activity is quite valid. Yeah, definitely. So what I think would be interesting is if we take like the nine steps that you came up learning and walk through them, like side by side for Chinese learning. And well, let's take the marketing example.
And one thing I hope to get out of this is to give a little background. We are creating those learning templates for our app that basically you start with a template and people can like fill in their own stuff and get started from there. And we have one for learning how to learn in general. We want to create one for scale learning, which could be like marketing and create more for language learning as well.
So yeah, ideally like this would serve as kind of the basis for those templates that we want to develop. Yeah, no, that's great. Well, let's get started I guess. So do you want me to go through and list the nine? Well, they're nine principles. I shouldn't say steps because they're not like intended to be sequential, but I do the first one is kind of logically first and the last one's kind of logical last, but the rest are kind of in a sort of a pleasing order.
They're not really necessary to be done in those order, but but should we go through. Yeah. Let's go through first one. There it goes. Let's go Meta learning, I think it's very interesting cause you have radicals. And did you approach that? Yeah, so I think whenever you're dealing with any complex topic that you have to study, you have to understand how it's broken down and what is it built out of?
Like, what is it, what would it mean to get good at this? You have to understand how it's broken down. Now, if you're in a classroom situation, you'd hope that the teacher has done this for you. I think that this can sometimes be a little misleading though, because if you go to university to study something often, what they will do is not teach you a sort of specific skills.
This is what you want to be good at. They'll just kind of be like, this is the domain, right? So, you know, when you're learning mathematics, they're just sort of, well, this is calculus and this is how you do calculus and maybe what you need to, what you wanted to learn calculus for was, well, I want to be able to use it to program video game graphics or something.
And so, you know, the calculus will be there, but maybe you'll be doing a lot of stuff that's not relevant to that or, or vice versa. Right. And so I think the right way of doing it is to figure out what it is. You're trying to get good at what it is that you're trying to learn. So if it's just a learning goal where I just like, I want to understand the history I still think it's useful to think in terms of like, well, where would I.
Like, what is it to have conversations? Is it general knowledge? Because even that suggests different applications. Like if you're learning history, you could be memorizing facts and just knowing lots of dates and having them stored in your head, or it could be like, well, no, I want to know what the general sweep of history is.
And I want to know like big trends and those are gonna suggest different kinds of things. But just taking a particular subject as a, you know, I want to learn Chinese. I want to be able to do all the things you can do when you learn Chinese, then it's helpful to break it down. So, you know, obviously with language learning, you've got speaking, writing, reading, and listening, and these help each other, certainly, but they are also somewhat independent to that.
You can be an excellent reader of Chinese, particularly Chinese, because it's not a alphabetic language. You can be an excellent reader and maybe not know how to speak at all. And obviously the opposite is also true that many people can learn to speak Chinese and, and don't recognize any characters.
So they're completely illiterate. And so I think that's the first thing to start is to sort of break it down into sections. And then let's say, we've decided we want to learn to to read Chinese. Then you have to know while there's all these characters, how many characters are they? How, how are they organized?
So you can find like if you were learning Chinese, for instance I really like my friend, all the lineages hacking Chinese website. He has a lot of sort of meta learning advice about learning Chinese he's a Chinese teacher and he spent time learning it himself. He's a Swede. He's not actually Chinese.
And because of his experience, both learning it and researching the pedagogy, he has a good understanding of how it works. So with whatever skill you want to learn, I think that's a really important first step is to set it up in such a way that you know, how people typically learn it. You know, what sort of like this is going to be the stuff I need to know.
These are going to be the things that I need to understand. These are going to be the things I need to practice, and that you're also sort of aware of maybe the breadth of the skill, but also where you want to use it. So again, with learning Chinese, I would advocate a totally different approach. If the person was saying, well, I'm going to go to Beijing and I want it.
I'm traveling there for two weeks versus I want to study classical Chinese literature. They just don't suggest it all the same kinds of activities. Maybe there's going to be some overlap, but at the same time, I think understanding how you want to use a knowledge is very important in, in the actual acquisition of it.
Yeah. And maybe let's just dive a bit deeper down the rabbit hole. Chinese characters cause that that's how I got into the whole learning, how to learn medicine stuff. Actually, the thing I found is an obscure blog post called like the Maryland method where you construct like this I don't know if you heard of it.
So this will be new for me. So basically you construct from the radicals of a character a story, but then you also take that pronunciation of that character. You break the opinion down and how to at the start. So for example, if you had you and you will have you, and, and then you would, would be tied to a specific person that would play a role in that story.
Obviously, An an would then be a specific location including the tone of. She's explained your mining method is what you're saying. Yeah. It's a monochromatic. Exactly. So it's kind of like, you create a lot of those yeah. Visual stories and almost placement kind of like, like a memory palace.
Right. But most of locations, so I would like to know. So that's a very interesting think about that. I think so pneumonics are very interesting. I write about them in the book later principle on retention, and I think that can be quite powerful. I also think that flashcards and space repetition systems can be quite powerful for language learning as well.
I tend to be a little bit more in favor of space repetition systems than pneumonics like, if you are only doing one, but obviously you can do both. So it's kind of often better to do both, but just because the space repetition algorithm, the idea that when you are learning something, so let's say you're learning a word is that there is an initial kind of let's call it like a binding process of the word has.
So with the Chinese, you know, character, you've got all the components, you've got the the initial, the final, the tone, and there's sort of what it means. And so there's a kind of like, you can imagine a little concept where there's various connections and what you want to do through practice is make the association of those elements more and more and more fluent.
Right? So that, you know, when you say the word in an actual conversation you don't have to like deconstruct it and figure it out, but there's obviously a problem that it's too complicated in the beginning. And so it all, a lot of it falls out and you don't remember what the tone was and you don't remember what the, so pneumonics are a kind of, I would say kind of scaffolding.
They allow you to sort of, when you're in the process of speaking, you can use the pneumonic as a kind of backup tool to figure out what was the right way to say this word. But over time, as it becomes fluent, you no longer need the pneumonic. You just recall it. And so space repetition systems work by having this sort of.
