31–40 of 95 posts
For example I use LLMs to generate cards for me, and Anki's algorithm to make them stick.
Similarly a LLM plugin could easily present a fresh sentence each time you review a particular vocab
I found Anki way too heavy and the available decks mostly wrong way around for actually learning vocabulary (that is they were from foreign language to native, instead of the other way around) and switching the direction was way too cumbersome. I have not yet found a really good tool for learning Mandarin, except for classes and actually talking with people and doing the hard work of writing the characters again and…
I also find Du Chinese and The Chairman's Bao quite useful, although indeed for the writing, nothing seems to substitute actually writing. Right now I can read much more Mandarin than I can write.
I think that the author was using Anki incorrectly, and that led them to the spurious conclusion that "Anki is dead". I also have attempted to use Anki this way- using someone else's deck to try to force myself to learn something new. But that doesn't work, because it is just memorizing random symbols, as they noted in the article ("The enemy is the static card"). For example in maths learning, memorizing arbitrary t…
It didn't. They wrote "Anki is dead" because it brings clicks.
> The enemy is the static card. It always has the same front, formatting, and font. After enough reps I would latch on to little cues that are irrelevant to the meaning of the card, meaning I would skip the very important step of thinking deeply about the content. A fairly common occurrence was that a word in the sentence would remind me about the meaning of the sentence, giving away the answer to the target word, wh…
Slightly OT, but this happens constantly with ML classifiers on any highly multi-dimensional problem. At first it seems like magic, and then someone digs into the principal components of the prediction, and finds a mixture of a few highly specific factors that -- in the worst case -- is an artifact of the dataset itself (image blur or color bias, for example).
Also common is that the predictive factors aren't pathological -- they're just "boring" -- and therefore the performance of the model is dismissed by the practitioner ("oh, I'd have thought of that, since it's only using a few common traits that are well-understood.")
I think that the author was using Anki incorrectly, and that led them to the spurious conclusion that "Anki is dead". I also have attempted to use Anki this way- using someone else's deck to try to force myself to learn something new. But that doesn't work, because it is just memorizing random symbols, as they noted in the article ("The enemy is the static card"). For example in maths learning, memorizing arbitrary t…
Writing my own cards as I'm learning is the only way I've found it effective.
1- front: image+subtitle (in TL) back: word in TL.
2- fill-in-the-blank phrases for the word, fully in TL, translation shows up after completion (you HAVE to use the function where you actually type it out)
3- front: word in TL back: translation in NL with an image, also the inverse, but the image is always in the back. Making it a different picture as the one for 1 is essential
So each new word would generate me about 6 to 8 new cards. At a fast enough rate of card creation, you won't run into the problem of memorizing each card because you will be creating like 100 cards in a day. The "fatal mistake" (to quote the author) of this article is underestimating how much this process of card creation and organization aids in learning. Creating your own study material IS studying in itself.
That is, assuming the strategy being compared to LLMs here is the correct one of actually studying the language and creating your own Anki deck while you study the material, instead of the incorrect strategy of downloading a deck
I don't see the dichotomy, both tools seem rather complementary to me. For example I use LLMs to generate cards for me, and Anki's algorithm to make them stick. Similarly a LLM plugin could easily present a fresh sentence each time you review a particular vocab
> The enemy is the static card. It always has the same front, formatting, and font. After enough reps I would latch on to little cues that are irrelevant to the meaning of the card, meaning I would skip the very important step of thinking deeply about the content. A fairly common occurrence was that a word in the sentence would remind me about the meaning of the sentence, giving away the answer to the target word, wh…