A love letter to flashcards

I use anki in a similar way to the author and it has been truly transformative to my learning and daily habits.

And, like the author, anki has become part of my daily workflow even for things that it's not really specifically designed for; e.g. easy frictionless LaTeX notetaking, cross-referenceable database (via note ids), incremental learning repo, long-term reminders (gtd-style) etc.

I can really recommend them. Now back to flashcards and active recall. They are the secret sauce. People in the thread are saying that understanding is important, while I agree you should understand things its not THAT important.

Important is that you remember not only *facts* what something is. But also how to do something. If you stare at a blank page not being able to do something like writing a a simple typedef struct in C. But knowing what a typedef and struct is, you are missing procedural knowledge.

If you can only programming with an IDE giving you cues like autocompletion you will never form the memory for the actual symbol. Only when you active recall something it will be rememberd until it becomes automatic freeing your working memory from the load and reducing cognitive load overall.

I strongly believe that an AI rephrasing your backside and giving some additional knowledge from your own notes is helpful. You should still write your own notes and flashcards, an AI can help here too but just dont copy and paste them.

Learning can be so much, creating mental models and checking their validity, creating anecdotes, connecting new knowledge and ideas to already learned ones. Have fun!

There are many people that start using anki or flashcards only to stop doing them after a month.

Another interesting observation is that some people use flashcards to optimize for testing not learning. You can get good grades (really good ones) but it might hurt your actual learning. (What that actual means would be a longer topic)

It took me quite a bit of iterations to get AI to generate output I found good enough and with acceptable errors rate for my practice but that was the part of fun.

If anybody wants to try the same route, the biggest mistake not to repeat is to trust LLMs to generate words definitions by them itself. It does it quite well, but still gives wrong definitions from time to time (~1% in my case for the OpenAI models 2 years ago). This wasn't acceptable to me and took a lot of effort to review and correct cards I already had. Feed vocabulary article with word definition to LLM instead if you want it to generate word definitions suitable to your level instead.

This is quite true; I feel this is the case with maths. Simple math, logic math is all fine, but higher maths and theorems I find very, very difficult to understand. Here this is one of the few areas where my memorizing techniques did not work well. Sure I can remember many things, but applying that knowledge is very different to just memorizing stuff.