I see a lot of discussion about SRS, and I think most can agree they have improved.
What I would like to see covered is a more vague area, but almost more important:
It’s the space in between reading/understanding something and the SRS. There are almost no standalone tools dedicated to creating flashcards easily from existing programs (web browser, PDF readers etc.) into popular SRS (Anki, Mochi etc.). They should work almost as OS additions to make everything feel native and frictionless; I don’t need another standalone tool that does X Y and Z, I just need some sort of pipe into an SRS that is Mac friendly and does the job whilst not being in the way.
If someone knows of such a tool, I would love to hear about it.
> There are almost no standalone tools dedicated to creating flashcards easily from existing programs
I think this is a common misunderstanding. Half the benefit of SRS comes from working out what the flashcards are. You have to circle around a concept, look for similarities, differences, examples, generalisations, properties, etc.
Is it hard work? Yes. Does it help understanding? Massively.
This is also a very difficult skill which, I believe, is why many people fail to appreciate SRS. They try, write bad flashcards, don't see results, and give up.
EDIT: This also leads to another common misunderstanding, that SRS is only good for memorising facts. With proper elaboration (thanks child comment), it can be used to build understanding of complex subjects too.
> Half the benefit of SRS comes from working out what the flashcards are. You have to circle around a concept, look for similarities, differences, examples, generalisations, properties, etc.
This is at least half true, but among SRS folks it's overstated.
The same argument stands for any creative endeavor.
Debussy had a greater experience than I did with Claire de Lune, because he composed it. In turn, my experience of it is probably greater than the next persons' because I learned it. Bottom of the heap is the lowly listener - but I think everyone would agree that listening is a wonderful way to appreciate music and shouldn't be diminished.
Same for literature, visual arts, etc etc.
The still greater reason that create-your-own has historically dominated for SRS decks is the specific curation aspect. Anything curated by someone else suffers from mismatch with your own intentions and prior knowledge profile.
(Plug time. Like most people, I am building my own grandiose SRS app. Some writing on it is here: http://patched.network )
>I think this is a common misunderstanding. Half the benefit of SRS comes from working out what the flashcards are. You have to circle around a concept, look for similarities, differences, examples, generalisations, properties, etc.
Yes. I really get the urge to automate stuff, but imo half of the benefit is from doing the leg work.
Creating your own flashcards and choosing what to curate is a helpful part of the process. This doesn't mean that being able to snip something nicely into a flashcard is not beneficial.
You might be right. I remember when I used SRS seriously for language learning, I got far more out of the cards I created painstakingly than the pre-built ones that I pulled off the shelf. That is - I still remember most if not all of the custom cards verbatim.
> They try, write bad flashcards, don't see results, and give up.
But if that's the case, then wouldn't a program that takes a long text (like a book) and creates GOOD flashcards, be way superior over someone making their own bad flashcards?
Fair point, please see my comment in response to allenu, in this same thread, for a detailed view.
I did not mean to glaze over this aspect, I am aware this is very important. I can not and do not use AI for automating flashcards for this reason alone. But, I think my point still stands, getting information from one disparate app into another adds a lot of friction (saving it somewhere, copy and pasting and yada yada) to something that (I believe) should be as easy as possible. We have 1 click instant payment, but I can't have 1 click get this into some sort of inbox in Anki ready to flashcard-ify?
To be honest, I have a whole frustration with apps and windows that I'm still trying to word, but fundamentally all we are doing when we are "computing" is moving information around. I wish that information was a first class citizen at the OS level that could be leveraged by any app immediately. Utopian view but this stuff ain't gonna think about itself.
That's usually done by writing and elaborating notes. I think it's not clear to most people how flash cards improve this. The original idea of flash cards is rote memorization of facts that need fast (automatic) retrieval.
I grabbed a set of flashcard for Spanish verb conjugations.
The guy had put in a lot of work to get them in the most frequent order, over 3000 lines of python. It been a massive help to me and I am not sure that writing the code to generate the list would really have helped my Spanish too much.
I've written my own flashcards app (Fresh Cards) and once in a while, users ask if there's a way to import flashcards from things like web pages and PDF files, but to be honest, I still don't know how it would work, so maybe you can help me.
From a user standpoint, would it be an interactive process where you highlight things and then click a button to say "turn this into a flashcard", or would it be an automated tool that would scan the content and come up with a list of questions and answers t hat would test the material for you? What criteria would be used to determine what's worth turning into a question and answer? And how granular should the question be? I've seen demos of things that pick out specific facts, like dates or names, from the text to turn into questions, but that might not be that useful to quiz for some material. It seems like a very open-ended process to me, so it would be hard to get right for everyone's needs.
I've tried Fresh Cards so thank you for developing that app, and trying to add cool new software into the space.
Great question. Here's one way to do it:
The first is how clunky the process of going from X to flashcard feels to the end user. One way to deal with the fact that we are crossing software border is to add an extra step where highlighting something allows you to go into an "inbox" before any cards are made. It is clear what the user has to do. They read something interesting, and add it to the inbox. When they are ready, they can head over and only then use some sort of automation (either via custom prompt for an AI or otherwise) to make the cards. This gives them another step, or interface, at which they can decide whether or not the thing they highlighted (since highlighting is easy) is actually worth something. It segments the process into clear easy sections: highlighting, deciding which highlights to flashcardify (and therefore keep), and flashcard review.
It definitely is an open-ended process, and I appreciate that apps need to have a strong opinion on how to direct users from start to finish; but I feel this is definitely possible now with cheap and quick AI.
I didn't answer every question but hopefully that helps somewhat.
I was an early user of FreshCards, and it’s a beautiful app, but creating cards was too much work. No share sheet or similar integration.
The easiest thing, which I believe I suggested, was highlight->action to create a new card front, and highlight->action to creat the back or a new front. It needs to work well casually in general, and easy when focused.
I’m sure AI could theoretically help but not sure it’s necessary. Part of the benefits of most cards is creating them yourself.
The macOS services model seems like a good fit for this kind of thing. Services are little bits of context-aware functionality that apps expose to enable integration between apps without active developer involvement. An example, in most Mac apps if you select text, right-click to open the context menu, and open the Services submenu you’ll see a number of services that do something with the highlighted text.
Ideally the SRS app would make services available to facilitate quick creation of new cards, so for example one might highlight some text, right-click, and select Services → New SRS Card… which then opens an in-place lightweight card creator dialog.
I hadn't thought of this; thank you for bringing this up. I will actually read into this. I didn't write it in my original comment, but I almost mentioned the OS because I'm coming round to the idea (albeit slowly) that the OS needs to provide some sort of hook into this capability natively for both maximum adoption and also ease of use (for both developer and end user).
Perhaps Shortcuts are now powerful enough to do this as a PoC, providing the SRS has some sort of open API that Shortcuts can take advantage of.
This is what we've built RemNote for! You can add your sources (PDFs, websites, YouTube, etc.) and create cards directly from them. Either with AI (click on a sentence => get an AI card), or by highlighting a sentence and writing your own card.
It's not at the OS level, but I think a focused standalone all-in-one experience is actually better. We've explored a chrome extension here that does something similar to what you suggest, but it somehow hasn't proven useful in practice. I always keep coming back to just doing everything directly in the tool (upload PDF, take notes, make cards), as it helps me focus deeply on what I'm learning.
Some examples I'm aware of (mostly in the language learning and especially Japanese learning space)
- subs2srs MPV script: create srs cards from subtitled videos, if you have subtitles tracks for source and target language it will fill them both in (though that sometimes has caveats, different languages may distribute the meaning of a line of dialogue over different subtitle lines)
- asbplayer chrome extension: inject extra subtitle languages into streaming services and create flashcards from them similar to subs2srs
- yomitan: browser dictionary lookup, primarily for bilingual dictionaries for Japanese and Chinese but also has custom dictionary support.
The big thing my script does differently is run Whisper locally to actually generate the subtitles from the video themselves. Most videos out in the real world don't come with convenient little SRT files bundled with them.
It doesn't yet shell out anywhere to automatically provide a translation, but that's more because I was already past that stage for most of its output reading-wise. It's explicitly tuned to make listening practice SRSable.
(I originally built this for learning Finnish. For the other 2 people here on that journey, https://finbug.xyz/ is where I've collected the other software I've built over the years for this.)
> It’s the space in between reading/understanding something and the SRS. ...If someone knows of such a tool, I would love to hear about it.
I have a slightly different system I'm developing:
Rather than reviewing with flashcards, review with actual content:
1. Tag the content with the words and grammar concepts
2. Estimate the difficulty [1] for you of each word or grammar concept -- the difficulty being essentially the inverse of your familiarity graphs in this article.
3. Choose content to read which balances difficulty and the impact on learning.
Since reviewing something you're about to forget has more impact than learning something new, "spaced repetition" falls naturally.
And instead of spending your review time going through flash cards, you spend your review time reading content in the target language.
[1] If you know the details of the FSRS algorithm, I'm using "difficulty" here differently than they do in their algorithm.
Not sure I understood the gist, but let me try summarise what you do generally (i.e. not just for language learning).
- Instead of flashcards, you read content/write notes.
- You tag said content in some way which allows you to understand how difficult it is.
- When in "review" mode, you essentially choose what to reread based on the difficulty you are feeling has the most impact right now.
I solve this problem with a system prompt in my LLMs[1].
ChatGPT is the main spot where I'm going to be trying to understand a new concept, so after groking it I'll ask it to make flashcards which I can then just copy and paste into Mochi.
An improvement would be some sort of MCP integration between the LLM and Mochi so it can just add the card directly. I'm sure we'll get there soon.
On Mac, you could make a little Shortcut that accepts your text selection or maybe even a screenshot and sends it to AnkiConnect to make a new note. Add this Shortcut to your share sheet and you can create new notes from any app. Later, go over the notes in Anki and add questions or if really lazy send the backsides to an LLM to create those questions.
If you're speaking in the context of language learning, there definitely are some great tools for "mining" audio cards from YT/Netflix and also for getting text from the subtitle tracks. Some are open source, free and easy once you get used to working with them (much like Anki itself). They're not frictionless for first-time users, though. Others are paid and a bit more newbie-friendly.
This mostly works with Mochi - you can paste PDFs etc into ChatGPT and the Mochi markdown format is simple, so it can generate flashcards for you (I have the format explained in my system prompt so I don't have to re-explain it every time). This synergizes nicely with the fact that you really want to understand something before you make flashcards from it.
If you pay for Mochi you also get API access, so one could make a ChatGPT wrapper which adds the cards for you. But since I like to review the cards manually before adding I don't mind the copy paste step.
Yes, I do something like this now. It definitely does do the job. I just wonder if there could be something more, something smoother perhaps, and the API access could do the trick.
I built a native flashcard app for mac that includes spaced repetition. You can close the main window, so it is not in the way and just select add flashcard from the top right menu bar in whichever application you are in
It's tricky I think, I think it comes down to specialized tools for different systems. I'm building a tool for Japanese in this direction. But of course it doesn't generalize to everything since the content and context extraction is very objective dependent.
I've never used it, but my understanding is that something that does this is considered a "killer feature" of Supermemo. It has a mode that lets you read text (via a PDF viewer) and lets you create flashcards as you read in some kind of semi-automated way. Or something like that. Like I said, I never used it.
You’re referring to incremental reading, which yes is indeed one of the killer features of SuperMemo. You're basically just reading, but you have at the core of it an SRS (SuperMemo) to store cool ideas in flashcard form and every article (“Topics” is how they are referred to in SuperMemo) will be shown to you at a later date. I like to think of them all on a “conveyor belt” that means everything you put into it will eventually find its way back to you. I love incremental reading but for many years I have struggled to find a way to mimic this OUTSIDE of SuperMemo. The overall peace of mind and level of control I have over the learning process is quite remarkable, and incremental reading is more than just the sum of its parts. I wish there were a standalone app for your phone or iPad for incremental reading, as I would love to use my iPad to do what I do when reading in SuperMemo on my windows laptop.
No, not PDF, only HTML. There are community companion programs like SuperMemo Assistant, that enhance SM, but it‘s all fiddly.
I paid for two SM versions and went back to Anki. It‘s very idiodyncratic, the user interface is atrocious (in the latest version it finally, finally added thumbs up/down icons for grading the answer —- before that you had to remember whether 1 is good and 5 is bad or vice versa).
SM is fascinating (including task management, sleep cycle tracker etc.), but it‘s held back by its technological choices (only support for Edge or IE, and Edge only in the newest version), and for incremental reading you‘ll be mostly ingesting Wikipedia articles, because PDF isn‘t supported.
I've fiddled with a bunch of stuff - macros, standalone programs etc - before finally settling on copy and paste. I just copy and paste a page of PDF into Anki then cloze single words (~6-15 words a page). I've worked through several textbooks this way.
Pro Tip , if you're using LLMs to learn, create an MCP tool for them to insert Anki cards on topics you're discussing in a csv on google drive, then sync that with you anki decks on your phone.
This was a game changer for me and working with LLMS, while I still think they make you dumb, and we essentially use them to offload critical thinking (almost only find myself using them when tired lazy, and just cant), if you must use them use them as a study tool.
I created a python script that checks my anki deck for the cards that I'm scheduled to review the next day and asks an LLM to generate new sentences for the cards, so that every time I see them, I see them in a new context.
I did this because I realized I was hitting an issue where I theoretically "knew" a word (would get it always correct on the card), but wouldn't always recognize it in a novel context.
I'm hoping that having the context be variable when I'm learning it will help fix this issue.
> ”I realized I was hitting an issue where I theoretically "knew" a word (would get it always correct on the card), but wouldn't always recognize it in a novel context.”
Some of the problem is due to the specificity of the training effect. I.e., if you mostly practice something through flash cards then you’re going to be training your ability to work with that on flash cards.
With language, there’s an additional challenge—many if not most words have different meanings in different contexts.
That’s a really clever use for LLMs, I have the exact same problem with my Anki deck. Do you store all the historical sentences for each card or is it just a destructive overwrite each time?
> f you're using LLMs to learn, create an MCP tool for them to insert Anki cards on topics you're discussing in a csv on google drive, then sync that with you anki decks on your phone.
Speaking for myself, I’d love to see a blogpost detailing how this is done. At the very least, I’d love to know:
How are you syncing csvs to anki cards and how does the MCP interaction look like for an LLMs response to the CSV creation
ChatGPT 4o's voice mode has been mindblowing for me for learning basic Mandarin. I'm sure I will hit the limits of the model sooner or later, but it has been so much fun bouncing around my apartment and asking what various objects are called / if words are related to other words. It is phenomenal for putting together short little sentences and getting immediate validation on grammar too.
No MCP on ChatGPT yet, but I can ask chat to generate an output of what we reviewed in a structured format.