Quiz pattern recall kind of structure and they can be quite valuable because you'll know you'll get that repetition so that if you do it enough, you will memorize anything eventually. And then the pneumonic can sometimes be helpful to, you know, speed that up as well. If you're, if you're having difficulty remembering them or keeping them separate and this kind of thing.
And so when it came to learning Chinese, I didn't know this Maryland method. So I was a little bit weaker on the mnemonics. I used them a lot with European languages where you can do the keyword method, but the the approach was to just, I went through like lots and lots and lots of flashcards, and that built up a kind of a certain foundation of like, I have a certain storehouse of words that I can use.
And from that store house of words, you can have conversations, which lets you practice them in a real context and it lets you get used to their sort of shades of meaning and nuance. And so this sort of, kind of building up approach was a big part of learning Chinese. Now there's a couple sort of Chinese specific issues that I think are kind of interesting.
So one which is that a lot of, I don't know how common it is now. I think the tide has shifted a little bit, but a lot of like Chinese teachers that are from China who are teaching Chinese really emphasize learning the handwriting from the beginning, which I don't think is necessarily a problem.
Calligraphy is great. And if you love it, it's great. So don't get me wrong. I'm not saying that no one should ever learn it, but it it's sort of only very tangentially related to it's very tangentially related to speaking Chinese and even reading Chinese. I would argue. It's often easier to learn, to recognize a character than to handwrite it.
And so if your goal were to start reading Chinese I would definitely not make handwriting the prerequisite step. I would, you know, you could learn to hand-write maybe a handful of characters. But I would focus on like recognition flashcards, where you have the character. And then what does it mean rather than production ones where it's like, here's the.
Pronunciation and meaning, okay, now you have to hand write the character that matches. Yeah. And so that's an example of, of what we're talking about of like tying your goals to the actual learning process. Because I think there is often a mistake that comes from some Chinese teachers that, you know, Chinese kids, that's what they start doing is they learn handwriting.
But of course, Chinese kids already speak Chinese. So it's not really like, it's not, you know, and also if you're going to be a full participating member of Chinese society, you probably do need to know to how to write the characters. So I'm not saying that it's useless in that regard, but it's maybe just a bit of a peripheral activity to actually speaking.
Yeah. I think this is where tools are very interested as well. I went with a mobile phone, basically, when you have opinion keyboard, it turns up the writing process from writing until actually the recognition process, which means it makes it much easier. Yeah. And I think the other thing too, is that technology has also enabled a lot of things that, like, I think the handwriting emphasis has also been superseded by technology in a lot of ways, because first of all the way you used to have to learn to read was you'd have to look up and in big dictionaries that are organized by radicals.
And so it was very difficult to do that. Whereas now you can use something like black co and have their document reader and like you just tap and tap, tap, tap, tap, tap, and figure out what words mean. And so that's not like, you know, that that's also not an issue anymore. And when you're actually, if you're interacting with people in China or in Taiwan or something like that, then when you type the characters, you can use the opinion.
And so I think this is a sort of also an example of how there's often like a Scholastic way of learning a particular task and it can be beneficial. I don't want to say that it's useless, but. It often sort of stresses certain components, which are kind of, they're important to the idea of the skill, but they're maybe not as important to actually practicing it.
So, you know, maybe we can get into it a little bit, but like another example would be like machine learning. I know there is a kind of like the academic path is to like start with linear algebra and calculus and vector calculus and work through lots of equations. And then you start doing, you know, gradient descent and you understand it turns the gradient and this kind of thing.
Whereas nowadays you can just, a lot of that math is encoded into the packages you use. And so you can just start doing like, you know, with your own data sets and stuff, you just need to understand roughly how the algorithm works. And so there's a little bit of a split sometimes with people who are, you know, kind of really mastering the deep fundamentals and people who are kind of more sort of practitioners who, maybe they are not understanding every single detail of what they're doing, but they're able to get the results that they want.
Yeah. That's very interesting. Cause my, my last job as a data scientist, like I just said that we actually called that method like import machine learning where you just import a library or anything for you, you basically don't need to do it. Don't need to know anything about the mathematics behind it, but then there's also a danger that it actually can lead to.
Like analysis, which don't make any sense because you didn't understand the basics well, and I think that's it. I think there's always the trade-off right. Like I think it, you know, the more, you know about something, the more deeper you understand it, the better you'll be. And so that's true, you know, obviously if you know how to handwrite, you're in a better situation than not knowing how to hand write.
Obviously if you understand the math behind machine learning, then you're better off. I think you know, this is sort of another question. It's also one of sequencing too, because you know, you can imagine you and then the mastery level, and there's a sort of, I would call it kind of two philosophies of this approach.
So one would be to start with the very basic, so like kind of the first principles and then build up to whatever actual task you're trying to do. And the other one would be to start with kind of the task you're able to do. It has to be something you're able to do, but start with kind of the tasks you're able to do.
And while sort of working with it and getting proficiency. You're also learning some of the theory and stuff. And so I tend to be more in favor of the latter approach, but as you're right, it's definitely true that, you know, someone who has a PhD in mathematics will understand machine learning better than someone who's just, you know, downloaded Jupiter, just playing around with it.
But I think there's definitely situations where you know, like we said, with the language learning that you know, having the perfect handwriting and having the perfect understanding of all the characters before you have a conversation, definitely puts a barrier in front of having a conversation.
Yeah, definitely. So if we then like shift to the opposite side of the spectrum, so if we look at meta-learning for, let's say, let's say marketing, so one thing I tend to do, and I don't know if this concept's meta-learning is, but just. Taking a look at the space and see who are like the best people in, in marketing, like maybe on Twitter or whatever.
And they find a couple of people I like, and then I just, just start following them and try to imitate what they do. And that that's kind of how I start learning a new skill. How do you see meta learning for abstract skills? Like, well, so there's kind of two parts, so you're saying abstract. So I think like you could say like calculus is abstract, but, but it's also some wrong word.
I would say, I would say it's more, it's not so much that marketing is abstract, but that a lot of the skill itself is kind of tacit that it's not really written down anywhere. So that being a good marketer is not really that related to it. And so I think. You know, this is one of the reasons, one of the themes of my blog recently has been talking about apprenticeship learning.
