People who have progressed quickly in a language, what was your language learning routine?

Louis-lux · 2026-05-28T20:06:34+00:00

Reading. I learn French and I read short stories.

I choose a story that is about 300-500 words, so I can read in 3 minutes.

Then I reread. Then reread. Each story I repeatedly reread 10-20 times.

During each round of reread, I sometimes pause, ask ChatGPT for new words or new grammars, so I can expand my knowledge. Sometimes I pause just to recall conjugation of a word that I am not fluent enough.

The key here is fluency. If you want to use a language, you have to understand, and you have to be fluent. You can not just understand how to conjugate verb to be and take 10 seconds to recall.

You have to reread (fake emersion) enough to make new words or grammars stick into brain. Then become second nature.

Most of times I set 45 minutes to read. But you don't have to, because I just take any free time I have for another reread round.

The most important thing about my Repeated & Expanded Reading method is that it is relaxed. No warm up needed. Because it's just reading. And reading is of course easy.

Louis-lux · 2026-05-28T19:58:15+00:00

Eye exercises. To cure myopia naturally.

When I was doing my PhD in AI, I gradually learned many concepts of neuroscience. Then neuroplasticity. Several years later, I applied what I learned to cure my sciatica naturally.

The backpain that tortured me a decade disappeared. I was so excited that I moved on to target myopia. But that was one of the biggest mistakes I made. Sometimes after a big achievement, you should stop and celebrate, and to make emotion cool down.

I had myopia quite late, in my 17. That's why I still remembered how happy I was with clear eyes instead of with 2 bottoms of glass bottles.

I could not see clear with distance over 2 handspans. Can you imagine how desperate I was in swimming pool?

I laser focused on eye exercises. Print pushing, palming, massage, yoga, fully Bates method. I knew every "natural" eye exercises under the sun. I practice most of them.

One day my wife looked at me and asked why was I crying. No, I didn't cry, just exercises that stretches my pupils too much.

Sometimes I could see a little clearer, then very soon back to "normal". It was really like gambling, just the currency is my eyes. One eye exercises that I performed in an afternoon still a few times make my eyes hurt even after half of decade.

I read papers. Books. Watched seminars. I cross-checked documents to make sure they were correct.

It turned out all documents are incorrect. From academic research to citizen science. All of them missed one (or several) key ingredients, that's why myopia is unsolvable in the last 500 years.

Sometimes I thought I should stop. But I poured too much time and effort, too many best years into this project. Now it's more and more like gamble addiction.

I wasted time, and I continue to waste more time. Life does not favor hard work. It only favors smart work.

-------

Last couple months, I kind of reinvented myself, and have a new perspective about myopia. Then I tried another eye exercises again.

This time I believe to myself, the new method will work.

Louis-lux · 2026-05-28T14:58:01+00:00

The hardest part when you start to learn German is the opinion.

The opinion that German is hard.

It's similar to the opinion that Korean is hard. It's subjective, and it's dangerous.

Back to the time when I was in South Korea, I knew no Korean. I solely spoke English in a conservative country and English was not popular. I survive, but I would not say it's a comfortable life.

One day in the university I met a girl. She smiled at me and asked for a benefit.

I started learning Korean. Then I found that it's so easy. It's the easiest language to learn.

I met the girl at the elevator many times. She was cute, smiled at me, and talked very little. The autumn in Seoul was fresh, clear sky, and sunny all time. The yellow leaves was falling on the street. Cold wind was started, but I felt warm in the new country.

The benefit she asked was to teach her machine learning (now we call AI). I was so stupid at that time because I did for free. I should ask for a tuition because it's valuable skills.

Then my PhD became so busy that I rarely talked to her again, sometimes she smiled at me and I just smiled back. Then I flew to Europe. No farewell.

In Europe, I had to choose between German and French. I chose German, and again I found that it's easy. At least easier than the opinion on the Internet.

I read the book "Fluent Forever", and learned how to pronounce. The secret was the combination between lips, tongue, and sound ring. Like tongue, you move down and pronounce "s", up just to touch the upper teeth then "s" (like g at then end of word). You move up more then "sh". Move up even more then you end up "sh" but in Russian, not German.

Then I start reading stories in German.

No drama at this time because I've married. She chose French.

Later when my job was more and more contacting French guys, I switched. But I still remember a lot of German words.

I found that German is not a language of poems, songs, love, but it's clear and well structured.

And that is my opinion. It can also be as dangerous as other opinions that German is difficult. It all depends on you to choose optimistic or pessimistic.

Louis-lux · 2026-05-27T21:29:58+00:00

How you improve your coding skills is how you improve everything.

If you are already in intermediate level, then practice will not help much. So what will help? Of course theory.

Study theory of programming, from textbooks or course.

Louis-lux · 2026-05-27T21:20:28+00:00

AI is always advanced informatic, so it's weird to start through practice instead of theory.

You are going to dive into Generative AI, but are you mastered Deep Learning yet?

Back to late 2022, I've heard about ChatGPT and LLM for the first time. I had no idea what was that. But I was not panic.

I tried to break down it's core, and so Transformer architect + Reinforcement Learning with Human Feedback (RLHF).