My personal peeve about Anki: I don’t like its data model. It seems to me that there ought to be collections of notes (which might be things one would download or generate with an LLM or make yourself or share with friends or students). On top of one or more collections of notes are the sets of cards to want to learn, and they can derive from the notes. This includes, roughly, templates plus some concept of which cards are enabled. On top of that is the spaced repetition history and model. There also ought to be a way to constrain what cards should be studied in a given session. (For example, if learning Chinese or Japanese, one might want to have a pencil and paper when practicing writing but not reading. When practicing without paper, one might want to skip the writing cards.)
Anki doesn’t seem to separate these layers at all. Everything is a monolithic database. Import is unpleasant. Export is unpleasant. Sharing is unpleasant. Doing anything other than practicing and editing in the UI is unpleasant. And, every time I try Anki, I get stuck when I can’t manipulate my own data outside Anki.
Is there any system out there that doesn’t have this issue?
> there ought to be collections of notes (which might be things one would download or generate with an LLM or make yourself or share with friends or students). On top of one or more collections of notes are the sets of cards to want to learn
Is that not what anki does? You have a collection of cards, each card can be in one or more decks derived from the cards.
> There also ought to be a way to constrain what cards should be studied in a given session
That's also decks. You can have your 'Japanese' deck, and then the 'Japanese::writing' subdeck for the subset which require you to have your writing materials handy.
You can also use "Better Tags" to tag cards, and then create a sub-deck with an ad-hoc tag query to only study a subset if you want.
Does creating more decks and then studying the subset you want to in a session not work for what you want?
> Anki doesn’t seem to separate these layers at all. Everything is a monolithic database.
Decks are separate files which can be shared, edited, created, studied, and reasoned about independently.
The "spaced repetition model" in anki is obviously separate from the fact that there are multiple (FSRS and the old one).
> Export is unpleasant. Sharing is unpleasant
It's just files (zip files really). What's unpleasant about it?
> And, every time I try Anki, I get stuck when I can’t manipulate my own data outside Anki.
There's libraries to manipulate anki decks outside of anki for practically every programming languages. There are literally dozens of tools that can generate and import anki cards, such as the large family of japanese "mining" tools which create anki cards from media, dictionary entries, etc etc.
It's open source, and the code has clean library abstractions you can work with, so it's trivial to nab any of the data out of it.
> Is there any system out there that doesn’t have this issue?
Every issue you described is something that I experienced in other software, but which anki solved for me, so for me "anki" is that system.
> Is that not what anki does? You have a collection of cards, each card can be in one or more decks derived from the cards.
Kind of? As far as I can tell (and I haven't spent enormous amounts of time digging in), there are decks, and a deck contains the notes, the templates (and the cards, which may or may not have any sort of independent existence outside the notes and templates that generate them?), and a deck also contains the scheduling information.
One can export the textual and markup contents of decks, but not the media, into a text file, and one can re-import it, supposedly losslessly. One can also export a deck minus scheduling information for sharing purposes. I'm not sure that one can re-import it.
Then there is a collection, which is the whole world: decks along with their scheduling info.
> That's also decks. You can have your 'Japanese' deck, and then the 'Japanese::writing' subdeck for the subset which require you to have your writing materials handy.
I'm guessing that, if I start by importing a Japanese deck from some other source (because, for example, there's a source with high-quality notes), and then I split it into a writing subdeck, and then the original source adds new notes for new words or makes changes or whatever, that merging the results is basically unsupported.
> > Anki doesn’t seem to separate these layers at all. Everything is a monolithic database.
> Decks are separate files which can be shared, edited, created, studied, and reasoned about independently.
Yes, but only as monoliths (again, as far as I can tell). I can export an "Anki Deck Package (.apkg)", but checking that into git would result in a bit of nonsense. I can't export my scheduling information and templates separately from the underlying notes (or, if I can, I failed to find this option).
>> Export is unpleasant. Sharing is unpleasant
> It's just files (zip files really). What's unpleasant about it?
Excel and OpenDocument sheet files are also zip files. But the respective tools are less limiting and don't expect the users to unzip those zip files. (And their merging and text import/export facilities are also weak, and that's unfortunate.)
I could be wrong about most of this. But Anki doesn't seem friendly to a decomposed workflow in the way that modern programming lanuages are.
It’s amazing how every single point you’ve made here is wrong as the other commenter already dove into. On top of that Anki is one of the best documented pieces of open-source software I’ve messed with. If you’re able to program, ChatGPT can basically handle any task you want it too, I data mine the sqllite database regularly for my own insights.
My personal workflow with memorizing with Anki using LLMs is as follows: Read textbook material first. It's important that you understand what you are learning.You cannot just breakdown information into atoms and expect to understand how it works together (for example: you can learn that there are monounsaturated fats, polyunsaturated fats,
saturated fats and trans fats. But without reading beforehand about them from a textbook or other source, you will not understand how they differ (in chemical structure, biological function etc). After I understand the material, I feed LLM the documents (textbooks etc) and give it the following prompt:
>I want to generate flashcards from the provided textbook document using the attached PDF. Each flashcard should contain a question and a corresponding answer formatted as pairs in plaintext code block. The structure should be: "Question","Answer"
>Extract key concepts, definitions, and explanations from the textbook. If in the text imperial unit system is used, convert it to metric. For mathematical symbols and equations, format them using inline MathJax syntax because I will be importing the copied text to Anki. Ensure questions are clear and concise while answers provide a direct yet comprehensive response.
After the text is generated, I check out the accuracy (in 95% of cases the cards are accurate) and I import them into my decks. The rest is good old school Anki memorizing.
Actually, every point was right and the data model is terrible. I've been using it for years. The other commenter just mentioned a list of things that the software does do and basically said "isn't that good enough for you" a bunch of times. No, it's not. Anki's concepts of flashcards, and how it stores and manipulates them, are horrible.
It's hard to do many, many things in Anki that should be trivial, impossible to do many, many things that should be possible, and the things you can do involve the types of queries being run over your entire collection that causes the app to slow to a crawl after you add about a dozen decks. And in general: I can adjust far too many things that I don't even care to adjust and probably shouldn't be adjusting, and things that should be trivial to do are impossible.
It's bad. Ankidroid is a little better, but they're also stuck with the data model.
You're right about the data model. I built my own flashcard app [1], so I've had to understand the database schema that Anki uses and a lot of it seems very inelegant, but on the other hand, I can see how it was purpose-built and probably grew over time and things were tacked on. (For instance, there's one table that has a single row, where several fields are simply JSON dictionaries.)
On the other hand, how templates work and how cloze deletions work are really nice. With the flashcard app I built, I didn't have templates, but did have a very basic cloze deletion system where you could mark text to be "hidden" on the front. It was very limited in that you'd only ever get one front/back combination. You could hide multiple bits of text, but they'd all be hidden at the same time. With Anki, you can create multiple groups of hidden text, so that you end up with multiple flashcards from the same note (i.e. you hid three separate groups of text, so you now have three different cards to test with).
I've been working on an update to my app to incorporate templates and cloze deletions like how Anki does it, so now I appreciate that aspect to it.
For my own database, at least in the new version I'm working on, I've ended up creating a schema where the individual attributes for each card are thrown into their own tables, but this is mostly because I needed to support updating individual attributes separately since I use a very simple journaling system to sync across devices. With Anki's schema, I can see why sync was complicated (at least in earlier versions) since it wasn't really built for it.
Sorry, but your landing page is really awful. I’m not allowed to learn about your app because I’m on a tablet? And I have to give you my e-mail address, even though I know nothing about your app so far?
Suggestion: Allow me to browse your site and learn about your application, and I’ll decide if it’s interesting enough for me to open it on my desktop later.
For that I buy a vocabulary book, or a phrase book. As I read through it, and if I don‘t know a word or understand a sentence, I try to learn it using various methods, and create an Anki card to keep it in memory. Anki is just to retain the word.
On a plus side, you can buy specialized vocab/phrase books, I have one just for onomonopias. Also my beginner vocab books come with recordings from actual native speaker voice actors, which I add to the deck. Much better quality than anything an LLM or speech synthesizers can give you.
What are you talking about? Anki explicitly has the concept of 'notes' from which one or more 'cards' are derived. You can absolutely easily make custom decks that only have certain card types.
Currently ts-fsrs and rs-fsrs support FSRS 6 and py-fsrs should also support FSRS 6 in the next day or so. Also, both py-fsrs and fsrs-rs include the ability to optimize the FSRS model from your past reviews!
I used this for spaced repetition for opening training on Chessbook, can vouch that the Rust package is excellent. Easy to use and immediately lowered the training load on our users while keeping retention high. FSRS is awesome.
I use Chessbook and mostly like it, but I wish there was a way to configure the spaced repetition parameters. In particular, I find the frequency of reviews too low to retain well, especially for recently added moves.
I used basically this algorithm in college with the following setup:
Make a word document that lists all the keys to memorize vertically. Save as PDF
Open the PDF in a viewer with annotation tools. Make a clickable note in the margin just next to each key. Write out the value to memorize in the note field.
Cycle through the clickable notes. When you get one right easily, drag the note more to the left in the margin. As you cycle, focus on the ones furthest to the right. If you get one wrong, move it a bit further to the right.
In general the notes will move to the left until you're comfortable with all of them. And the balancing of which ones you need to see and focus on plays out very naturally and you feel in control the whole time.
There are many downsides with this compared to a tool like anki (e.g. I only used it on a laptop), but there was also something about it that just worked really well for me, so I never ended up switching to a different tool. But this was before anki had the similar algorithm described here. Maybe my experience would be different today
I've been looking into FSRS since I'm building a language learning app[1], but I haven't implemented it yet. Can FSRS work if I don't want to have 4 choices - bad, good, hard...? I have found myself to get into a decision paralysis so just bad/good works better for me. Plus I can swipe the cards tinder style! :D
My second reason is that I'm worried about the complexity - both from non-nerdy users perspective and me having to debug it.
Yes. Some months ago, I forget whether it was v5 or maybe before, the 2 button grading approach meant that it actually performed better for users (ie. it performed better for users that explicitly only used two grading buttons).
I don't know if this is replicable with v6, or not. I would be interested to find out!
I am the creator of Trane (https://github.com/trane-project/trane/) which can replace Anki and similar systems for domains that have a well-defined hierarchy between subskills (turns out that's most of them, including learning vocabulary).
There are several unresolved issues with Anki, SuperMemo, at al.
1. Emphasis on memorization. I wanted something that could be applied to domains (music) whose scoring is not based on memorization, but mastery.
2. Lack of any hierarchical information limits how well it works to learn much larger skills. It's trivial to replicate the functionality of Anki with Trane: just have one lesson where you put all your exercises. Anki cannot replicate what Trane does, which is to use the dependencies of the many sub-skills to track and limit progress until mastery is achieved.
3. Emphasis on creating your own exercises. You are expected to come up with your own decks, which takes a lot of time. For complicated skills, you need to be a domain expert to really know how to do this.
Trane is pretty much done, and I have used it to teach myself music. It does not have a UI at the moment, so I am pretty sure I am the only user. Not that I mind, because I rather not work for free.
Currently working on a literacy tutor that will be built on top of it. When it's complete, it will be able to guide all students from learning their A-B-Cs to reading and writing at college level, backed by the most up-to-date research on reading and writing acquisition. Hopefully I will be able to release an MVP in the middle of the year.
You might be interested in reading the literature on Knowledge Tracing, which is a superset of spaced repetition, aiming to predict what the student knows from their answers.
The simplest approach is Bayesian Knowledge Tracing [0], which is just a simple probability update and an Expectation Maximization optimizer to fit the latent factors. The standard version assumes an independent set of skills with no forgetting, but there are extensions for that [1] [2]. PyBKT [3] implements some common ones, so take a look there.
Learning Factor Analysis [4] seems to work considerably better than naive BKT, while being very simple to implement (it's a logistic model, sharing the family with most spaced repetition algorithms), so that might be promising if the hierarchical dependencies are incorporated. Some researchers have been applying increasingly complex NNs [5], including transformers, but personally I think that's just more parameters to overfit [6].
I'm not an expert. I only built a basic KT tool to prepare for the national Ukrainian exam and found these along the way.
> For complicated skills, you need to be a domain expert to really know how to do this. (...) I have used it to teach myself music.
It sounds like you must have had some interesting difficulties with that, not having been a domain expert in music. What were they and how did you overcome them?
I have been mostly working on a set of courses based around backing tracks I got from a course called “improvise for real”. So I only had to make the structure of those backing tracks explicit, which only required knowing the circle of fifths.
Spaced repetition has been all the rage for 20 years now.
Dozens of apps, thousands of lectures, and it turns out its not really a silver bullet.
There's nothing really wrong with it, it's just that people tend to fall off the same way they do on any other education pattern.
A couple years ago I was thinking "If Google and Apple really cared about kids they would make a spaced repetition unlock system", where by you have to make note cards every week and then have to answer correctly to get into your phone. (obviously requires some bypass system, other rules, etc)
You could probably jury rig it with a popup that comes up after you unlock, but people would never install it anyway.
Spaced repetition is time-optimised, but it isn't self-discipline optimised, nor motivation-optimised. If you're limited by time, it's very efficient, but it drains motivation. If you're anywhere close to being limited by motivation (or, failing that, self-discipline), it just causes burnout and failure.
I credit Anki to my success at GCSEs and A Levels despite having a head injury, and I also credit it to me burning out so hard I took a gap year!
And I'm enjoying the gap year, but Anki made it a near necessity.
There was an interesting post here awhile back about autonomy and motivation. The gist was people's motivation is proportional to their autonomy. This is quite intuitive, you can see people are really motivated when they have autonomy (think kids with Minecraft, musicians with instruments). One terrible thing about Anki is that it probably is horrible for autonomy. Quite possibly using anki actually has a negative effect on motivation.
>I also credit it to me burning out so hard I took a gap year!
Do you think targeting a sub-90% difficulty could help reduce burnout? My experience is that working to recall something I'm on the verge of forgetting can be very effortful.
IMO, the most limiting feature is that spaced repetition is a method for memorization, but memorization is only one part of learning and it's very often not the most prevalent part.
But when memorization applies, gamification is a really good way to avoiding burnout (as long as you don't overexpose yourself to it). There are many spaced repetition games for children, I don't know why people make so few of them for adults. (But then, fearing the duolingo owl is a popular meme nowadays.)
I have downloaded 3 card decks for learning Spanish.
The main deck I use for verb conjugations expects me to use it for maybe half an hour per day or the list just build up (I have no idea if this is standard behaviour, but I don't seem to get the same build up on the other decks that I use less frequently).
While it end up being a bit of a chore some days, I appreciate that it does force me to use it every day, which is good for my discipline.
I would say the implementations are time optimized, over the others. I’m building a language learning application, and have put in a lot of effort to make sure that the Spaced Repeition is motivation-optimized.
It’s centered around your performance and review times, to make sure you aren’t struggling to much; no due dates to avoid Anki slogs; gamified with some internal mechanics; dopaminergically influenced with aspects of randomness.