And I think the issue is that there are certain things that schools teach very well and certain things that probably, I would not want to learn outside of school, but there's also things that it seems like schools don't teach them very well. Like people take the class and they don't seem to be that much better at whatever they're doing.
Or they, you know, they know a lot of theory and facts, but it has nothing to do with what they're actually practicing. And so the idea of the apprenticeship process is that someone models to you, what's the right way to do this. You look at it, you understand it, then you try it yourself. And then also, hopefully they give you feedback or you get feedback from the environment on the right way to do it.
And the advantage of this approach is that the actual written out as an explicit description, understand. It doesn't have to be there. So the apprentice, the master does not actually have to understand why they're doing it that way or what the rule is. And I think that's you know, that has a strength and a weakness.
So the strength of it is that it really that's how we have to learn lots of skills because there isn't a really good, you know perfectly spelled out theory of it. You know, like mathematics tends to be like the exception to that, but you know, even just like being a good computer programmer, for instance, well, yeah, the concepts of like a variable and a function and efficiency, if you can teach those, but like what makes.
Coding design elegant. And what makes us, you know, th th there's a lot of aesthetic there, and I think there's quite a bit of aesthetic even in fairly technical fields. And so the idea of the apprentice relationship is that if by emulating the apprentice, you can sorry by the apprentice, emulating the master, you can sort of adopt their practices and make them your own, even if the exact rules for doing it, aren't always specified.
Whereas in school subjects where, you know, you learn about the skill, but you're not doing a lot of that, seeing examples and getting practice, and then it can often go off the rails where you know, a lot about marketing, but you're not actually good marketer. You just, you just know what the four PS of marketing are and, you know, the difference in pushing people, but you don't, you don't actually like, okay, here's a concrete situation with this product.
Okay. How do we market it? You know, it's difficult, right? Because what you know is not organized in terms of actually solving. Yeah. And I think that goes like into the, I think third step on the. At principle, which is like the directness and basically said it often learning by doing the exact skill that gets us to like get the deepest or most facets knowledge of it.
Now in the case of language learning. I guess we would be looking at something like immersion, right? Yeah. I mean, directness, the idea of directness is basically figuring out what you want to get good at and doing a lot of proc practice that matches that. So there are some weaknesses to this, just that.
You can definitely pick a skill that's like way too complicated. So if you want to get good at calculus and you don't know arithmetic, like you're done, like it's not, you're not gonna be able to do it. So you have to build up to it. So I think there is an understanding of prerequisite knowledge and this kind of stuff, but at the same time, if you want to get good at speaking a language, then practicing speaking, it would be the direct way of doing it.
If you want to go to a reading, it would be reading. So this is a little different from there's certain language learning kind of enthusiasts who have, I will call it like the right way to learn a language is to start with this, right? So there is the input people who are like, no, no, no, no delays speaking as much as possible and focus on listening.
Cause it helps you understand the language and it, you know, if you want to be a fluent comprehender before you're a fluent speaker. And then there's the you know, Benny Lewis speak from day one types where they're like, no, no, no, no, you need to start with speaking right away. And all this stuff is wasting time.
There's the school learners where you have to understand my point is just simply that. The approaches are probably going to converge given enough time and exposure that someone who spends a lot of time speaking, eventually you're going to get good. You'll hopefully start listening and reading and stuff.
You'll probably reach the same point, but the directness idea is just sort of that, well, if you wanted to speak, if that was your goal, then speaking is probably the way to get good at that. And if you wanted to understand things, then listening would be the way to get good at that. And so they definitely synergize, but I tend to be more of a favor of like, what are you planning on doing with the language?
You know, if you're living away from the country that speaks it. And most of your engagement is watching movies or television shows or something. Then I think the input hypothesis is like, totally correct. But if it's like, no, no, no, no. I want to be like, I'm going traveling. Or I want to be able to interact with friends that are doing this and have conversations then having conversations is certainly the starting point.
So I think this is this idea of directness is a kind of a matching activity of figuring out what you're trying to actually get good at and then matching matching the practice process to that. Yeah. And I think that's very interesting, especially now since, I mean, there are a lot of travel restrictions.
It's not so easy to just go to a country and immerse yourself into that. So like what would you do instead if you, if you want to have that immersive experience and be able to actually transfer that to when you are able to go to that country. So I think immersion is both is both underrated and overrated.
So. It's underrated, it's overrated in the sense that a lot of people really focus on living in the country that speaks it. And in my mind, that's the least important part of immersion because like, yeah, it's great to be in the country that speaks it. You get lots of opportunities and, and whatnot. So I don't want to deny that, but it's, if anyone, if you've ever traveled, if you ever know people, who've learned languages before many people can live for many years in a country and not learn anything.
So it's certainly not, it's not, I wouldn't say the important criteria. For me, the important criteria is of immersion is that you are in a situation where you have to use the language a lot. And that has to use is the key part, because you can go to another country and find ways not to use the language.
You can find ways to, you know, make friends that only speak English and, you know, communicate with points and grinds when you're in the restaurant. And you know, find the one person who speaks English and then there'll be able to help you out. And so I've found like my wife speaks Macedonia.
She she was born in north Macedonia. And we did a little immersion project at home where it was like, okay, well for a month to each other, we're only going to speak in Macedonian. And I, you know, that plus some other study and stuff got me to a point where I was able to have conversations you know, decently well with her and we, I didn't, I wasn't in Macedonia at all.
Right. And so I think the focus there is how do you create an environment where you are required to use the language in real situations? And that's how you build that skill. But again, it goes back to my original point that you have to think about how you want to use. Knowledge you're learning.
And I think that becomes that distinction becomes increasingly important. The further you go on, so we can talk about experimentation a little bit later, but the idea is that, you know, the beginner course for anything is probably going to be pretty similar. Like, you know, it doesn't really matter what you want to use Chinese for you.