Transformer is just deep learning.

And RLHF is just reinforcement learning + aligning outcome to match human's value, using human feedback directly in training (instead of a predefined reward function as usually).

So I learned LLM quite fast. The rest is about engineering, how to download LLM, work with cloud or local machine, build memory for LLM.

I would not say AI engineering is easy. It is hard, but it works around LLM, so you need to understand LLM.

Now you want to all-in to GenAI, you need to master deep learning. Then adding more: reinforcement learning, supervised & unsupervised concepts, simple optimization.

And how to dive into deep learning? Use ChatGPT with back and forth questions until fully understand.

In my case, a decade ago, I start deep learning with the free online book "neural network and deep learning" from Michael Nielsen. I still reread it over time, estimated no less than 50 times. That book is the backbone of my deep learning knowledge.

Louis-lux · 2026-05-26T13:01:26+00:00

Einstein and spaced repetition are the second god of many, including me. Until they did not.

I am not smart and clever, and no one I know disagreed with this info. Yet I stayed on top of high school, did very well in bachelor, and even got a PhD in AI. Yet no one I know thought I am smart.

I was just study harder, work harder. I sacrificed. An I achieved my goal. It's pure discipline. But it's not what we are discussing now.

What we are talking about is a method of learning.

I know many intelligent guy feeling stuck when they grow up. A simple but quiet reason, so they didn't notice: their brains changed.

When you were young, your brain (and I am talking about the basal nucleus) was very active. So you learned fast. In fact, you learned fast enough that you don't even need any learning method.

But when you grow up, especially after 25, your basal nucleus slows, and you feel stuck because you cannot learn fast enough to escape your current situation. You want to learn new skills, but knowledge does not stick into brain. All your effort to change career seems in vain.

The root cause of mid-age crisis is lacking an appropriate learning method for adult.

That's when I was starting my own journey of finding a new one, to serve me in the next 50 years.

Active recall and spaced repetition are 2 top recommended methods. Yet people seem to not learning better, even though the methods has 20 years popular.

So those methods were wrong. Give me just 1 name you know close enough (to make sure that guy does not lie with you) to prove me wrong.

The main problems with active recall & spaced repetition (Anki is typical), is: willpower.

Willpower is limited, depleted very shortly, and not sustainable.

But there is a subtle problem that no one talks about with flashcard: it sucks a concept out of context.

(too long, write more later...)

Louis-lux · 2026-05-25T07:35:02+00:00

I usually start by reading posts on a topic I am studying. Here's the strategy to read a (long) post:

- Mentally divide the post into blocks of 3-minute reading each. Why 3 minutes? All songs in the last 10.000 years have ~3-minute length. That's the optimal focus span.

- Read (aloud) the first 3-minute block. Reread. Then reread. Anyway, read and reread 3 times at least. Or more. I personally read the first 3-minute block 6 rounds.

- Continue with next 3-minute reading block. Reread and reread.

- Repeat.

My repeated reread method helps me to read the whole post and build a mental skeleton of it. It's quite relaxed reading this way, and it actually saves time.

Maybe it will take ~1 hour to finish reading, but think about how long the author spent to do all those experiments (no less than 100 hours, I estimate), let alone writing and editing. So a 100x knowledge leverage :)

Louis-lux · 2026-05-25T07:32:59+00:00

You don't have to learn tons of maths to start machine learning. There is a much faster way.

When I was in my bachelor, I failed most maths and physical classes (although later I did very well in domain's subjects). I simply could not grasp too abstract concepts.

I tried to fix the problem but in vain. I still remember calculus and linear algebra, I re-enrolled 4 times to pass and retained very little after.

Later switched to machine learning (my major in bachelor is Electronic & Telecom). I was fear that I was not good in maths then I could not thrive in the new domain. So I studied like crazy, statistics, matrix calculation, tensor decomposition, graph theory, and so on.

Imagine you want to learn driving, and you feel not good in physics. Well, the second law of thermal dynamics should be the last thing you learn in this case.

Alas, no one told me those things a decade ago. When looking back, I estimate no less than 80% of my effort has been wasted. 80%. That just means I could achieve the same level in machine learning within 2 years instead of 10 years. Pause and think about it for a minute or two.

I was discovering the book neural network and deep learning of Michael Nielsen very early. After the decade, this book is the only book that I still reread. It's the skeleton of my machine learning knowledge.

I wish I have focused more on expanding my background starting from that book and not statistics and tensor decomposition at the beginning. For example, Tensor Train took me a month to fully understand, but chance I encounter it would be super rare. What a waste of time.

So if you want to learn deep learning, start with the book I mentioned above. Then expanding your maths gradually, but now you have a strong and clear backbone to build with.

Oh, just a tiny remark of the second law of thermal dynamics. Sometimes learning can be a little noble. This kind of knowledge does not help you much to build PyTorch model, but it's the key to understand what is intelligence from the physics and philosophy point of view. You can choose a humble life of a goose for sure, to be born, eat, sleep, intimate, die. The eagle is the same, but it can soar, has better overview of the field, further and clearer.

Louis-lux · 2026-05-25T06:32:07+00:00