Spaced Repetition is just an equation (SM2 is laughable simple), but a lot of applications just slap a UI on it and call it a day, but that’s not the only way to use it!
One thing that bothers me about SRS is that it doesn't get enough attention from people who understand the difference between memorization and language acquisition. It gets a ton of attention from people who are doing test prep or who get intrinsic reward from their memorization accomplishments.
Memorization is not my goal — I want to get better at reading Spanish and French — but I find that drilling on vocabulary and example sentences helps a lot. I compare it to using scaffolding in construction. Scaffolding is not a building. Scaffolding doesn't serve any of the purposes a building does. But if you need to build, expand, or refurbish a building, sometimes building scaffolding in and around it can speed things up a hell of a lot.
I wish there were better guidance for using memorization to assist in language learning, but the world seems to be split between people who are satisfied with memorization as their goal (for test prep or intrinsic satisfaction) and people who dismiss memorization entirely because it isn't their goal.
If I weren't already busy enough using Anki to accomplish my own goals, I would almost certainly look into deeply integrating LLM calls into it so that we could e.g. practice writing and speaking with it in a way that is much closer to the kind of immediate feedback loop you get with a tutor.
For now, I make do by having Gemini Flash 2.5 open in a separate window and checking my short answer writing responses with that.
There's some UX problems of SRS (that I'm working on) that makes it high friction
1) Time taken to create cards
2) Need for self marking
3) Creates a one to one mapping of prompt-answer
4) If you're an autodidact, you have to teach yourself first (alternatively called understanding, scaffolding, etc)
More fundamentally, SRS isn't a superpower because it's just very specific to creating a direct prompt retrieval. Generalization is poor. Even creating a graph of knowledge, is a chain of edges between bits of knowledge, isn't done very well here.
And I suspect there's a very deep, fundamental difference between recollection knowledge and logical-modeling knowledge. Recollection seems very similar to a dictionary access, and if you recorded the time to recall in humans I suspect they'd all be constant. But learning the knowledge of a logical model, like of a mathematical concept, appears to be vastly different and have very different time to compute.
Proponents of SRS will point out logical models need facts as well, like formulas, lemmas, etc. Which is true. But if you already grasped it before you'd grasp it faster the second time. So the practical use of SRS is a significant step above having a very well sorted and labeled notebook, but still way below becoming a genius.
Poor generalization (overtraining on prompts) and loss of context over time are the biggest issues I've found with them. Slow card creation workflows and needing to rate your own reviews are merely UX issues -- losing context and losing generalization make SRS actively harmful when used for some topics.
There's 2 solutions I've thought of but haven't tried implementing:
1. A free-recall based approach. Free recall allows you to operate at a higher level of organization and connect concepts at lower levels. However, how you would schedule SRS with free recall is not clear.
2. Have an LLM generate questions on-the-fly so that you don't overtrain on prompts. You might also instruct the LLM to create questions that connect multiple concepts together. The problem with this approach is that LLMs are still not so good at creating good test questions.
You say that but it's completely revolutionized the way medical students study.
IIRC the effect was so profound they had to modify the structure of some tests or something to that effect.
And polyglots have been using SRS for years.
As always, the real problem when people fail to do something that works is psychological, not technical. I'd say anyone who made an Ozempic for motivation would make a killing, but I believe it's already a scheduled substance. Maybe one without potential for addiction or abuse. Or maybe an Ozempic for conscientiousness.
I'm not so sure. My brother's medical school had to tell students they had to study the actual material rather than Anki decks because so many students were failing tests.
I would expect the flashcards produced under this regime to be utterly useless, like a flashcard with "A" and the answer is "B", or simple math problems. In other words, Goodhart's law.
This is a very big problem. Virtually all the results from research here comes from some form of simple word recall. Direct recall occupies some part of real world tasks, but IRL if you're stopped by doing something it's people not because you can't remember it (and you could look it up if you forgot).
It's a silver bullet for learning facts. You still have to actually do the learning. Nobody was claiming it would download knowledge into your brain Matrix-style.
You'd probably say silver bullets aren't a silver bullet because you still have to load the gun and shoot it.
This is a strange comment because it shrugs off something that has been transformative and hugely useful to a lot of people because it doesn’t fix all conceivable problems.
I don't think it's a strange comment. He's mostly right (and so are you, but I think you're talking past each other). There's nothing wrong with SRS, and I agree with you that it's basically like cheat codes for memorization, but there is a limit to what most people can do. i.e. most people do tend to drop off.
I remember reading some stats from WaniKani (Japanese SRS app) a while back...
WaniKani has 60 "levels" to learn 2000+ kanji. Each level takes about a week (there's no skipping ahead), so the material takes about a year of study to complete -- that's if you're going at breakneck pace, which most people aren't.
According to the numbers I saw on the WK forums, ~8% of users reach level 30 and less than 1% reach level 60... and that's just to learn as much kanji as a 9th grader. That's to say nothing of the grammar and the 20,000+ vocab words you'll need to SRS to truly learn the language, or the thousands of hours you'll have to spend speaking/listening/reading, immersing yourself in native content, etc.
People give up very easily. The language learning community often gives year estimates to reach "near-native level" in a language based on frequency of study. In reality, the process takes a lifetime. I don't know if people truly know what they're signing up for when install those apps and begin studying. It's a lifelong commitment. It's just something you do now, every day.
You can stop at any time of course, and most people do (more than 99% of them apparently).
> Dozens of apps, thousands of lectures, and it turns out its not really a silver bullet.
I mean, you say that, but I did mandarin for maybe 6 months, I did reviews for maybe a year or two on and off, I haven't done a review of mandarin for 8, 9 years now and I can still recall quite a bit of it. So for me it's worked quite well.
I’ve been using Anki for about a decade now, and as far as I’m concerned, the only real improvements needed are design/UI based. It is functionally irrelevant if the algorithm is optimized or not when the actual user interface seems boring to potential users. While I do like that Anki has power user options, it’s also very unintuitive to the average person just looking into it.
Which is really a shame, as the spacing effect itself is such an underrated aspect of human learning that it almost feels like cheating.
AnkiDroid maintainer here: we're actively working on a new design for the reviewer (currently available in the Developer Options in the production app).
I don't think any of us are satisfied with how most things look, but we're severely under-resourced.
Feel free to email me if you'd be interested in getting involved with the Android side of things.
I love Anki but it’s an archetypal example of “designed by an engineer”.
It’s powerful, with a lot of depth to its features - but it’s also hideous, clunky and unintuitive, and it takes a long time to figure out how to use it effectively.
An HN-reading tech nerd can probably figure it out, but your average Duolingomaxxing normie? No chance.
>An HN-reading tech nerd can probably figure it out, but your average Duolingomaxxing normie? No chance.
Me, the person who reversengineered obfuscated code doing weird crypto primitives and submitted patches to linux kernel can't figure it out either. Maybe I'm not HN nerd enough, so I had to do the duolingo to pass my citizenship exams.
Anki seems like it works for a lot of people with a very specific flow, but I don't know what the flow is and why it doesn't work for me. It's weird.
Reminds me of how I'm using Anki on iOS to learn German, and my phone's configured language is German, except for the Anki app, which is ironically the only app I've configured to be in English because I couldn't understand what 80% of the buttons meant.
Those reasons are why I love Anki. I'd rather have a program that exposes every mechanism of how it works and allows me to access it than a program that doesn't and the program appears to appear to work by magic. Give me visible cogs that I can tune and a good manual any day of the week.
Anki is refreshing function over form design. It's beautiful.
I think the default settings are fine for 99% of the users. I've used them to "master" a language and I've been more than fine. Actually, I'd argue I was more effective than people who didn't use SRS.
Ah i've been curious about what improvements folks would like to see most in SRS learning and this thread is gold! It does seem as though Anki’s core is undeniably solid, yet its power can also feel like a hurdle for non power users. Additionally, i'm not sure "boring" is necessarily bad, as i've heard and to agree that learning may be best when it feels like a strenuous workout.
Language learning is the classic use case, but I also use it from everything from historical facts to encyclopedia entries on a subject I’m trying to master.
Probably the simplest use case to get started is improving your English vocabulary. (Assuming English is your first language.) I try to add a card for any word I come across that I don’t know the meaning of, and it works very well.
Try to learn a different writing system, alphabet or not. Arabic, Cyrillic, Hangul, whatever. It has finite number of cards and you don't need large context to understand them.
My biggest gripe with it is how clunky the editor window is. That’s the main part that’s due for a redesign in my opinion.
It has other oddities too though, like the tab bar in the main window that doesn’t act like a tab bar. It should also really have two button mode (Again and Good only) for the review screen as a built in option, too — the addon that adds this is very popular and it’d be dead simple to implement.
Compared to i.e Duolingo, the app is quite boring. I still have been using it for years. But I sometimes wonder if adding a bit of gamification may help. For instance, streaks, sound effects, etc. Obviously, those should be optional
I've quit Duolingo because of the gamification. It's far, far too much, and it puts me in the wrong mindset for learning. Instead of concentrating on the knowledge, I'm gaming the system to improve my score the most. There were times I would stop learning because I knew if I saved it for later, I could use a multiplier for a higher score.
And the daily emotion-tugging streak reminders started to actually piss me off.
On top of that, at one point they were changing the icon regularly and made it really ugly. Despite a ton of complaints, they left it that way for a long time.
So I canceled my subscription and I'm done with them. I'll find another way to study that I like (I've already tried Anki and it works, but I don't like it) and isn't mentally abusive.
I used to be something of an Anki evangelist and recommended it to anyone that would listen. But the minute I showed it to someone that isn’t already technically-minded, their eyes glazed over and they lost interest immediately.
I think it just needs a fresh minimal design, a tutorial, and some premade decks that aren’t just the half-baked free ones.
There's an excellent heat map addon that helps with that. Some people have tried the "dopamine effect" style things (confetti when you answer a question etc), and it didn't work for me, but there are addons for it if you'd like to try it.
it'd be nice to have a better UI. but the reason people don't use Anki isn't because it's hard to use. it's because the time to value is high, and the value really only comes from long term discipline and motivation.
people that are motivated and will succeed with Anki regardless of design will power through an annoying UI. so with better design, you'll increase top of funnel but radically decrease conversion.
I wrote "Why Anki Doesn't Work for Me" (https://medium.com/@iandanforth/why-anki-doesnt-work-for-me-...) six years ago, which means it was before the new algorithm was implemented. While Anki likely still suffers from all the other issues I mentioned, this directly addresses my point (3). I'm going to have to give it another try and see if the other points are still too much friction, or if the frustration caused by the algorithm was a majority of my pain.
I had similar issues... anki would drill me hard while stuff was still in short term memory (single session) then push it back weeks or months before I had any retention. I'd get to it again and it'd be completely gone, queue re-learning it from scratch.
I brought it up around the time I tried it and got shouted down. Pretty much every spaced repetition app was treating anki like a holy emissary, so I gave up on spaced repetition entirely.
There is definitely an aspect of online language learning communities where certain sanctioned methods are treated as gifts from the gods, while other methods brand you as a no-good heretic who doesn’t really want to learn the language.
I had a similar experience. In retrospect I felt like I was wasting my time trying to use it. I somehow ended up with memorization sessions that were too easy and impossibly hard and there seemed to be no way to kind of bridge the gap.
I switched to FSRS via the extension partway through my A levels. I also used the little google collab notebook to custom fit it to my learning patterns - I'm not sure if that's in the version that was merged into the main version.
It about halved the amount of reviews I needed to do, and they didn't come up in bursts, so they were a lot more pleasant. I didn't quite believe it at first, and worried that it would be less effective, but it worked just as well if not better.
> I also used the little google collab notebook to custom fit it to my learning patterns - I'm not sure if that's in the version that was merged into the main version.
It was! There's a little "Optimize" button in the deck settings that you're supposed to click once a month or so, which does what the old colab would do for you.
I’m doing my A-levels at the moment with economics and geography still to go, do you have any tips or advice for leveraging FSRS / tailoring it to my learning style that is more specific to A-levels, based on your experience?
WaniKani has the best UI for any SRS software I've ever seen, but they suffer from the old algorithm. They're guilty of all of your points and the article's fourth heading concern:
> And the idea that you’ll literally never see a card again after the last interval is terrifying, as it means you’re constantly losing knowledge.
What I find interesting about spaced repetition is the underlying thesis that raw memorization, in certain contexts, is playing a more important role for learning than what some modern education ideas would make you assume. In mathematics or programming, for instance, there is this idea that understanding a concept is better than memorizing algorithms or recipes (derivation methods for instance). But spaced repetition challenges that, in a sense.
If you zoom out and look and the shift in educational systems from pre-industrial revolution to modernity, memorization is a key topic. Basically educational reformers wanted a switch from memorization-heavy classics-based education with lots of Latin and Greek – to one with less emphasis on memorizing and more technical focus, more “understanding” and so on.
Like other big cultural shifts from the time, the correction was necessary but also probably went too far in the opposite direction.
Which is a long way of saying that memorization is underrated and it mostly has a bad reputation from anti-Victorian reformers.
Most modern programming lives by the idea that you don't need to remember something as long as you remember where to look it up. Of course that's only true for some things: I can look up an API call, but I need a reasonably complete working knowledge of the concepts offered by my chosen programming language and its idiomatic design patterns. In most cases this is maintained through application (practice is unstructured spaced repetition), but if I wanted to get into say C++-based driver development then spaced repetition would definitely help build and maintain the necessary knowledge
It makes sense to memorize elementary operations that are reused frequently because that frees your mind to focus on the "higher level of abstraction" of learning. You probably learned the multiplication tables by heart before you were asked to do more complicated multiplication problems for example.
I think the difference in recall- knowledgeable and logical-model-knowledge will be really interesting. LLMs appear to strongly be the first. But this is very hopeless on mathematics.
>But spaced repetition challenges that, in a sense.
Common sense challenges this honestly. Education systems that traditionally have put a strong focus on repetition, memorization and what you could call neuromuscular training (e.g China, the USSR, France) in particluar in STEM far outperform anyone else. Vietnam outperforms most rich countries.
In programming circles it's a cultural cliche because our profession is full of people who go by: "I am a genius, I work smart, not hard", probably the most damaging idea ever uttered in education, and in the humanities it's seen as culturally unsophisticated.
In reality, 95% of everything is mechanics. Starcraft, math, even literature and acting. Creative freedom is enabled only by a large body of effortless recollection.
I'm sorry, I didn't read the article but I thought my experience would be a good anecdote.
I've used Anki for multiple years and learned around 18'000 Japanese words. It's difficult to say but I'd say I've learned how to read around 5'000 kanji. When I studied in Japan, my kanji reading—don't mix that up with comprehension!—was way above everyone else's. And most of my classmates were either Korean or Chinese.
That's what 10 minutes of free time—I did that during my daily train rides—can get you! Keep practicing. Being ignorant is the first step towards becoming more knowledgeable.