You got to learn a few, like you got to learn the hallway, you got to learn like a few things like that. But as you get better and better, the amount of patterns let's say that are contained in the subject just goes up exponentially. And so the choice of which ones to learn becomes increasingly important.
And so this is a sort of you know, I think the more that you can tie that to how you're actually using it the better, but that's sort of the idea of directness is just that when you spend a lot of time practicing a skill, that's not quite the skill you want to get good at often the transfer is less than you'd think it is.
Yeah. And then a lot of the principles is the focus. So you often do those ultra learning projects. Like you just mentioned, like immerse yourself in a little Barcelona for one month, but yeah, I think a lot of people don't have the time or opportunity to do that kind of focus. So there are a lot of autumn methods, like for example, Pomodoro timers, where you're focusing on a much smaller scale for 25 minutes, then five minutes.
So what are your views on that? Is this like long-term focus necessary or does it translate into like smaller scale focused? There's two main ideas from focus. Number one is that learning requires time. How, how intensely the time commitment is. It's not what's super important, but it does require time.
And so, you know, the, the right way to think of learning a language is it's not how many months it takes to learn a language. It's how many hours, because ultimately it's the hours that result in learning a language, not the months. I think there's, in some ways, a benefit of stretching the hours out over a longer period of time, that's shown to increase retention.
Although there are some situations where what we could call mass practice of putting it in a short period of time can be beneficial. And we can, you know, the mask spaced, there's lots of distinctions like that as well, that applied to learning. But I think I'm thinking learning in terms of how many hours, rather than how many months or years is, is really key.
So if you're only spending half an hour a week, it will take you an extremely long time to learn a language. But that's one of the reasons I suggested this immersive approach is because it converts a lot of like regular activity into practice. I think that's one reason why, if you know you can find a project in your job that forces you to use this skill, or you end up doing way more practice because we got to do your job.
But if it's something that's outside your job, you made me only have a couple hours a week. And so that in those cases, sometimes even a less efficient method, but that enables you to do it a lot can, can make make a big difference. The other aspect of focus is learning requires kind of all of your mind and mental bandwidth.
And, and so if you are, you know, distracted, if you are kind of like doing it for two, you know, you're doing it while you're also doing errands and this kind of thing, it will be less effective. And so I think that's another problem in some cases is that if you're learning something that's actually difficult.
If you're learning, you know, mathematics, if you're learning languages, even if you're learning marketing and stuff often we don't devote enough focus so that we're not actually giving it our concentrated attention. Now, as you said, Pomodoro can be great. 20 minutes is good. There's certainly some activities that require more than 20 minutes.
So I don't want to state a rule, but you know, if you're doing flashcards, maybe you only need. I think you could probably do it with five minutes. You know, just because all that's really needed is to look at the flashcard, answer it and put it back. But at the same time, I think, you know, like what we were saying with directness, if you only do flashcards and you don't actually speak the language, you're going to be missing a lot of the components skills involved in speaking.
And so, you know, flashcards are good. You can insert them into your day. You know, that's the same thing with Duolingo. It's something you can just do whenever. But I also hesitate that there's often a tendency to just, well, this is the easy thing. So I'm just going to keep doing that and I'm not going to do the thing I'm actually trying to get good at.
And that can also create. Yeah, definitely. So, yeah. You mentioned flash cards. So I think that goes into one of our principles, which is like drilling the weak points now for like learning a language it's, it's kind of a fairly straightforward you have either like where like vocabulary or maybe sentences grammar.
But then one thing I've been thinking about is how can we use flashcards for like tacit skills, like marketing. And I'm almost thinking in the direction of like, like periodic reflection prompts or something like that. Is that something you've given thought to. So I think that, you know, first of all, I should say that this view that I hold about flashcards is not universal.
So if someone wants to see the like super pro use flashcards to learn everything, I recommend that they look up Michael Nielson. He's very smart, much smarter than me. And so if you, after listening to this is like, well, I don't know about that. Then you can talk to him, but I tend to use fash cards for much more restrictive purposes.
Basically I use them for things that I need to memorize and that have a clear cue response prompting. So things that are good for flash languages, memorizing facts. You know like, so facts could be you know, in a, like they could just be, you know , what's the distance between the sun and the earth.
If you wanted to memorize that, you could do that with flashcards very easily. You can do it with somewhat more complicated information, as long as you can break it down into queue and response. So if you have like, you know, I used it when I was learning anatomy. When you have like a, this is a picture of the brain and all the brain nerves, and you can kind of blank out the answers and then you just have the answers on the back.
You have to do them one at a time. So you can only like, the question should only ask one thing, not that reproduce this whole map, but. But you can see that the relationship is queue response, queue response, and you're trying to make that totally automatic. And the problem there there's, there's, there's two problems with that.
One problem is that for a lot of let's call them conceptual skills. It's difficult to actually break them down into those Q response situations. So, you know, if you're learning like quantum mechanics or something like that, it's often difficult to know what that, what is the actual relation and the other thing too, and this is sort of goes to the tacit knowledge often.
What we're actually trying to get good at is we are trying to generalize from a, let's say. A kind of a particular situation, right? I need. So I'm sort of drawing from this situation, some sample of like, this is a problem and I need to deal with it in a particular way and get a result. And so this is not isn't to say that you couldn't do it with a kind of spacing algorithm, but it's just hard to do with current flashcards, because what happens is that.
Two different problems. One problem is that you only use a few representative examples from that. And so you memorize those representative examples, but you don't cover the whole domain. Right? So if you're learning sentences, for instance, you get rich, you memorize those sentences, but you don't memorize all the other possible sentences.
Right? So it's, it's just, there's a sampling problem there. Or you put all of them in there and which gives you way too many flashcards. And you're doing kind of, I don't want to say overlearning, but you're kind of, you, you maybe don't want to have that much practice. Like, you know, you don't have like 10,000 flashcards for a particular cue response relationship.
So I don't know. I think. I'm sort of optimistic that you can use flashcards for some things. And there are certainly people like Nicole Nielsen who have sort of taken a bit of a different approach where they've they formulated the sort of cue response relationship a little bit differently for complex subjects that I don't know, maybe as useful.
