zlacker

[parent] [thread] 2 comments
1. dragon+(OP)[view] [source] 2026-02-03 01:57:55
Too old school and too effective.

FSRS just works, even without a GPU so it's not the cool kind of AI / machine learning these days.

No joke though: the FSRS model is marvelous, and Anki remains one of the best free + open source implementations around.

I've been learning German recently and Anki (in FSRS mode) is one of the most important learning tools I have. No joke.

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Every card remembers every rating you give it, as well as the time / date. This allows for Anki to solve for a 'forgetting curve', and predict when different cards have a chance to be forgotten.

There is furthermore the machine learning / stochastic descent algorithm to better fit the assumed forgetting curves to your historical performance. This is the FSRS Optimize parameters button in the settings panel.

replies(1): >>michae+u84
2. michae+u84[view] [source] 2026-02-04 03:51:21
>>dragon+(OP)
> Every card remembers every rating you give it, as well as the time / date. This allows for Anki to solve for a 'forgetting curve', and predict when different cards have a chance to be forgotten.

True to a point; every card has its ratings, but the "forgetting curve" algo of FSRS is only tuned to the deck (or "option set") that the card is in, not per card.

replies(1): >>dragon+Pn4
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3. dragon+Pn4[view] [source] [discussion] 2026-02-04 06:25:06
>>michae+u84
The entire FSRS parameter set (~20+ parameters, depending on FSRS version) is per deck.

Each card is tuned to... 2 parameters IIRC? f(Difficulty, Stability, Time) == Retrievability. Time is just time so its not really a parameter, but Difficulty and Stability is solved on a per-card basis.

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