I've tried to get into anki a bunch of times but never stick with it. It's an on-and-off thing for me that I end up looking into again every few years, which I've gone through about 5 times now. Here's how it usually goes:
* Get interested in memorizing something / multiple things
* Find that the decks available to me are actually not so great
* Get reading online, people say that the real way to benefit from it is to make your own deck (which ups the time commitment significantly)
* Read online about how to get the most out of anki, find out that everyone universally agrees that the default settings are terrible but nobody quite agrees on how to set it for best results
* Try to hit a happy medium, but find that the overhead of 'rating' the difficulty of recall for cards (and how it interacts with the complex settings that I still don't have complete confidence in) adds an incredibly (to me) distracting amount of overhead and never get used to it
* Miss a few days, get overwhelmed with the amount of cards stacked up, don't feel good about my settings (which have implications for what cards show up like, a year + down the line)
* Ultimately fizzle out
I'm probably going to start the cycle over again soon. I really do want it to work out for me. Any tips to avoid this issue? I'm planning to actually pay for some decks this time to see if that gets me to the quality I want, and going to skip the whole 'trying to make my own deck' thing for now
Yeah, ignore the "defaults are terrible" people. Turn on FSRS, if it isn't on by default (I think it is), and forget about it.
I have seen this opinion offered hundreds of times and each and every time I reflect upon the irony that not one of these commenters having trouble navigating the UI, etc to their liking doesn't just ... Make Anki cards about Anki.
If that sounds silly, it shouldn't. I've made flashcards out of all kinds of other programs, from vim to shell shortcuts to Photoshop. Nobody ever expects an interface built for professionals to be something they can just waltz in on and understand perfectly on day 1.
* Make your own cards (unless there's an automated workflow [Japanese, sentence mining], really good shared decks, or you're studying for a standardized exam [USMLE])
* Deck Settings (scheduling): Enable FSRS. Press 'Optimize', then press optimize once per month.
* Deck Settings (workload): Wait 2 weeks before gradually increasing new cards per day (if you want to study for longer). Decrease it immediately if you feel you're getting overwhelmed.
* Deck Settings (backlog): Set max reviews/day to 9999
* App Settings: Disable 'Show next review time above answer buttons'
* Recommended: Press 'sync', and create an AnkiWeb account. In app settings, set Anki to auto-sync on open/close. This is a free backup.
* Optional: Use a mobile client (AnkiDroid is free on Android, AnkiWeb is free on iOS)
You'll feel like you completed the first day far too quickly, and will want to do more. Avoid overstudying until you build intuition for how it impacts your daily workload.
We spend hours a day browsing the web, so I made a browser extension[0] that translates sentences at your knowledge level into the language you're learning, so that you're always learning a little through immersion.
I also used the same "10 minutes a day on Anki" strategy with my A levels, and it made the revision process so so much nicer because stuff I'd learnt two years ago was as fresh as if I'd learnt it a couple of months ago, rather than years.
Looks not bad but a) billing/prices should imho be prominent and not hidden behind trial or get started. And b) not sure if 5/12/20 per month is not too much? The About section is nice. (I use two other paid language services, thus no need/interest in another)
There's a surprising gulf between word recognition and overall sentence comprehension. I'm learning Farsi with a combination of Anki and Youtube videos and sometimes I find myself in the weird state where I recognize every word in a sentence, but yet cannot assemble its overall meaning.
Yeah there’s a few different levels. 1) not knowing the words 2) knowing all the words but not what they mean together 3) not being able to keep up with the speed at which the sentence is spoken…
Not buying at all that you learned 18000 words and 5000 kanji in ten minutes per day. Thats 60 hours a year for say five year, or 300 hours. Thats leaves you with about 70 words and/or kanji per hour or less than a minute per word/kanji. A rate which far surpasses native speakers.
Anki works, it doesnt need these unrealistic takes.
Actually, it took me 20 minutes of time per day to do my reviews + new words. I had, on average, 200 cards to go through daily (180 review + 20 new cards).[1] Going through 18'000 words took me around 5 years. 5×365×20=36'500
> A rate which far surpasses native speakers.
Are you comparing me to babies? It took me 2 weekends to learn all kana, but it takes years for a toddler to learn just hiragana. It's not a fair comparison.
> Anki works, it doesnt need these unrealistic takes.
I wonder why you think it's unrealistic. It's not like I'm a genius or anything.[2]
[1] Two cards is one word; one for English -> Japanese, one for Japanese -> English.
[2] Some teachers definitely thought I was a genius because of my memory, but it was all thanks to Anki. And proof is that I was absolutely bad at text comprehension. Anki doesn't make you practice that.
I learned 17.5k words comprised of ~3k kanji in around 2 years at about an hour a day of review time. That's reviews + new cards, not including time immersing in order to find the daily quota of new vocab which itself was 2 to 3 hours of study.
So, by my calculations for just the Anki time alone it's about 17.5k words split across 730 hours, which comes out to about 23 words and hour or one word every 2.5 minutes.
I've seen a pretty wide variety of people do Anki, and I can say there's a distribution in length of time per card for basically the exact same types of cards among people. The slowest people average around 3x slower than the fastest.
That isn't terribly far off. I used Anki throughout my A levels, spending about 250 hours on it in total according to its statistics, and had something like 10k cards that I reviewed 50k times.
Now, those cards weren't alone - they were reinforcing content that I'd learnt in lessons. But if they were doing it for 10 minutes a day a few times a day, it seems quite plausible to me.
Sure, but I didn't read it as 10 minutes a day. The comment says ten minutes of free time. So could be 4 train rides, 10 mins after you finish your sandwich at lunch, 10 mins with your coffee in the morning, etc etc.
Pretty OT: A few month ago I tried to marry my simple note system with anki. My goal was to be able to send simple front/backside cards to an api and it would get integrated and I can use it immediately. Ofc, when I edit cards via my notes-backend, the cards in anki should update too.
Long story short: not possible with anki. It took like an entire day for me to realize its just not possible without diving deep into ankis sqlitedb and having the client installed on my server to interact in a horrible way with decks. I wrote my own space repetition [1] backend in a week and never looked back to anki. Ill intergrate FSRS in my software.
I looked into this before too. Ankiweb (the place where cards created on Anki sync to) does not provide a rest API. The service is free though. It makes sense they may not want automated clients.
There is an implementation of their sync server, which you can self host. And it has a REST API
Anki can import .csv files and if one of the column content is matching an existing item, it will update the contents of the card while keeping the repetition history.
Think of it like including a column with unique keys.
I know this is not precisely what you wanted, but yes, Anki can update card contents.
i use the python package genanki to accomplish this. I've found it to be extremely dependable -- just use the first field as a UUID and you're golden (future imports dedupe and auto update imported cards with the same first field)
I haven't seen it mentioned yet with CTRL-f and I haven't used Anki in a while, but has there been work put into modifications in Anki or other programs using spaced repetition along with interleaved practice to also see if that improves studying.
I think it’s important to note that the original SRS algorithms are not for learning. They or for remembering or “not forgetting”.
The system assumes you have already learned the fact (for some unclear to me definition of learned)
Most users inserts new words in the hope that repeating them in anki will help them learn. It does to some extend, but it is not quite the right tool.
So for example, in Japanese, simply remembering how to read a word out loud is a task in and of itself. If you put words in context (which in language learning makes sense) the learner will quickly start to recall the meaning of the word based on the look of a sentence.
For a learning system this open up a lot of issues to solve. The best attempt I’ve seen was a web app that gave you full sentences and you clicked the characters word you didn’t understand and based on that it would give you different sentences.
There are two problems with that website: I don’t remember what it was called and it used google translate from 10 years ago. The second could be improved by expanding the corpus and use LLM to form sentences for the learner.
That tutorial guy on YouTube, Derek Banas, swears by Anki. He's quite the voracious learner as well as being a pretty good contractor. I've used it myself (sparingly, when taking on new projects with new technology stacks), and never really committed to it because of the somewhat static and predictable nature of the learning session (as described in the article; the algorithm). However, from learning about the upgrade (well, 2023 upgrade), I will try it out again: high hopes.
> Thankfully, the leading spaced repetition software, Anki, has incorporated FSRS as its default scheduling algorithm since version 23.10, released in 2023-11
I've used Anki for a long time and apply updates, but I don't closely track changes. Based on the above, I figured I'd be using FSRS, but I'm not. All of my decks have that setting turned off. Fair enough (no silent updates to existing data), but even when I create a new deck, I have to turn the FSRS setting on manually. I found the same even with a whole new profile. What aspect of this is "default"? Is there a global setting I'm missing?
I'm glad it's available, though, without any plugins!
I found it a little annoying that SRS is immediately explained to mean Spaced Repetition System, but then the F is added without explaining what it stands for. Most references of the article do neither. Except https://github.com/open-spaced-repetition/fsrs4anki/wiki/The... which says the F means Free. Seems a little too easy? I found nothing else. Chatgpt says it means Flexible, which actually makes more sense? Anybody else can chip in?
When "FSRS" is first used it's a clickable link, and the first sentence on that link is:
> FSRS (Free Spaced Repetition Scheduler) is a modern spaced repetition algorithm that was developed by Jarrett Ye.
If I do a search of "flexible spaced repetition software" I get no results, which strongly suggests the dumb guesser you're using guessed something plausible to placate its user. This is common behaviour for this type of software.
In summary, I politely suggest you critically review how you interact with knowledge on the internet.
I was working on a product which has FSRS implemented, and is heavily inspired by anki. The change we made was that rather than rate yourself, you have to type your answer and its graded by an LLM. It also has a button to explain the concept to you as if you are 5 (eli5) and you get feedback on your answer.
You can also create the flashcards by uploading a pdf and then generate them from it.
I've stopped working on it and am now building something highly similar aimed towards high school students, but any feedback is welcome. This version was built for uni students
mimair.com - I never got around to adding any payment option so its completely free
This seems impossible to me. In anki, there's "hard", "good", and "easy" which are all for "I got this right".
For my usage, "hard" is "I got it right, but I was only like 60% sure", "good" is "I had to actively think", and "easy" is "effortlessly correct, no real thought required".
There's no way for an AI to tell if my identical input is the result of a 50/50 guess, or a little thought, or effortless recall. "delay to answer" also isn't a good approximation, I have a habit of alt-tabbing and chatting with a friend on random cards of any difficulty.
I find distinguishing those levels of easy for totally identical answers ends up making SRS more effective, and AI just can't know my inner thoughts. Maybe once we have brain implants.
Yes, this is also something I have been thinking about, can an LLM really know how well I know something. There is the issue with the grading with again, hard, good and easy that I can cut myself some slack and say "I knew that" even when I didn't(and I have a strong memory of having done this myself). And there is the possibility of bullshitting the LLM and just all you know about the subject rather than the exact definition of the flashcard. I'm leaning towards any knowledge rather than specifying that the exact answer should be graded. Whats your take?
One way it could grade you automatically is by the speed of flipping the card (or entering the correct answer). If it took less than a second to confirm then evidently it was easy.
Rating yourself is an important trait of SRS, it forces you to think how you are doing, what is good enough and what not, what is more or less important, etc.
Me too. I made a specialized Kanji learning app. My different approach is in the cards. I used free dictionary data to create a card for each kanji with all the relevant data in a single card. So a common kanji might have dozens (and even hundreds) of words (each word with 0-2 example sentences) to help you remember.
I like the anki way of self rating, so I kept it. I want to be able to say: “hey, I know I screwed up the stroke order this time, but it won‘t happen again, promise” and hit “Good”.
1) The time it takes to make cards. RemNote allows you to take Notion-style block notes and quickly turn bullet points into flashcards using symbols. For example, you might be in class and make a bullet point in the format
- The quick brown fox jumps over >> the lazy dog
which you can later review as a flashcard that is automatically separated front/back by the >>.
2) The old and unintuitive UI - again, basically just Notion with flashcards. You can easily view all your notes in a bullet hierarchy and then switch over to SR flashcard practice. Even has rich code blocks, image occlusion, tables etc. A much better implementation of Anki's notes/cards metaphor in my opinion.
I am not sponsored by RemNote, just a university student who has bounced off Anki and really likes the app.
As a longtime Anki user I just want to say THANK YOU! Just downloaded RemNote for the first time and gave it a spin. I’ve been using Anki for years for language learning (Ukrainian and Russian and Arabic), but also for poetry memorization. Weird coincidence: a few days ago I was looking for an AI-powered flashcard creator: I get regular emails from curated sources that have lots of useful information, but I am too lazy to create the cards to remember the points. I just downloaded RemNote and tried the AI-generation feature: fed it an article from UkrainianLessons.com and I was amazed at how it gave me a list of useful flashcards instantly. This is a game changer. The ability to study and create “in context” is also amazing since not all information needs to be a flashcard. The Notion-like/Workflowy/Roam interface also looks like a joy to work with. Really hope this is not a fly-by-night startup, as I am really looking forward to a decade of learning with this thing after a previous decade with Anki.
RemNote founder here - been building RemNote for the past 8 years (4 in private for myself, 4 in public), and we're not going anywhere! SRS is the future.
I wonder how it compares with the current SuperMemo.
I experimented with SuperMemo around 18 months ago, and it made me fall in love with SRS again. The main reason being the algorithm is less punishing when I skip a day. Maybe it has better defaults?
I once skipped a whole week and could get back on track in the next week, in Anki that feels unbearable.
Another thing I really liked about it is that you can edit a card as you are studying without having to open a separate window, helps me stay in the flow when studying.
But… With a better algorithm I might give it a try in the future… Being FOSS is the real advantage here.
I really wish there was a FOSS equivalent to SuperMemo. Spaced Repetition is cool and all, but Incremental Reading that uses principles similar to SRS to augment learning novel content and then retain pieces of it through more standard spaced repetition is really next level.
A while back I built https://readboost.io/ but so far never advertised for it. The idea: Embed Q&A into your ePubs and optionally download Anki cards for your book. Probably gets buried here, but maybe someone finds some value in it.
They have gotten better and I think it's clear they'll continue to get better :). FSRS is already good (I use it both in Anki and for periplus.app), but looking at the benchmarks [1] there's a lot of room left for improvement.
One direction could be to incorporate semantics, which afair FSRS doesn't do at all yet. A good flashcard deck will have a lot of semantic overlap, e.g., a card for the vocab word itself, that word in a sentence, etc. Struggling with one component is a strong signal you'll struggle with another.
The same thing could be done for just better spacing, so you don't "cheat" by having too closely-related cards next to eachother in a review (the review signal will be less noisy).
Yes, we can improve FSRS in that way. But it requires to collect a lot of review data with cards' content, which breaks Anki's privacy policy. And FSRS is my side project which has squeezed all my free time... I'm not very motivated to improve it now.
systemS? There is only one program out there that is viable: AnkiDroid.
Anki runs on desktop: you have to be chained to a desk rather than taking advantage of idle moments when you are on-the-go. Even if you have it on a laptop, you still need a place to sit; SRS on mobile can be used anywhere, like standing-room-only public transit.