But I definitely feel like the, if you are dealing with a complex domain, then doing the sort of complex. Practice should be your sort of basis point and then the decision of what to memorize should come from. Ah, I'm not getting enough practice on this, or so for learning a language, for instance, it's, it's really clear that like often you forget words, like that's the major problem, so, oh, I'm using this word, let me put it in my flashcard deck and memorize.
It is really helpful. And I would even argue that memorizing words that you don't use a lot or that you, sorry, not that you don't use a lot, but you haven't encountered yet is still helpful to give you that base so that you can have conversations and stuff. And so I think that that that having that base is useful.
So just memorizing. 1, 2 thousand words, just to start having conversations is probably useful. And then I would also say that you know, as you encounter things like I keep forgetting this, or I don't know what this is putting it in your flashcard deck, very helpful because it lets you separate off the memorizing activity and making sure that you memorize it.
But at the same sense, I don't think it's possible to substitute like actually speaking with the activity of doing flashcards because then you end up, you don't have good. You're not able to bring the skill together properly. There's lots of issues that, that make that hard to, to sort of completely substitute.
So I tend to view it as a tool that solves a particular problem. And if you know when to use it, it can be really powerful. Right. Yeah, definitely. And I mean, that touches up on like the fifth principle of retrieval practice as well. So how would you then apart from flashcards, which might work for some people, but yeah, maybe not for most approach, like drilling your weak points for three doc practice for say marketing or copywriting, for example.
Yeah. So let's use the, let's use the issue of copywriting. Cause I think it'll be a bit easier. The marketing is going to be a little bit harder to drill unless there's some sort of idea of a drill is that there needs to be some sort of repetitive activity, like ideal with this situation and I get better, right.
And so there's a few different ways you can drill. So, one way we talked about is to isolate, to pick out some component of the skill and do a lot of practice on its own. So this works for lots of things. If you're learning basketball, doing layups practice will make you better at layups. If you're learning tennis, practicing your serve, you know, thousands of times we'll give you more practice than just doing it in games.
So I'm not against doing isolating drills. But sometimes it's hard to take one part out of the whole. So if you're learning copywriting, it's very difficult to write headlines without having, you know, something else to write about, you know, that you just, what are you going to do? You just write headlines, but you don't have any real good feedback of whether they're good or not, because you don't know what is going to go below them.
One is a kind of emphasizing methods. So you do the whole task, but you give special emphasis to a part. So this can be, you know you are skiing for instance, and you just really focus on making very smooth S-curves the whole time. Right. And that would be different from let's say, okay, I'm going to focus on skiing in a different environment, or I'm going to be going faster, or what have you, you know, those are different emphases.
So it's sort of, what do you pay attention to while you're doing the skill? You give extra attention to some aspect that you want to improve. And this can be helpful because often there's so much going on in the task that you're not able to perform it very well. And so giving extra attention to some component part can allow you to get better.
Yeah. While also giving you the actual context that the component is performed within which, which is beneficial or on in some cases necessary for many skills. Another thing that you can think of for drilling is to just focus on how can you get feedback that is more specific to the thing that you're trying to get good at as well.
The major weakness of a lot of our complex skills is that we're making kind of, we're making mistakes in one thing, but it's hard for us to see them in the context of the whole. And so, you know, like if you're wanting to get good as a writer, then you may want someone to be giving you feedback on some aspect of your writing, you know, like storytelling or this kind of thing.
So there's lots of different ways you can do drills that. But I think the essential function of drills is the same in all cases that you have a limited amount of mental bandwidth. And by focusing on an aspect of the skill, either in isolation or through emphasis or through, you know, better feedback, you can change how you're doing it so that you'll perform.
Yeah. I think that's very helpful. And then, yeah, you mentioned feedback as well, which is another one of the principles. I think it's a very interesting one because obviously yeah, if I'm studying computer science at MIT, I get immediate feedback. I pass the exam or I fail if I speak a language, you know it's a bit more, it's still pretty clear, right.
People understand me when I talk to them or they don't, but then if I do something like copywriting, I write something, I put my article out, maybe there's no reactions at all. And I don't know what's going on. Like, it's my headline. That is my article. Not interested that I posted in the wrong places. So how can we get better feedback and those, those yeah.
Very toxic. Yeah. So there's two ways we can talk about doing this. So one is like, let's talk about just the overall goal of improving your copywriting, because I think feedback is an important point, but I think there's other techniques that matter as well. So the idea of feedback is.
If ideally you can get feedback from an expert and they can tell you what you're doing wrong and how to fix it. So that's obviously better than just, okay. I'm just going to wait and just try stuff and see if they see what will work, but that's often not available or it's not available for the skill you want.
We, you know, we don't all have coaches telling us exactly how to do it. And so I think there's a few ways you can do it. One is to look at metrics. So, you know, the way you can measure aspects of your performance and then vary what you're doing and see how to improve. So this is a kind of like it's trial and error, but with feedback.
So you learn better with that. And I think you can also try to seek out environments that will create feedback. So that's another sort of, you know, if you want to be a standup comedian, you kind of need to go to open mics because yeah. You can tell jokes to your friend, but you're not really going to get the feedback you need to figure out what's funny and not right.
Whereas he's tending on Mike and they boo you and you're bad then you'll know. Right. And so I think part of the feedback issue is that we are often it's very stressful, right? It's very stressful to do that. And so we avoid doing it even if it's what would result in greater learning. The other thing I think is.
Let's say you're learning a complicated skill, like copywriting or like marketing or this kind of thing. I think a sort of an underrated approach to getting good at those skills is copying some exemplar. So finding someone. So for instance, if I like, you know, I've done this and I mean, once you actually finished the book, it changes quite a bit.
But I did this process of like, when I started writing my book, I read some books and I used what is the structure of this book to, to structure my book. And then as I wrote it, it ended up changing a fair bit. But the idea here is that I don't know how to write a book. Let's find examples of good books. I like and try to copy whatever the structure is.