The AnkiMobile companion app for iOS is a paid app that is somehow chained to the desktop version, whereas AnkiDroid is a full-featured clone of Anki that you could use air gapped without ever syncing anything to or from another device. It has integrated management of decks and note creation/editing.
Every other SRS app out there is just playing very distant catch-up to Anki/AnkiDroid. They usually mention Anki in their pitch, trying desperately to explain why some very minor and very subjective negative point about Anki is worth switching to their massively inconvenient solution.
Do any of these algorithms use vector embeddings to determine the semantic similarity between cards? Seems like that might be a useful parameter for tuning the algorithm, since you’re likely to forget something similar on a topic you’ve forgotten things about.
I probably need to go read the studies but of SRS is so great, why aren't all schools just SRS farms (or are they?)
Especially for language study, as a friend put it, speaking a language is like learning a musical instrument, no amount of book studying will teach you how to play the instrument. The way you learn to play is to play. And similarly, the way you learn to speak is to speak. Sure, you can fill your vocabulary, but I question a little how much it helps in context. Obviously it's not zero. I'm sure curious, if there are better methods than SRS for language learning given that hearing, creating, understanding, and speaking whole sentences is the goal, not individual words. I can generally learn a new word in my native language with one exposure, no SRS needed.
I'm building a language app based on using LLMs and spaced-repetition.
We generate cards that respond to speech to evaluate card recall and pronounciation (via speech recognition). We don't market it as AI but behind the scenes we use LLMs to explain the context behind every word and phrase, offer additional usage examples and cultural notes, and also generate roleplays based on specific topics & scenarios.
Are there any algorithms/plugins that are optimized for an on-/off-review style (ie, potentially months-long gaps between sessions)? I know that the ideal would be to do reviews every day, but I'm doing this for pleasure and I'd rather tweak the algorithm to what works for me than the other way round.
I'm not ready to share a link to my actual implementation yet, but I've been working on an SRS system for Chinese and been using it as my daily driver for about 3-4 years now, after previously using Anki and getting frustrated with how reviews pile up after a couple of days off.
I've done lots of tweaking to the algorithm over the years to make it feel like I'm less surprised by the scheduling, and less like a slave to it. One very stark difference between mine and Anki is that I have a large number of "overdue" cards, but the system still prioritises when to show me the overdue cards with quite a few different metrics based on how overdue it is, how new it is, how long the current interval is, etc. So, like Anki, I still just double the interval for correct cards, but for incorrect cards, the reviews are repeated same day until they're correct, and then the interval is reduced a lot more than Anki. So, the cards then become overdue sooner, but because the scheduling of overdue cards is better, they get pushed later if your overdue queue is too large, and sooner if you've not got anything more useful to review.
FWIW, my typical session is 40 minutes per day during my daily lunchtime walk, and I'll get through about 150 cards in that time. If I'm on a long train journey, I'll often clear out double that or more, but the disaster situation of being on holiday for a month might leave the queue with a couple of thousand extra cards, but they never seem unmanageable. Even after a 2 month break when I was travelling last year, and only doing reviews on flights and trains, I'd definitely forgotten some words from not reviewing at the appropriate time, but the percentage of totally forgotten cards felt better than I used to experience after just missing a few days with Anki.
One thing the article mentions that I don't massively concern myself with is desired retention. I'm not sure I'd want to express it as a target percentage, but I've definitely been thinking about how I want to change things to deprioritise stubborn words without just suspending them or deleting them. I definitely find that having them keep showing up, so I might see a pattern of them wrong twice each day before finally getting them right, after a few days of that they do usually suddenly stick for good. But sometimes I look at the word and think I don't really care if I remember it or not.
Does anyone have tips for how to use space repetition to be a better knowledge worker? I feel like i could use it to have a better memory of business processes, but i dont know how to get started.
I gave up on spaced repetition systems, even my paid memrise subscription, because I couldn't find good flashcard sets. To create good flashcards, you need some domain knowledge. An AI can pick facts from wikipedia and quiz you on them, but it takes a real human to identify what knowledge is relevant and worth learning.
I would pay for an e-ink tablet dedicated to notes and spaced repetition. (I know there are e-ink note taking tablets, but none of them have spaced repetition.)
I'd like to be able to take freehand notes, and then be able to block out, or blur, certain sections and each blocked or blurred area becomes a spaced repetition entry.
Or, in more detail. I'd like to look at a page of notes and loop select a certain area. That selected area becomes a spaced repetition item. After the initial loop selection I can do another loop selection to blur one or more areas that would be blurred. Etc, etc.
There's a number of happy Onyx Boox users using AnkiDroid.
You can probably do what you want with the in-built image occlusion feature. Might be worth downloading an Android emulator and seeing if we meet your workflow requirements.
I find with spaced repetition that it works really well for some well-known things like vocabulary (EDIT: well-known meant as "spaced repetition is well-known to work for this use-case, not well-known as "the subject is well understood"), medical etc. but for everything else it becomes a struggle for a long time.
I have been trying for years to fined a way to use it for mathematics and physics - with the former being more of a focus and didn't really get anywhere. For definitions it works, but it's quite hard to write proofs in a way where there is a short obvious memorization based answer. Either you spend far too much time on a card or the card gives you too much information so you don't really test the knowledge.
I also tried it for computer shortcuts - it seems to me that they are really useful only when part of the muscle memory - so practicing them works better then memorization.
Math Academy provided a self-service learning system with a novel spaced repetition algorithm which could take the hierarchical body of math into account.
It's someone I wondered, what is the point of memorizing a proof if it only ever proves something you already know. The answer is you hope it generalises. There is a possible way you can do it in SRS, being inspired by RL training. Instead of cards you'd show options within a game or simulation. But this would need a lot of expert knowledge for a single concept.
i've learned entire math topics calc 1, calc2, calc3, statistics, linear algebra with anki. It's really easy. Just add the parctice problems at the end of the chapter to the front and the answer on the back.
Hmm, I have Anki and I don't see an option for this algorithm. Anyone know how to enable it? The preferences say I'm on the "V3 scheduler" but have no option for an algorithm. I don't think I'm on the algorithm described in the blog post because whenever I don't know a card it goes back to 1 day as if it was new. Or maybe I am on it and I'm just misunderstanding how this works? I'm on Mac, Version 2.1.66 (70506aeb).
Go into the deck preset options (any deck is fine). Look for the FSRS section and check if the toggle is enabled. If it's not there you probably are on an old version.
I have been using Supermemo daily (except for when I miss a day or two, vacations with no desktop, etc) since about 2010. I have found the newer algos to be pretty good. I have not had any bugs or a messed up collection. Its one of the pieces of software that is keeping me on Windows. There is still no foss replacement for incremental reading/writing [1]. Also, Supermemo has two modes that lets you skip a few days without being overloaded [2][3]. So you don't go from 20-30 cards to 200 if you skip a day.
That being said, its just another tool in the toolkit for learning stuff. I don't think I'm that much smarter or better at anything just because I have used Supermemo often for awhile. Honestly, I just like making cards and throwing articles I want to read later into Supermemo for processing. Most of what I use Supermemo for is incremental reading, which I have never been able to find a good replacement for. I like being reminded of cool stuff I have read and ideas that I have had. I would recommend also learning and practicing various mnemonic techniques alongside spaced repetition.
Most of the other algos/apps I have tried have been okay, I have not tried FSRS because I don't really use Anki anymore. I used Anki when I was in college for about 2-3 years because I would do flashcards using the mobile app. I was still using Supermemo daily during the same time period though.
I also use Clozemaster for language vocab with Supermemo. I put the sentences and some explanations into Supermemo after I do them in Clozemaster. I do not really consider myself to be a language learner or learning a language. I pick up new vocab very slowly and do not do anything else to practice the languages I am learning vocab from. I have also been using Math Academy almost daily for about seven months which is nice, but definitely not a full replacement for learning math. Using Math Academy actually made me start working with math textbooks and online resources again.
I’m sure the algorithm can play a huge role in the effectiveness of learning but for me the difficult part was always creating the cards and actually opening the app to practice.
I've built Komihåg [1] to try and combat this: Select any text on your iOS device and a flashcard is automatically created for you, and the app is then showing you the cards on the Home Screen / Lock Screen / Apple Watch Face.
I haven't gotten to implement any sophisticated scheduling algorithm yet but will definitely do that eventually.
Cool idea. I’ll check it out. It would be cool to do something like this for single word highlights on an e reader. If I have highlighted a singe word it is because I want to add it to my vocabulary.
I'm using it to memorize all of the Paris métro stops and study for the French drivers license test. It was also a huge boon when I prepared for my citizenship interview.
I tried it for a while with my eldest child (then aged 3) to help her remember numbers, letters, etc. She didn't find it very fun past the first couple of times, so I figured I wasn't going to hoist it on her.
Anything you wanna the retain the knowledge of. Basic usage is remebering shortcuts, names of people, apis, you name it. More advanced usage is you can break down complex concepts into atomic cards, which helps you remember how things work.
HamStudy.org is exactly this, an SRS site/app that already has the questions and some explanations to go with it (the site is free, but they also have an app which is a couple bucks and almost the same but in my opinion slightly better). I used that a couple months ago I studied for the technician class license and got a perfect score when I took the test. Then I studied the general class license and got one wrong (34 out of 35 = 97%. You only need 26/35 = 74% to pass.) I could probably go for the third one next but maybe it would be more useful if I actually go get a radio and start using it first.
The advice with gendered languages is to always learn the word alongside some context that includes its gender, e.g. "Der Tisch" (The masculine table) rather than merely "Tisch->Table".
It's surprising how much easier to translate a foreign when it's given in a sentence. Also helps when there are multiple translations for a word depending on context.
Used to use it in university (CS) for cramming before tests, mostly when there were lots of definitions to memorize. Also summarizing stuff and writing your own cards for it helps already with learning itself.
I’ve been meaning to build a unix shell deck for a while. There are so many tools that are so powerful but I just don’t use them regularly enough to remember how they work when I need them.
Mine has all sorts of shit in it. Mac keyboard shortcuts. Nautical terms. Cyrillic characters. Credit card verification codes. Phone numbers. Airport codes. Ionic component names. Names of my friends’ kids. A surprising amount of Z Specification. Anything I think it would be useful to remember.
How do you manage the data? Multiple decks or just one with everything? Do you directly use the app to add new phrases, or do you have some sort of automation / tooling on your phone or laptop?
This is something I’ve been tackling myself in the language app I’m making https://store.steampowered.com/app/3220820/Bilingual_Crosswo.... Right now, I’ve added a set of front loaded intervals: 2M, 5M, 10M, 20M, 40M, 2H, 6H, 1D, 2D, 4D, 8D, and so on eventually stretching to a full year.
I’ve always felt this setup was a bit arbitrary and considered it a temporary solution. Thanks for saving me some time on research!
Interesting. I was never really happy with any spaced repetition algorithm, so I recently implemented my own dumb system which simply asks you for the number of days after which the card shall be shown again: https://github.com/kldtz/vmn
Usually my intuition about how well I know something is not too far off. If you don't specify anything, it doubles the time since the last review.
I had a similar problem where I can't remember the answer to the card, but after revealing it, it seemed too easy to make it due in a few days, so I would lie to the program and press Hard/Good. Later I removed scheduling times on top of buttons and decided to trust the algorithm. I believe it helped me to stop caring about schedule times and loosing progress on a certain card. After all, these algorithms were made for ordinary people with ordinary memory behavior.
I think my problem is that I'm not using the system as intended. I learn new vocabulary mainly by reading texts or watching videos in the target language and use spaced repetition to keep track of my progress. If I can't remember a word (as indicated by SR), I'll reread the text/rewatch the video where I've first encountered it. I don't want to keep reviewing the same word in my spaced repetition program, especially not in the same session.
What’s a good way to learn to understand concepts in a spaced-repetition way? I’ve used anki before for remembering facts or answers to specific questions, but is there a standard way to setup spaced repetition flashcards to learn, for example, when to apply a certain software pattern or something?
The folks at SaySomethingIn, that originally started with Welsh and other Celtic languages, have recently expanded to Japanese. I haven’t tried it myself, but I’ve found some decent success with one of their other courses. It’s all about spaced repetition and focuses exclusively on listening and speaking.
I like WaniKani because it forces me to type the right answer. When I tried Anki, it was too easy for me to "cheat" and press space for something I "kinda" remembered.
I do agree with the author's phrase of "...a daily ritual of feeling bad about what you’ve forgotten..." though, and would like to try the new algorithm. Is there a way to configure Anki to force you to type the correct answer?
I do think that Wanikani and Bunpro are kind of in a catch-22 on this compared to Anki. They've built their gamification features and UI on the idea that cards have specific buckets that they're in and something like FSRS is a lot more varied than that. Especially Wanikani, which has a system of unlocking more items based on your current items reaching a specific stage.
So I haven't integrated FSRS, and of these two, I've only used Wanikani, and have been playing with a reimplemention for Chinese hanzi: https://hanzi.bpev.me
But seeing how it's implemented, I think they could totally integrate something like FSRS to at least just replace their scheduling (how long until an item is next shown). The unlocking system can be implemented as a separate gatekeeping mechanism, and the buckets can be coded for certain step thresholds (instead of wanikani's "stage").
I dream of building a WaniKani competitor that uses FSRS. Unfortunately it's one of those projects where 10% of the work is building, and 90% of the work is marketing/community building/evangelism. (And the 10% is not trivial work either!)
Super nice, thank you for this post! Based on this I've updated the vocabulary learning scheduling in DuoBook (https://duobook.co) to FSRS based. We should be up to date with the science based learning :)
Japanese media is quite popular, and many fans want to watch/read their favourite thing in its original language. This is probably the reason most people learn a language, and a huge reason why so many kids around the world speak English. Chinese culture doesn't have the same impact, yet. As to Spanish, most kids who want to learn Spanish can do so at school so there is no need to go above and beyond to learn Spanish on your own.
> Chinese culture doesn't have the same impact, yet.
At this rate if 2/3rds of their popular media(manhua, games, animation) continues being cultivation fantasy featuring the exact same power system, tropes, character archetypes, often even setting(murim) and content, it never will.
Animanga were always poised to make it big, because for all their shortcomings, they have interesting, exotic(to us) themes/tropes/vibes, and go really hard on hyping scenes up.
You learn Japanese for the media and culture; Mandarin for the financial opportunities; Russian for the reverse-engineering community; Spanish, French or Arabic to be able to speak with large diverse groups of people, typically for travel; Klingon, Na'vi, Esperanto or Elvish to fit in certain communities
Accordingly, the stereotypical CS major is attracted to Japanese and Klingon, the stereotypical Business major to Chinese. Even though few follow through because of the amount of work and perseverance required
For me, it's about the media. I'm interested in Japanese anime and manga, and now light novels.