Now this can be difficult to do in some circumstances where you're not sure why they're doing it in a certain way. And so there is a kind of the critique of this is that it's mindless copying. You're just, you know and you can see that in someone, if like you don't get good at writing essays by just recopying someone's essay verbatim, but you could probably get better at writing essays if you were like, okay, here's an essay.
I really like, how could I sort of, what are the main elements of it and how could I sort of repeat those exact main elements in sort of a slightly different essay or maybe using the same topic, but I'm going to, you know, use my own examples of this kind of thing. And so this idea is just that kind of by finding something that you, a process or a method that works and kind of following it fairly rigorously in the beginning, you, you just basically you limit how much trial and error needs to be done.
You're kind of, you can find it to, okay, well, I only really need to experiment in this range because I've already found something that works pretty well. So I really liked the idea of, you mentioned data science, but. In, in sort of machine learning this idea of like pre-training and like, basically if you want to use a neural net to solve a task, you find a neural net that was kind of like pre-trained on the same kind of data, and it's much faster to train your neural net than just some random you know, neural net that you're using.
And I don't want to draw the like brains or neural nets connection to too strongly, but there is something similar there that, you know, by limiting the problem space to something that, okay, well, I'm doing it basically the way this other person is doing it is very valuable. And so I noticed in my own skill development as a writer, if you look at my earlier essays, and if I told you who I was like following, you're like, oh, these essays are exactly like so-and-so's essays.
And so my unique style developed much later. And so I tend to be of the view that. We tend to put requirements for creativity and originality too early on learners that, you know, we want them to produce something original. And like for instance, learning art, we were like, you know, it's about being expressive and original from the get-go.
Whereas it sort of like, is it though, or is being a good artist, having a certain mastery of you know, certain types of media. And then when, you know, like all these various sophisticated ways of expressing yourself, then you can combine them in a way that's like truly original. And so I tend to be more of a fan of the you know, that approach where you sort of, you have the basic tools and then you can go and do something.
Yeah. Like, I mean, what's Picasso set like the artists, good artists copy, great artists steal, right? Yeah, no, it's true. It's true. And I think that's another area where like academic norms can sometimes be. Stifling because you know, there's a lot of emphasis against like plagiarism, for instance, that like you can't copy someone's homework and you, you can't plagiarize.
You have to do it yourself. And there's a reason behind that. Obviously plagiarism when you're publishing work is bad, don't plagiarize. But I think some of the issue there is that that's not how people used to do things, you know? Like how do you become a good painter? Will you like coffee? This person's exact painting until you figured out how they did it.
Like, I think that kind of finding an exemplar and copying it, isn't a really underrated strategy and it's something that people will kind of like only sheepishly admit to that. Oh yeah. I looked at so-and-so stuff and I tried to do something very similar. And so the fact that this is a learning strategy that people use covertly I think is also kind of evidence that this sort of prescription against it is often wrong.
Yeah, definitely. Then we spoke earlier about you know, kind of, how do I retain a skill, for example, a language I haven't haven't used it in a while, which ties it up the seven principle of retention. And I think I actually noticed it's very similar for skills. Like in my case, it was audience building.
Like I did a lot of audience building for like my app, like six months ago. And then I went to like deep into the technical stuff, build all this technical stuff. And now one month ago I tried through audience building and it was like, well, I've lost this company. They need to relearn it. So how can we kind of retain skills better?
I will say that forgetting is a kind of universal part of human cognition. And I mean, there's some people who have argued that forgetting is adaptive. So it's not even. You know, we like the idea of remembering everything perfectly forever, but people who have certain kinds of brain deficits where they actually do manage to remember a lot are often you know, in terms of intellectual functioning far below.
Now, I don't want to say that it's like entirely causal, but it definitely seems to be the case. It's organized in such a way as to remember virtually like with perfect recall every single detail you wouldn't be very intelligent because part of what it is to be intelligent is to abstract things away from the experience and to strengthen particular patterns as they become more useful.
And so I think this sort of adaptive brain hypothesis does suggest that we forget things that we don't use. Right. And so, you know, for me, for instance, like I've learned these other languages, I don't practice them as much as I'd like to. I have a toddler at home. And so they are getting weaker, but that's sort of adaptive in the sense that.
Brain in this sort of, if I can speak about it as if it's an actor, my brain sort of recognizes, oh, you're not using this right now. I'm going to strengthen my English speaking ability or the other kinds of behaviors that would come out of these situations. And so I think that there's a few strategies that you can use to help retain things.
One is to spread out practice over longer periods of time. This is the spacing effect. One is to proceduralize skills. So the idea is that skills tend to have a declarative representation when you are thinking about it consciously and executing it. And there's a procedural representation where it's just like the flashcard, you see it.
And then, you know, the answer on the back and the idea is that the procedural representation tends to be more durable. It's less flexible, but it's more durable. And so, you know, a good example of this is like, if you're thinking about typing your password in, on your computer, that. You at the first point, you were thinking of what the word or letters or numbers were and you're typing it out.
And then there was a point where you weren't really thinking about it and you're typing out, but you still know you still have the kind of the explicit memory, but there's some times when you've been using a password for so long that you actually forget what it was and you have to put your fingers on the keyboard and do it otherwise, you won't remember what it was.
It it was it this, or this, and you actually have to type it. And so this is an example of the kind of like it's sort of pejoratively called muscle memory, but procedural learning applies to cognitive skills. It's not just motor skills, but the idea is that once it becomes totally automatic, it becomes stored in this like more durable, but very specific kind of program.
And so this is one of the reasons that I was in favor of the current. Immersive approach for language learning, because the way you learn it in school is often you don't because they're trying to cover the whole language. In the limited class time, you don't really get to proceduralize any of the components.
So the actual key phrases that you need to function in the language, you know about. They're in there, but they're not at that fluent processing level. And so you can get into this weird dissociation where you have people that have considerable linguistic knowledge so that they are in some ways more expert, but because they haven't proceduralized it, they are not fluent.
They do not speak any fluent way. They cannot engage in conversations. But if you were to say, well, how do you say this? They'd be like, oh, it's this right? Like they, they can do it. They're just not actually fluent with it. And so I think that's sort of you know, it tends not to happen because usually with lots of practice, you know, more and you're more fluid, but it is possible to dissociate those two.