I'm not at all interested in anything I've seen in other non-English languages, except possibly Korean now, since they seem to be producing a lot of stuff.
However, almost everything that I'd enjoy gets translated to English for both Japanese and Korean now, so there's a lot less incentive to learn them.
I'd say it's confirmation bias. In my personal circle, not a lot of people are interested in the Japanese language, but I know a few who took at least a few lessons on Mandarin or Spanish.
I've learned Japanese and part of the reason is that I thought kanji were attractive. I remember watching anime on TV when I was a kid and seeing the opening credits with Japanese characters looked soo cool.
When I was a kid, most of the foreign culture I was exposed from came from the US, and then Japan followed with a small amount.
No wonder my second language was English and third language Japanese.
Never heard a single word of Mandarin in any media I was exposed to. I can understand Spanish very well but I do not count it as a learned language as it is too close to Portuguese (my first language).
1. Generally people using such systems to learn language only need to do so if they aren't immersed in the country where it is being spoken. I stopped using Anki for German after a while of living here, even though I'm still learning. Therefore, most language learners are doing so not because they want to live in the country but because they want to consume media written in that language
2. Japanese is becoming one of the most popular languages for foreign media, probably even surpassing English at this point. Anime is really huge now, particularly in the US. It has shifted from being a nerd thing to being of interest for the "cool kids" (if there is even such a thing now). Japan also had a huge and very interesting media industry in the 80s and 90s including some very novel video game concepts, most of which has not been translated
As I understand, anki's use of spaced repetition comes from how it presents you cards in increasing or decreasing frequency based on how you have answered it previously. In this way, I prompt chatgpt to ask me questions, and it revisits previous questions or topics for me based on how I've answered previously. I continue the same conversation periodically prompting it for questions to ask me.
You are so right. I just began doing this today for my exams, and it really feels like cheating with how easy it is. That, and also creating a podcast with NotebookLM with all the pdfs as source and using as a prompt "Make this a long summary for studying".
Point of feedback: I know it says it in the link, but it would be nice if an article almost entirely about FSRS actually spelled out what it stood for even once in the body of the article.
(Free Spaced Repetition Scheduler, in case anyone was wondering)
Anki is a good piece of software. But I couldn't come up with a worse scheduling algorithm if I tried (old and new one). It's like "here's the thing you just added one second ago. Here it's again immediately after. Ok you got it, you'll see it once again in a month or so lol".
It makes it unusable and every time I tried I went back to my own self written program that just lets me set/adjust the intervals myself.
When was the last time you tried? Anki used a static algorithm (SuperMemo 2) before the new FSRS - which is dramatically different.
In the short term (first day), I think it's still better to set your own intervals (typicall 1 minute, then 5, then 10). But after that, the algorithm optimizes for reminding you just before forgetting. Highly recommend giving it a try.
I try Anki every couple of years because it has an app and can sync. I also tried fsrs and rage quitted after a few tests. These people can get high and mighty on their algos and research. If they'd just add a manual interval mode they'd contribute a lot more to humanity.
The current version of the supermemo algorithm is SM-18. The author thinks SRS has gotten way better since the author was previously using an out of date version of the algorithm, SM-2.
SM-17 is linked from the benchmark repo: https://github.com/open-spaced-repetition/fsrs-vs-sm17, though I get the impression those numbers come with a dash of subjectivity. It seems fair to compare to older versions of the algorithm though because SM-17 is only used in the SuperMemo software (and Anki) and isn't widespread.
> If we step back, we realize that this scheduling system (called “SuperMemo-2”) is pretty arbitrary. Where does the rule of 1, 6, 2.5times correct + 1, reset back on failure come from? It turns out it was developed by a college student in 1987 based on his personal experiments. Can’t we do better?
Note that Anki uses (used) such an old algorithm because it derived it from an ancient open source version of SuperMemo, a software which started the spaced repetition trend. Anki just added a usable GUI instead of the convoluted mess that is SuperMemo. Newer versions of SuperMemo improved the algorithm, but they are no longer open source. I wonder how FSRS compares to current iterations of the SuperMemo algorithm.
language learning is 100% memorization. eventually your brain memorizes all the phrases that click into “situation-space,” for every possible situation there is a memorized response. language can be broken down into situational meta-phonemes. using flash cards and grammar is just a way to bootstrap yourself into memorizing all the appropriate responses for any given kind of situation.
LLMs should only be used where hallucinations can be tolerated (either low stakes, like a video game; or where competent human review exists). What you describe is neither of these scenarios. You may be trying to memorize something that's not low stakes (and if it's low stakes why bother memorizing? Just make it up as you go), and if you're using study tools you're probably not (yet) competent enough to check for mistakes.
Yeah, my immediate thought when reading this was that it's great they've replaced a formula with a better formula, but couldn't it be replaced by something smart? An LLM could in theory be content-aware, taking into account that this card reinforces these associations, which makes this other card easier to recall but this third card harder to recall. And it may even be able to say, this card is related to a more central concept, it should get priority because that will help in the longer run.
In the long run, the appeal of machine learning to me is that we can move up the stack of what we optimize for, so instead of targeting a proxy metric, say a certain recall ratio, we might actually be able to target directly the thing we care about, say ability to use these things in practice. Moving upwards in the teleological hierarchy.
You're free to choose not to memorise things, but please don't be an arsehole about people who do want to do so for whatever reason. Having said that, you seem to misunderstand the point of spaced repetition, which is that you don't memorise the same thing over and over again; instead, you memorise it enough times to learn it, and not many more.
I see a lot of discussion about SRS, and I think most can agree they have improved.
What I would like to see covered is a more vague area, but almost more important:
It’s the space in between reading/understanding something and the SRS. There are almost no standalone tools dedicated to creating flashcards easily from existing programs (web browser, PDF readers etc.) into popular SRS (Anki, Mochi etc.). They should work almost as OS additions to make everything feel native and frictionless; I don’t need another standalone tool that does X Y and Z, I just need some sort of pipe into an SRS that is Mac friendly and does the job whilst not being in the way.
If someone knows of such a tool, I would love to hear about it.
> There are almost no standalone tools dedicated to creating flashcards easily from existing programs
I think this is a common misunderstanding. Half the benefit of SRS comes from working out what the flashcards are. You have to circle around a concept, look for similarities, differences, examples, generalisations, properties, etc.
Is it hard work? Yes. Does it help understanding? Massively.
This is also a very difficult skill which, I believe, is why many people fail to appreciate SRS. They try, write bad flashcards, don't see results, and give up.
EDIT: This also leads to another common misunderstanding, that SRS is only good for memorising facts. With proper elaboration (thanks child comment), it can be used to build understanding of complex subjects too.
> Half the benefit of SRS comes from working out what the flashcards are. You have to circle around a concept, look for similarities, differences, examples, generalisations, properties, etc.
This is at least half true, but among SRS folks it's overstated.
The same argument stands for any creative endeavor.
Debussy had a greater experience than I did with Claire de Lune, because he composed it. In turn, my experience of it is probably greater than the next persons' because I learned it. Bottom of the heap is the lowly listener - but I think everyone would agree that listening is a wonderful way to appreciate music and shouldn't be diminished.
Same for literature, visual arts, etc etc.
The still greater reason that create-your-own has historically dominated for SRS decks is the specific curation aspect. Anything curated by someone else suffers from mismatch with your own intentions and prior knowledge profile.
(Plug time. Like most people, I am building my own grandiose SRS app. Some writing on it is here: http://patched.network )
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>I think this is a common misunderstanding. Half the benefit of SRS comes from working out what the flashcards are. You have to circle around a concept, look for similarities, differences, examples, generalisations, properties, etc.
Yes. I really get the urge to automate stuff, but imo half of the benefit is from doing the leg work.
Creating your own flashcards and choosing what to curate is a helpful part of the process. This doesn't mean that being able to snip something nicely into a flashcard is not beneficial.
You might be right. I remember when I used SRS seriously for language learning, I got far more out of the cards I created painstakingly than the pre-built ones that I pulled off the shelf. That is - I still remember most if not all of the custom cards verbatim.
> They try, write bad flashcards, don't see results, and give up.
But if that's the case, then wouldn't a program that takes a long text (like a book) and creates GOOD flashcards, be way superior over someone making their own bad flashcards?
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The technical term is "elaboration" and it is key to long term retention.
Fair point, please see my comment in response to allenu, in this same thread, for a detailed view.
I did not mean to glaze over this aspect, I am aware this is very important. I can not and do not use AI for automating flashcards for this reason alone. But, I think my point still stands, getting information from one disparate app into another adds a lot of friction (saving it somewhere, copy and pasting and yada yada) to something that (I believe) should be as easy as possible. We have 1 click instant payment, but I can't have 1 click get this into some sort of inbox in Anki ready to flashcard-ify?
To be honest, I have a whole frustration with apps and windows that I'm still trying to word, but fundamentally all we are doing when we are "computing" is moving information around. I wish that information was a first class citizen at the OS level that could be leveraged by any app immediately. Utopian view but this stuff ain't gonna think about itself.
That's usually done by writing and elaborating notes. I think it's not clear to most people how flash cards improve this. The original idea of flash cards is rote memorization of facts that need fast (automatic) retrieval.
I grabbed a set of flashcard for Spanish verb conjugations. The guy had put in a lot of work to get them in the most frequent order, over 3000 lines of python. It been a massive help to me and I am not sure that writing the code to generate the list would really have helped my Spanish too much.
https://www.asiteaboutnothing.net/w_ultimate_spanish_conjuga...
Agree - making cards yourself is like programming yourself for how you want to understand and remember an idea.
I've written my own flashcards app (Fresh Cards) and once in a while, users ask if there's a way to import flashcards from things like web pages and PDF files, but to be honest, I still don't know how it would work, so maybe you can help me.
From a user standpoint, would it be an interactive process where you highlight things and then click a button to say "turn this into a flashcard", or would it be an automated tool that would scan the content and come up with a list of questions and answers t hat would test the material for you? What criteria would be used to determine what's worth turning into a question and answer? And how granular should the question be? I've seen demos of things that pick out specific facts, like dates or names, from the text to turn into questions, but that might not be that useful to quiz for some material. It seems like a very open-ended process to me, so it would be hard to get right for everyone's needs.
I've tried Fresh Cards so thank you for developing that app, and trying to add cool new software into the space.
Great question. Here's one way to do it:
The first is how clunky the process of going from X to flashcard feels to the end user. One way to deal with the fact that we are crossing software border is to add an extra step where highlighting something allows you to go into an "inbox" before any cards are made. It is clear what the user has to do. They read something interesting, and add it to the inbox. When they are ready, they can head over and only then use some sort of automation (either via custom prompt for an AI or otherwise) to make the cards. This gives them another step, or interface, at which they can decide whether or not the thing they highlighted (since highlighting is easy) is actually worth something. It segments the process into clear easy sections: highlighting, deciding which highlights to flashcardify (and therefore keep), and flashcard review.
It definitely is an open-ended process, and I appreciate that apps need to have a strong opinion on how to direct users from start to finish; but I feel this is definitely possible now with cheap and quick AI.
I didn't answer every question but hopefully that helps somewhat.
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I was an early user of FreshCards, and it’s a beautiful app, but creating cards was too much work. No share sheet or similar integration.
The easiest thing, which I believe I suggested, was highlight->action to create a new card front, and highlight->action to creat the back or a new front. It needs to work well casually in general, and easy when focused.
I’m sure AI could theoretically help but not sure it’s necessary. Part of the benefits of most cards is creating them yourself.
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The macOS services model seems like a good fit for this kind of thing. Services are little bits of context-aware functionality that apps expose to enable integration between apps without active developer involvement. An example, in most Mac apps if you select text, right-click to open the context menu, and open the Services submenu you’ll see a number of services that do something with the highlighted text.
Ideally the SRS app would make services available to facilitate quick creation of new cards, so for example one might highlight some text, right-click, and select Services → New SRS Card… which then opens an in-place lightweight card creator dialog.
I hadn't thought of this; thank you for bringing this up. I will actually read into this. I didn't write it in my original comment, but I almost mentioned the OS because I'm coming round to the idea (albeit slowly) that the OS needs to provide some sort of hook into this capability natively for both maximum adoption and also ease of use (for both developer and end user).
Perhaps Shortcuts are now powerful enough to do this as a PoC, providing the SRS has some sort of open API that Shortcuts can take advantage of.
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This is how anki already works on Android, using a custom intent.
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This is what we've built RemNote for! You can add your sources (PDFs, websites, YouTube, etc.) and create cards directly from them. Either with AI (click on a sentence => get an AI card), or by highlighting a sentence and writing your own card.
It's not at the OS level, but I think a focused standalone all-in-one experience is actually better. We've explored a chrome extension here that does something similar to what you suggest, but it somehow hasn't proven useful in practice. I always keep coming back to just doing everything directly in the tool (upload PDF, take notes, make cards), as it helps me focus deeply on what I'm learning.
Love RemNote -- ability to take notes and create SRS cards within the notes is so sick
Does RemNote use the algorithm described in the link or something else?
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Some examples I'm aware of (mostly in the language learning and especially Japanese learning space)
- subs2srs MPV script: create srs cards from subtitled videos, if you have subtitles tracks for source and target language it will fill them both in (though that sometimes has caveats, different languages may distribute the meaning of a line of dialogue over different subtitle lines)
- asbplayer chrome extension: inject extra subtitle languages into streaming services and create flashcards from them similar to subs2srs
- yomitan: browser dictionary lookup, primarily for bilingual dictionaries for Japanese and Chinese but also has custom dictionary support.
You can add my https://github.com/hiAndrewQuinn/audio2anki script to the space, in a similar position to subs2srs.
The big thing my script does differently is run Whisper locally to actually generate the subtitles from the video themselves. Most videos out in the real world don't come with convenient little SRT files bundled with them.
It doesn't yet shell out anywhere to automatically provide a translation, but that's more because I was already past that stage for most of its output reading-wise. It's explicitly tuned to make listening practice SRSable.
(I originally built this for learning Finnish. For the other 2 people here on that journey, https://finbug.xyz/ is where I've collected the other software I've built over the years for this.)
> It’s the space in between reading/understanding something and the SRS. ...If someone knows of such a tool, I would love to hear about it.
I have a slightly different system I'm developing:
Rather than reviewing with flashcards, review with actual content:
1. Tag the content with the words and grammar concepts
2. Estimate the difficulty [1] for you of each word or grammar concept -- the difficulty being essentially the inverse of your familiarity graphs in this article.
3. Choose content to read which balances difficulty and the impact on learning.
Since reviewing something you're about to forget has more impact than learning something new, "spaced repetition" falls naturally.
And instead of spending your review time going through flash cards, you spend your review time reading content in the target language.
[1] If you know the details of the FSRS algorithm, I'm using "difficulty" here differently than they do in their algorithm.
Not sure I understood the gist, but let me try summarise what you do generally (i.e. not just for language learning).