And so I think that's very interesting. So definitely getting to fluency with skills is another way to make them last longer. And I think ultimately, you know, I would say the real advice here is that, you know, given this adaptive mind, I bothers us. If you use something regularly, you'll remember it.
And if you don't use it regularly or you don't need to use it regularly, you will forget it. And the. The research on relearning is fairly optimistic. So people will forget so much that they cannot perform on tests that they had passed before. But if you give them a chance to relearn it people tend to relearn things much more quickly than they learned it the first time.
So that's sort of, maybe that's just me, you know giving myself a little bit of an out, given that I've spent so many years learning so many different intensive skills that I'm not able to practice as much these days, but I think it's definitely not the case that. You know, the things that you learned from high school are totally forgotten, even though you might think they are it's because if you went and relearned it, even if you have no memory of the specific lessons anymore, you'd still learn it faster.
And so I think that's a little bit hopeful that what we learn is still in there. I would also recommend people there the psychologist, Robert Bjork has this hypothesis that we never actually forget anything that a human memory storage is actually infinite. But our recall ability of memories is limited.
And so as we learn new things, old knowledge gets less and less retrievable. But, but if you were to relearn it, it's kind of still in there in a sense now, I don't know whether that's entirely true. Clearly the brain does not have an infinite storage capacity, but it may be more true than we think that, you know, things that you learn are, are kind of still in there.
They're just not accessible. And so, you know, if you spent a lot of time learning something very rarely do you have to spend quite as much time relearning it as you did learning it the first time. Yeah. And so you mentioned one of the things to better retain the skill is to get really fluid in it, which I guess translate into almost getting that intuition, which is another of the principles.
Right. And again, intuition is very interesting, I think like for our language, like we kind of have an intuition when we yeah. Speak it like naturally. But then for skills like math or even copywriting, there seems to be people who just have that kind of intuition almost like are a genius in that particular skill.
Right. So how do you see geniuses? I know you wrote about this in the book. Can we actually get to the level of a genius or is there some part of this intuition that is kind of inherent well there's opinions vary. So I quoted a Andrews Erickson who tends to be on the extreme, let's say extreme environmental or like learning view that kind of any skill is learnable by anyone.
And that with large quantities of practice, like large quarry of means of practice are necessary and important for, you know, expertise. He's kind of the 10,000 hour rule guy. But then you have other thinkers. I'm trying to remember his first name, but it's Haier, aren't going to be that maybe I'm getting it wrong, but he is a neuroscientist who specialized in intelligence, who has very much the opposite view that we have like strong, fixed innate intelligence that is not improvable through any kind of practice other, you can make it worse through having that diet and exercise and stuff, but you can't make it better than just being normally healthy.
And this sort of like strongly constraints, how quickly people learn in this kind of thing. My own feeling is somewhere in between. I think that certainly some people are smarter than others. I think that makes a long way to explain the extreme ends of performance. So people who like Albert Einstein clearly smart, you know, I don't think you can become Albert Einstein just through practice.
But I think that what we know about learning shows that if you like take someone who has no practice and lots of practice, the things that the person who has lots of practice can do are impressive. And that's from a change in the structure of your long-term memory and the, the sort of there's been kind of a wave of research in artificial intelligence and human cognition and sort of the early wave was the idea.
Well, we're going to give computers these sort of general purpose methods, and they're just going to be really good at them. And that's how they're gonna, you know, perform well. And it turns out that that doesn't work, that in order to perform well, you need to have tons and tons and tons of domain specific knowledge.
And so the idea here is that people who spend extensive periods of time interacting with a discipline just build up huge libraries of this information and it makes them smarter in that way in the, in the doing things that they're used to doing. So the classic experiments on this had to do with chess chess, masters who chess masters did not.
So this is a study by DeGroote found that the chess masters and the sort of more casual players did not differ in terms of how they thought about the game. Like it's not like the chess masters were faster thinkers and they analyze more moves and they were, you know, all the only difference seemed to be that chess masters had a larger library of internally stored patterns in chess.
And the way that they showed this was that if you give someone a sort of random chess board and get them to reconstruct it, the better players can do this better. And but if you give a randomly, so you just randomly move around the chess pieces so that it's not something that would ever happen in a game.
The chess masters do not do better than people who are not experienced with chess. And this suggests that much of what they know. It's like, oh, this is this position. And the night was forking the queen and the rock and you know, and oh, it was like this and it was like that. And this kind of. Elaborate set of chunks allows them to think more smoothly and effectively in going through the game.
And so the idea here is, is sort of that you know, just as in learning a language, depends on knowing a lot of words, learning any domain or skill depends on having a lot of individualized facts. And so we tend to we tend to exaggerate when we view the sort of skill being learned as a sort of monolithic ability.
So the kind of metaphor that I rally rail against is this sort of the mind is like a muscle. And so I just do a lot of like kind of bulk practice, like, and just get really strong. And so this is sort of the, I think, mistaken intuition behind things like brain training, which is the idea that if you just do some narrow kind of practice activity and you just get really good at it, that you'll just be smarter in all sorts of ways.
And there's lots of research showing that brain training doesn't work and the better metaphor is probably. It's a little bit more like an organized library that like, if you have more and more and more books in the library, you just have more knowledge. You can just handle things better. Now it's not a perfect analogy because it has to be organized and structured.
Well, so we can also talk about how the file cabinet metaphor, the mind doesn't work either, but I think it's a better than the muscle analogy. Right. Yeah, it is. It's very interesting to find them a good analogy for the brain. Almost impossible. I would say. I guess that brings us to the last principle, which is the experimentation.
So we talked a bit about expectation before, like what can we do to experiment with language? What can we do to experiment with, I don't know, marketing copywriting, how can we approach expectation? So I think this is sort of going back to what I was saying before that, like in the beginning, phases of learning a skill, your goal should be to sort of reduce how much you have to experiment.
Like, you know, find a method that teaches you how to do it, like constrain the problem space. So you're not just like trying a bunch of random stuff, but as you get better and better, there's two problems. First you run out of learner materials, right? There's like learning materials are overwhelmingly weighted toward the beginning.