- Instead of flashcards, you read content/write notes. - You tag said content in some way which allows you to understand how difficult it is. - When in "review" mode, you essentially choose what to reread based on the difficulty you are feeling has the most impact right now.
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I solve this problem with a system prompt in my LLMs[1].
ChatGPT is the main spot where I'm going to be trying to understand a new concept, so after groking it I'll ask it to make flashcards which I can then just copy and paste into Mochi.
An improvement would be some sort of MCP integration between the LLM and Mochi so it can just add the card directly. I'm sure we'll get there soon.
1. https://gist.github.com/christiangenco/db4b61c315b93fc2a404a...
I’d say a missing thing is figuring out the order in which cards have to be shown.
Showing schlafen before ausschlafen, or contextually simpler cards before more complex ones.
Optimizing blindly easy medium hard and next time to show a card is probably very far away from efficient learning.
If the process is inspected, most of the forever knowledge that I acquired I heard once and internalized.
On Mac, you could make a little Shortcut that accepts your text selection or maybe even a screenshot and sends it to AnkiConnect to make a new note. Add this Shortcut to your share sheet and you can create new notes from any app. Later, go over the notes in Anki and add questions or if really lazy send the backsides to an LLM to create those questions.
Thank you - I hadn't considered this.
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If you're speaking in the context of language learning, there definitely are some great tools for "mining" audio cards from YT/Netflix and also for getting text from the subtitle tracks. Some are open source, free and easy once you get used to working with them (much like Anki itself). They're not frictionless for first-time users, though. Others are paid and a bit more newbie-friendly.
Yomitan (https://yomitan.wiki/) does this
This mostly works with Mochi - you can paste PDFs etc into ChatGPT and the Mochi markdown format is simple, so it can generate flashcards for you (I have the format explained in my system prompt so I don't have to re-explain it every time). This synergizes nicely with the fact that you really want to understand something before you make flashcards from it.
If you pay for Mochi you also get API access, so one could make a ChatGPT wrapper which adds the cards for you. But since I like to review the cards manually before adding I don't mind the copy paste step.
Yes, I do something like this now. It definitely does do the job. I just wonder if there could be something more, something smoother perhaps, and the API access could do the trick.
I built a native flashcard app for mac that includes spaced repetition. You can close the main window, so it is not in the way and just select add flashcard from the top right menu bar in whichever application you are in
https://apps.apple.com/us/app/flashcard-max/id1430950704
Just tried RemNote with their AI-generated cards features and so far looks amazing. They can generate cards from PDFs, webpages and notes.
Thank you - I'll give it a try!
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It's tricky I think, I think it comes down to specialized tools for different systems. I'm building a tool for Japanese in this direction. But of course it doesn't generalize to everything since the content and context extraction is very objective dependent.
I agree, it is tricky. But I believe it is possible, see my response in this thread to the user allenu as a middle ground.
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I've never used it, but my understanding is that something that does this is considered a "killer feature" of Supermemo. It has a mode that lets you read text (via a PDF viewer) and lets you create flashcards as you read in some kind of semi-automated way. Or something like that. Like I said, I never used it.
You’re referring to incremental reading, which yes is indeed one of the killer features of SuperMemo. You're basically just reading, but you have at the core of it an SRS (SuperMemo) to store cool ideas in flashcard form and every article (“Topics” is how they are referred to in SuperMemo) will be shown to you at a later date. I like to think of them all on a “conveyor belt” that means everything you put into it will eventually find its way back to you. I love incremental reading but for many years I have struggled to find a way to mimic this OUTSIDE of SuperMemo. The overall peace of mind and level of control I have over the learning process is quite remarkable, and incremental reading is more than just the sum of its parts. I wish there were a standalone app for your phone or iPad for incremental reading, as I would love to use my iPad to do what I do when reading in SuperMemo on my windows laptop.
No, not PDF, only HTML. There are community companion programs like SuperMemo Assistant, that enhance SM, but it‘s all fiddly.
I paid for two SM versions and went back to Anki. It‘s very idiodyncratic, the user interface is atrocious (in the latest version it finally, finally added thumbs up/down icons for grading the answer —- before that you had to remember whether 1 is good and 5 is bad or vice versa).
SM is fascinating (including task management, sleep cycle tracker etc.), but it‘s held back by its technological choices (only support for Edge or IE, and Edge only in the newest version), and for incremental reading you‘ll be mostly ingesting Wikipedia articles, because PDF isn‘t supported.
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I've fiddled with a bunch of stuff - macros, standalone programs etc - before finally settling on copy and paste. I just copy and paste a page of PDF into Anki then cloze single words (~6-15 words a page). I've worked through several textbooks this way.
Pro Tip , if you're using LLMs to learn, create an MCP tool for them to insert Anki cards on topics you're discussing in a csv on google drive, then sync that with you anki decks on your phone.
This was a game changer for me and working with LLMS, while I still think they make you dumb, and we essentially use them to offload critical thinking (almost only find myself using them when tired lazy, and just cant), if you must use them use them as a study tool.
I created a python script that checks my anki deck for the cards that I'm scheduled to review the next day and asks an LLM to generate new sentences for the cards, so that every time I see them, I see them in a new context.
I did this because I realized I was hitting an issue where I theoretically "knew" a word (would get it always correct on the card), but wouldn't always recognize it in a novel context.
I'm hoping that having the context be variable when I'm learning it will help fix this issue.
> ”I realized I was hitting an issue where I theoretically "knew" a word (would get it always correct on the card), but wouldn't always recognize it in a novel context.”
Some of the problem is due to the specificity of the training effect. I.e., if you mostly practice something through flash cards then you’re going to be training your ability to work with that on flash cards.
With language, there’s an additional challenge—many if not most words have different meanings in different contexts.
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This sounds useful. Maybe someone could create an Anki plugin that does this.
Or is there something similar already available?
That’s a really clever use for LLMs, I have the exact same problem with my Anki deck. Do you store all the historical sentences for each card or is it just a destructive overwrite each time?
That sounds like a really useful project!! Have you considered publishing it?
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> f you're using LLMs to learn, create an MCP tool for them to insert Anki cards on topics you're discussing in a csv on google drive, then sync that with you anki decks on your phone.
Speaking for myself, I’d love to see a blogpost detailing how this is done. At the very least, I’d love to know: How are you syncing csvs to anki cards and how does the MCP interaction look like for an LLMs response to the CSV creation
Ask chatgpt how to do it
ChatGPT 4o's voice mode has been mindblowing for me for learning basic Mandarin. I'm sure I will hit the limits of the model sooner or later, but it has been so much fun bouncing around my apartment and asking what various objects are called / if words are related to other words. It is phenomenal for putting together short little sentences and getting immediate validation on grammar too.
No MCP on ChatGPT yet, but I can ask chat to generate an output of what we reviewed in a structured format.
My personal peeve about Anki: I don’t like its data model. It seems to me that there ought to be collections of notes (which might be things one would download or generate with an LLM or make yourself or share with friends or students). On top of one or more collections of notes are the sets of cards to want to learn, and they can derive from the notes. This includes, roughly, templates plus some concept of which cards are enabled. On top of that is the spaced repetition history and model. There also ought to be a way to constrain what cards should be studied in a given session. (For example, if learning Chinese or Japanese, one might want to have a pencil and paper when practicing writing but not reading. When practicing without paper, one might want to skip the writing cards.)
Anki doesn’t seem to separate these layers at all. Everything is a monolithic database. Import is unpleasant. Export is unpleasant. Sharing is unpleasant. Doing anything other than practicing and editing in the UI is unpleasant. And, every time I try Anki, I get stuck when I can’t manipulate my own data outside Anki.
Is there any system out there that doesn’t have this issue?
> there ought to be collections of notes (which might be things one would download or generate with an LLM or make yourself or share with friends or students). On top of one or more collections of notes are the sets of cards to want to learn
Is that not what anki does? You have a collection of cards, each card can be in one or more decks derived from the cards.
> There also ought to be a way to constrain what cards should be studied in a given session
That's also decks. You can have your 'Japanese' deck, and then the 'Japanese::writing' subdeck for the subset which require you to have your writing materials handy.
You can also use "Better Tags" to tag cards, and then create a sub-deck with an ad-hoc tag query to only study a subset if you want.
Does creating more decks and then studying the subset you want to in a session not work for what you want?
> Anki doesn’t seem to separate these layers at all. Everything is a monolithic database.
Decks are separate files which can be shared, edited, created, studied, and reasoned about independently.
The "spaced repetition model" in anki is obviously separate from the fact that there are multiple (FSRS and the old one).
> Export is unpleasant. Sharing is unpleasant
It's just files (zip files really). What's unpleasant about it?
> And, every time I try Anki, I get stuck when I can’t manipulate my own data outside Anki.
There's libraries to manipulate anki decks outside of anki for practically every programming languages. There are literally dozens of tools that can generate and import anki cards, such as the large family of japanese "mining" tools which create anki cards from media, dictionary entries, etc etc.
It's open source, and the code has clean library abstractions you can work with, so it's trivial to nab any of the data out of it.
> Is there any system out there that doesn’t have this issue?
Every issue you described is something that I experienced in other software, but which anki solved for me, so for me "anki" is that system.
> Is that not what anki does? You have a collection of cards, each card can be in one or more decks derived from the cards.
Kind of? As far as I can tell (and I haven't spent enormous amounts of time digging in), there are decks, and a deck contains the notes, the templates (and the cards, which may or may not have any sort of independent existence outside the notes and templates that generate them?), and a deck also contains the scheduling information.
One can export the textual and markup contents of decks, but not the media, into a text file, and one can re-import it, supposedly losslessly. One can also export a deck minus scheduling information for sharing purposes. I'm not sure that one can re-import it.
Then there is a collection, which is the whole world: decks along with their scheduling info.
> That's also decks. You can have your 'Japanese' deck, and then the 'Japanese::writing' subdeck for the subset which require you to have your writing materials handy.
I'm guessing that, if I start by importing a Japanese deck from some other source (because, for example, there's a source with high-quality notes), and then I split it into a writing subdeck, and then the original source adds new notes for new words or makes changes or whatever, that merging the results is basically unsupported.
> > Anki doesn’t seem to separate these layers at all. Everything is a monolithic database.
> Decks are separate files which can be shared, edited, created, studied, and reasoned about independently.
Yes, but only as monoliths (again, as far as I can tell). I can export an "Anki Deck Package (.apkg)", but checking that into git would result in a bit of nonsense. I can't export my scheduling information and templates separately from the underlying notes (or, if I can, I failed to find this option).
>> Export is unpleasant. Sharing is unpleasant
> It's just files (zip files really). What's unpleasant about it?
Excel and OpenDocument sheet files are also zip files. But the respective tools are less limiting and don't expect the users to unzip those zip files. (And their merging and text import/export facilities are also weak, and that's unfortunate.)
I could be wrong about most of this. But Anki doesn't seem friendly to a decomposed workflow in the way that modern programming lanuages are.
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It’s amazing how every single point you’ve made here is wrong as the other commenter already dove into. On top of that Anki is one of the best documented pieces of open-source software I’ve messed with. If you’re able to program, ChatGPT can basically handle any task you want it too, I data mine the sqllite database regularly for my own insights.
My personal workflow with memorizing with Anki using LLMs is as follows: Read textbook material first. It's important that you understand what you are learning.You cannot just breakdown information into atoms and expect to understand how it works together (for example: you can learn that there are monounsaturated fats, polyunsaturated fats, saturated fats and trans fats. But without reading beforehand about them from a textbook or other source, you will not understand how they differ (in chemical structure, biological function etc). After I understand the material, I feed LLM the documents (textbooks etc) and give it the following prompt: >I want to generate flashcards from the provided textbook document using the attached PDF. Each flashcard should contain a question and a corresponding answer formatted as pairs in plaintext code block. The structure should be: "Question","Answer" >Extract key concepts, definitions, and explanations from the textbook. If in the text imperial unit system is used, convert it to metric. For mathematical symbols and equations, format them using inline MathJax syntax because I will be importing the copied text to Anki. Ensure questions are clear and concise while answers provide a direct yet comprehensive response.
After the text is generated, I check out the accuracy (in 95% of cases the cards are accurate) and I import them into my decks. The rest is good old school Anki memorizing.
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Where does your SQLite db sit? I have been thinking about creating a local database to save and feed into LLM but i have no experience with it
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Actually, every point was right and the data model is terrible. I've been using it for years. The other commenter just mentioned a list of things that the software does do and basically said "isn't that good enough for you" a bunch of times. No, it's not. Anki's concepts of flashcards, and how it stores and manipulates them, are horrible.
It's hard to do many, many things in Anki that should be trivial, impossible to do many, many things that should be possible, and the things you can do involve the types of queries being run over your entire collection that causes the app to slow to a crawl after you add about a dozen decks. And in general: I can adjust far too many things that I don't even care to adjust and probably shouldn't be adjusting, and things that should be trivial to do are impossible.
It's bad. Ankidroid is a little better, but they're also stuck with the data model.
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I think there is an argument to be made about the poor learning curve (ironic) for learning how to organize and use Anki
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You're right about the data model. I built my own flashcard app [1], so I've had to understand the database schema that Anki uses and a lot of it seems very inelegant, but on the other hand, I can see how it was purpose-built and probably grew over time and things were tacked on. (For instance, there's one table that has a single row, where several fields are simply JSON dictionaries.)
On the other hand, how templates work and how cloze deletions work are really nice. With the flashcard app I built, I didn't have templates, but did have a very basic cloze deletion system where you could mark text to be "hidden" on the front. It was very limited in that you'd only ever get one front/back combination. You could hide multiple bits of text, but they'd all be hidden at the same time. With Anki, you can create multiple groups of hidden text, so that you end up with multiple flashcards from the same note (i.e. you hid three separate groups of text, so you now have three different cards to test with).
I've been working on an update to my app to incorporate templates and cloze deletions like how Anki does it, so now I appreciate that aspect to it.
For my own database, at least in the new version I'm working on, I've ended up creating a schema where the individual attributes for each card are thrown into their own tables, but this is mostly because I needed to support updating individual attributes separately since I use a very simple journaling system to sync across devices. With Anki's schema, I can see why sync was complicated (at least in earlier versions) since it wasn't really built for it.
[1] https://www.freshcardsapp.com/
For language learning only, but perhaps my own https://thehardway.app model suits you better (flashcards inside markdown-ish notes)
How much will you be charging for the app? Is it using LLM ?
Sorry, but your landing page is really awful. I’m not allowed to learn about your app because I’m on a tablet? And I have to give you my e-mail address, even though I know nothing about your app so far?
Suggestion: Allow me to browse your site and learn about your application, and I’ll decide if it’s interesting enough for me to open it on my desktop later.
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Yeah, if you're learning a language, have a group of restaurant words and another group about air travel, etc. Then then user will associate them.