End of the spectrum. And then second The there's a kind of an increased, like the skill kind of goes like this. So that like the amount of words that are the beginning of a language or here, and the amount of words that are at an intermediate level or here and then expert, it just goes up and up and up and up.
And so, you know, some of this is this idea of directness figuring out what you want to be able to do in the language that you're learning the right words. Some of this is also you know, related to a performance. So I'm thinking, you know, artistic skills are clearly something that is probably good to have some basics of like understanding how light and shadow work and line and how you apply paint.
And, you know, these kinds of things are going to be universal to painting, but developing a style, you have to experiment, you have to try things. And so one of the, you know, this is an artistic lesson that I learned which I thought was very valuable is that good artists build what is called like a visual vocabulary, which is that they have certain ways of representing things, which to the, to the viewer, they just say, oh, that's a tree, or that's a cloud, or that's, you know, a person, but they're done in a very particular way.
And that's what makes the artists unique. And so there, while it's a mistake to view the opposite lens, that we should be getting people who have no experience painting to develop a visual vocabulary, there is also a truth that in, in developing a unique style, you have to develop one and it has to be unique.
Otherwise you're not a unique artist, right. And so there is a certain amount of experiment. Whereas you figure out, okay, well, this is how I hold the brush, and this is how I do this. Some of this is unconscious. You just develop it automatically because, oh, this worked last time. So I'm going to do it this way.
But sometimes it's very conspicuous. You sort of, you make decisions about how you're going to do something that, that works for you. And so I found in my sort of evolution as a writer, my early phases were very much kind of in the emulating and, you know, trying to find methods doing what works. And now I'm often ignoring advice that people give about what's the right way to write, because I'm trying to find, well, I want to write the way I want to write, and that's going to be in a very specific way.
That's going to have specific trade-offs. And so I think that the, the more you get further on in the learning continuum, the more there is a kind of. Benefit to experimenting, to trying your own thing, to getting sort of feedback from different environments you know, trying different approaches because that variety itself will be what helps you find sort of the unique solution to your problems, right?
Yeah, definitely. So, so yeah, we've covered tonight principles. And like what are we trying to achieve with what the app is actually? Well putting those, those principles almost like an actionable template that people can follow to learn a particular topic or skill. And hopefully this conversation will actually be very helpful to that for language learning and maybe something like copywriting and marketing, but in general what is your view on tools to help us learn and how they can like which, which of the printers.
They can help and which are maybe but we just don't have any tools for, ya know, you know what I think tools can be great. But I always say that like the right way to view it is in terms of this is the problem, what would be a good tool to solve it rather than here's a tool? How can I like it's the, here's my hammer.
And I'm going to, you know, hammer a bunch of things that aren't nails. And so we've already talked about a few of them. Pneumonics are a great tool. They're a great tool for handling the intermediate. Of when you are struggling to memorize something to when it is fluent. So they're not relevant after you're fluent with it and they are relevant for knowledge that may never get fluent.
Although again, when we were talking about proceduralization and this kind of thing it, there's a sort of an irony there of like, I'm not going to use it enough that it's ever going to be fluent, but I'm going to use it enough that I want to make a pneumonic for it. But they tend to be a good intermediate tool.
The flashcards, I think are a really great tool. I tend to view them as having more limited scope that they're very good for. One-to-one cue response relationships. I tend to think that doing more complicated practices better. Like, so, you know, if you're doing physics, do the practice problems rather than do a lot of flashcards.
In, in most cases you know, obviously memorizing a formula trigonomic identity flashcards are great for that, but, but recognizing when you can apply that, I think that you know, we talked about getting sort of real practice and real feedback I think is super important. I think it's important to have a good sort of prerequisite skill before you can get to doing that.
But I think that it's it's certainly going to form the bulk of the time you spend actually getting good at something. It should ideally be doing the real thing. And I think also we talked a little bit about copy copying, finding methods, finding something to reduce the sort of scope of the problem in the beginning so that you're not just trying random stuff and failing.
But at the same time, once you become really good at it, the trying stuff and experimenting and increasing the amount of variety you have is very important. Not only for getting yourself out of things that don't work. Cause if you do things the same way all the time, that self can be a problem, but also to develop a style and to find things that are going to be unique to solve your problems, which is not relevant for every skill.
We don't require originality for everything, but certainly a lot of the skills we value most highly this kind of experiment ting activity is, is very important. Yeah, definitely. All right. That's that's super helpful. I guess one thing I always ask at the end is like, who would you like to see next on a podcast?
Oh, wow. Well, I don't know. I don't know who you're going to get as a guest for me. I feel like. I think there's lots of people who are doing great work. You know, I'm of course I'm friends with Cal Newport, James clear. I don't know what their schedules are like for coming on podcasts these days, but I know that they are also great thinkers and, you know, I think you'd also maybe want to talk to someone like Tiago forte, who he's very into the sort of technology driven knowledge assembly and this kind of stuff.
And him and I have had debates about about various ideas, but I think he's a very interesting thinker. You might want to try sancha Aaron's he wrote how to take smart notes, which has really taken off with the whole Roam technologies and things. So it's very much in the same vein. I had a conversation with him and I think he's.
Yeah, I think those are some very interesting people. I'll, I'll reach out to them. And then finally, I guess if people want to know more about you follow you, what's the best way for them to do that? Yeah, so they can go to my firstname.lastname@example.org. I have over 1500 articles there that I've written on topics of learning, of course, but also self-improvement and productivity.
And you can also check out my book ultra learning, it's available, Barnes and noble, Amazon. It's also audibles. You're not sick of listening to me already. You can listen to me, read the book and you can also follow me on social media. I'm not personally as active, but we use it to, you know, share articles and stuff that I've written before.
And so you can follow me that way. If you prefer to get your information via Twitter, Instagram, Awesome. I'll sure be following you and perfect. So thanks Scott, for, for being on it was a great, and I think we'll have a lot of, a lot of value in this conversation and as many ways as possible. All right. Thank you. Thanks, Scott.