For that I buy a vocabulary book, or a phrase book. As I read through it, and if I don‘t know a word or understand a sentence, I try to learn it using various methods, and create an Anki card to keep it in memory. Anki is just to retain the word.
On a plus side, you can buy specialized vocab/phrase books, I have one just for onomonopias. Also my beginner vocab books come with recordings from actual native speaker voice actors, which I add to the deck. Much better quality than anything an LLM or speech synthesizers can give you.
What are you talking about? Anki explicitly has the concept of 'notes' from which one or more 'cards' are derived. You can absolutely easily make custom decks that only have certain card types.
Yeah I'm confused too. "I don’t like its data model. I wish the data model was instead <perfectly describes Anki's data model>".
Seems like a YC business in the making. There's demand for improvements, and you already have your pitch.
Sprinkle in AI and you'd be a shoe-in.
If anyone's interested in experimenting with FSRS, we at Open Spaced Repetition provide official packages in Python, Typescript and Rust
PY: https://github.com/open-spaced-repetition/py-fsrs
TS: https://github.com/open-spaced-repetition/ts-fsrs
RS: https://github.com/open-spaced-repetition/fsrs-rs
Currently ts-fsrs and rs-fsrs support FSRS 6 and py-fsrs should also support FSRS 6 in the next day or so. Also, both py-fsrs and fsrs-rs include the ability to optimize the FSRS model from your past reviews!
I used this for spaced repetition for opening training on Chessbook, can vouch that the Rust package is excellent. Easy to use and immediately lowered the training load on our users while keeping retention high. FSRS is awesome.
I use Chessbook and mostly like it, but I wish there was a way to configure the spaced repetition parameters. In particular, I find the frequency of reviews too low to retain well, especially for recently added moves.
For Ruby folks — I’ve forked the FSRS gem to fix an issue where new cards were being spaced 60 days apart instead of 60 seconds:
https://github.com/arvindang/rb-fsrs
Originally adapted from the Python version linked here.
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I used basically this algorithm in college with the following setup:
Make a word document that lists all the keys to memorize vertically. Save as PDF
Open the PDF in a viewer with annotation tools. Make a clickable note in the margin just next to each key. Write out the value to memorize in the note field.
Cycle through the clickable notes. When you get one right easily, drag the note more to the left in the margin. As you cycle, focus on the ones furthest to the right. If you get one wrong, move it a bit further to the right.
In general the notes will move to the left until you're comfortable with all of them. And the balancing of which ones you need to see and focus on plays out very naturally and you feel in control the whole time.
There are many downsides with this compared to a tool like anki (e.g. I only used it on a laptop), but there was also something about it that just worked really well for me, so I never ended up switching to a different tool. But this was before anki had the similar algorithm described here. Maybe my experience would be different today
This sounds interesting, but I'm not sure I'm picturing it right .. You wouldn't have an example file handy?
I've been looking into FSRS since I'm building a language learning app[1], but I haven't implemented it yet. Can FSRS work if I don't want to have 4 choices - bad, good, hard...? I have found myself to get into a decision paralysis so just bad/good works better for me. Plus I can swipe the cards tinder style! :D
My second reason is that I'm worried about the complexity - both from non-nerdy users perspective and me having to debug it.
[1] https://vocabuo.com
According to the FSRS author [1], it will adapt to two buttons.
[1] https://www.reddit.com/r/Anki/comments/16t2lva/comment/k2cor...
Yes. Some months ago, I forget whether it was v5 or maybe before, the 2 button grading approach meant that it actually performed better for users (ie. it performed better for users that explicitly only used two grading buttons).
I don't know if this is replicable with v6, or not. I would be interested to find out!
I am the creator of Trane (https://github.com/trane-project/trane/) which can replace Anki and similar systems for domains that have a well-defined hierarchy between subskills (turns out that's most of them, including learning vocabulary).
There are several unresolved issues with Anki, SuperMemo, at al.
1. Emphasis on memorization. I wanted something that could be applied to domains (music) whose scoring is not based on memorization, but mastery.
2. Lack of any hierarchical information limits how well it works to learn much larger skills. It's trivial to replicate the functionality of Anki with Trane: just have one lesson where you put all your exercises. Anki cannot replicate what Trane does, which is to use the dependencies of the many sub-skills to track and limit progress until mastery is achieved.
3. Emphasis on creating your own exercises. You are expected to come up with your own decks, which takes a lot of time. For complicated skills, you need to be a domain expert to really know how to do this.
Trane is pretty much done, and I have used it to teach myself music. It does not have a UI at the moment, so I am pretty sure I am the only user. Not that I mind, because I rather not work for free.
Currently working on a literacy tutor that will be built on top of it. When it's complete, it will be able to guide all students from learning their A-B-Cs to reading and writing at college level, backed by the most up-to-date research on reading and writing acquisition. Hopefully I will be able to release an MVP in the middle of the year.
You might be interested in reading the literature on Knowledge Tracing, which is a superset of spaced repetition, aiming to predict what the student knows from their answers.
The simplest approach is Bayesian Knowledge Tracing [0], which is just a simple probability update and an Expectation Maximization optimizer to fit the latent factors. The standard version assumes an independent set of skills with no forgetting, but there are extensions for that [1] [2]. PyBKT [3] implements some common ones, so take a look there.
Learning Factor Analysis [4] seems to work considerably better than naive BKT, while being very simple to implement (it's a logistic model, sharing the family with most spaced repetition algorithms), so that might be promising if the hierarchical dependencies are incorporated. Some researchers have been applying increasingly complex NNs [5], including transformers, but personally I think that's just more parameters to overfit [6].
I'm not an expert. I only built a basic KT tool to prepare for the national Ukrainian exam and found these along the way.
[0] https://www.cs.williams.edu/~iris/res/bkt-balloon/index.html
[1] https://link.springer.com/chapter/10.1007/978-3-319-07221-0_...
[2] https://educationaldatamining.org/EDM2011/wp-content/uploads...
[3] https://github.com/CAHLR/pyBKT
[4] https://arxiv.org/pdf/2105.15106v4
[5] https://pykt-toolkit.readthedocs.io/en/latest/models.html
[6] https://arxiv.org/pdf/1604.02336
> For complicated skills, you need to be a domain expert to really know how to do this. (...) I have used it to teach myself music.
It sounds like you must have had some interesting difficulties with that, not having been a domain expert in music. What were they and how did you overcome them?
I have been mostly working on a set of courses based around backing tracks I got from a course called “improvise for real”. So I only had to make the structure of those backing tracks explicit, which only required knowing the circle of fifths.
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Spaced repetition has been all the rage for 20 years now.
Dozens of apps, thousands of lectures, and it turns out its not really a silver bullet.
There's nothing really wrong with it, it's just that people tend to fall off the same way they do on any other education pattern.
A couple years ago I was thinking "If Google and Apple really cared about kids they would make a spaced repetition unlock system", where by you have to make note cards every week and then have to answer correctly to get into your phone. (obviously requires some bypass system, other rules, etc)
You could probably jury rig it with a popup that comes up after you unlock, but people would never install it anyway.
Spaced repetition is time-optimised, but it isn't self-discipline optimised, nor motivation-optimised. If you're limited by time, it's very efficient, but it drains motivation. If you're anywhere close to being limited by motivation (or, failing that, self-discipline), it just causes burnout and failure.
I credit Anki to my success at GCSEs and A Levels despite having a head injury, and I also credit it to me burning out so hard I took a gap year!
And I'm enjoying the gap year, but Anki made it a near necessity.
There was an interesting post here awhile back about autonomy and motivation. The gist was people's motivation is proportional to their autonomy. This is quite intuitive, you can see people are really motivated when they have autonomy (think kids with Minecraft, musicians with instruments). One terrible thing about Anki is that it probably is horrible for autonomy. Quite possibly using anki actually has a negative effect on motivation.
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I don't understand, wouldn't it be worse for motivation to take longer to achieve the same results?
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>I also credit it to me burning out so hard I took a gap year!
Do you think targeting a sub-90% difficulty could help reduce burnout? My experience is that working to recall something I'm on the verge of forgetting can be very effortful.
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IMO, the most limiting feature is that spaced repetition is a method for memorization, but memorization is only one part of learning and it's very often not the most prevalent part.
But when memorization applies, gamification is a really good way to avoiding burnout (as long as you don't overexpose yourself to it). There are many spaced repetition games for children, I don't know why people make so few of them for adults. (But then, fearing the duolingo owl is a popular meme nowadays.)
I have downloaded 3 card decks for learning Spanish.
The main deck I use for verb conjugations expects me to use it for maybe half an hour per day or the list just build up (I have no idea if this is standard behaviour, but I don't seem to get the same build up on the other decks that I use less frequently).
While it end up being a bit of a chore some days, I appreciate that it does force me to use it every day, which is good for my discipline.
I would say the implementations are time optimized, over the others. I’m building a language learning application, and have put in a lot of effort to make sure that the Spaced Repeition is motivation-optimized.
It’s centered around your performance and review times, to make sure you aren’t struggling to much; no due dates to avoid Anki slogs; gamified with some internal mechanics; dopaminergically influenced with aspects of randomness.
Spaced Repetition is just an equation (SM2 is laughable simple), but a lot of applications just slap a UI on it and call it a day, but that’s not the only way to use it!
> it turns out its not really a silver bullet
One thing that bothers me about SRS is that it doesn't get enough attention from people who understand the difference between memorization and language acquisition. It gets a ton of attention from people who are doing test prep or who get intrinsic reward from their memorization accomplishments.
Memorization is not my goal — I want to get better at reading Spanish and French — but I find that drilling on vocabulary and example sentences helps a lot. I compare it to using scaffolding in construction. Scaffolding is not a building. Scaffolding doesn't serve any of the purposes a building does. But if you need to build, expand, or refurbish a building, sometimes building scaffolding in and around it can speed things up a hell of a lot.
I wish there were better guidance for using memorization to assist in language learning, but the world seems to be split between people who are satisfied with memorization as their goal (for test prep or intrinsic satisfaction) and people who dismiss memorization entirely because it isn't their goal.
If I weren't already busy enough using Anki to accomplish my own goals, I would almost certainly look into deeply integrating LLM calls into it so that we could e.g. practice writing and speaking with it in a way that is much closer to the kind of immediate feedback loop you get with a tutor.
For now, I make do by having Gemini Flash 2.5 open in a separate window and checking my short answer writing responses with that.
There's some UX problems of SRS (that I'm working on) that makes it high friction 1) Time taken to create cards 2) Need for self marking 3) Creates a one to one mapping of prompt-answer 4) If you're an autodidact, you have to teach yourself first (alternatively called understanding, scaffolding, etc)
More fundamentally, SRS isn't a superpower because it's just very specific to creating a direct prompt retrieval. Generalization is poor. Even creating a graph of knowledge, is a chain of edges between bits of knowledge, isn't done very well here.
And I suspect there's a very deep, fundamental difference between recollection knowledge and logical-modeling knowledge. Recollection seems very similar to a dictionary access, and if you recorded the time to recall in humans I suspect they'd all be constant. But learning the knowledge of a logical model, like of a mathematical concept, appears to be vastly different and have very different time to compute.
Proponents of SRS will point out logical models need facts as well, like formulas, lemmas, etc. Which is true. But if you already grasped it before you'd grasp it faster the second time. So the practical use of SRS is a significant step above having a very well sorted and labeled notebook, but still way below becoming a genius.
Poor generalization (overtraining on prompts) and loss of context over time are the biggest issues I've found with them. Slow card creation workflows and needing to rate your own reviews are merely UX issues -- losing context and losing generalization make SRS actively harmful when used for some topics.
There's 2 solutions I've thought of but haven't tried implementing:
1. A free-recall based approach. Free recall allows you to operate at a higher level of organization and connect concepts at lower levels. However, how you would schedule SRS with free recall is not clear.
2. Have an LLM generate questions on-the-fly so that you don't overtrain on prompts. You might also instruct the LLM to create questions that connect multiple concepts together. The problem with this approach is that LLMs are still not so good at creating good test questions.
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Where do we find more about what you’re working on? :)
> Dozens of apps, thousands of lectures, and it turns out its not really a silver bullet.
Easy statement to make when you're not defining the silver bullet. Kind of like saying dieting turns out not to be a silver bullet.
I've used spaced repairing for over 6 years. It's been transformative for me.
Would love to hear about how it was transformative for you
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What info did you memorize?
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You say that but it's completely revolutionized the way medical students study.
IIRC the effect was so profound they had to modify the structure of some tests or something to that effect.
And polyglots have been using SRS for years.
As always, the real problem when people fail to do something that works is psychological, not technical. I'd say anyone who made an Ozempic for motivation would make a killing, but I believe it's already a scheduled substance. Maybe one without potential for addiction or abuse. Or maybe an Ozempic for conscientiousness.
>I'd say anyone who made an Ozempic for motivation would make a killing
This is just ADHD meds right? That's why the uni students spend so much buying them.
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I'm not so sure. My brother's medical school had to tell students they had to study the actual material rather than Anki decks because so many students were failing tests.
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If you're expecting it to be a silver bullet, then you're in for a bad time.
You still have to do the work.
It's a lever or a pulley, nothing more.
> You still have to do the work
Spaced repetition is doing the work.
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I would expect the flashcards produced under this regime to be utterly useless, like a flashcard with "A" and the answer is "B", or simple math problems. In other words, Goodhart's law.
This is a very big problem. Virtually all the results from research here comes from some form of simple word recall. Direct recall occupies some part of real world tasks, but IRL if you're stopped by doing something it's people not because you can't remember it (and you could look it up if you forgot).
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It's a silver bullet for learning facts. You still have to actually do the learning. Nobody was claiming it would download knowledge into your brain Matrix-style.
You'd probably say silver bullets aren't a silver bullet because you still have to load the gun and shoot it.
> There's nothing really wrong with it
And a gigantic amount right with it.
This is a strange comment because it shrugs off something that has been transformative and hugely useful to a lot of people because it doesn’t fix all conceivable problems.
I don't think it's a strange comment. He's mostly right (and so are you, but I think you're talking past each other). There's nothing wrong with SRS, and I agree with you that it's basically like cheat codes for memorization, but there is a limit to what most people can do. i.e. most people do tend to drop off.
I remember reading some stats from WaniKani (Japanese SRS app) a while back...
WaniKani has 60 "levels" to learn 2000+ kanji. Each level takes about a week (there's no skipping ahead), so the material takes about a year of study to complete -- that's if you're going at breakneck pace, which most people aren't.
According to the numbers I saw on the WK forums, ~8% of users reach level 30 and less than 1% reach level 60... and that's just to learn as much kanji as a 9th grader. That's to say nothing of the grammar and the 20,000+ vocab words you'll need to SRS to truly learn the language, or the thousands of hours you'll have to spend speaking/listening/reading, immersing yourself in native content, etc.
People give up very easily. The language learning community often gives year estimates to reach "near-native level" in a language based on frequency of study. In reality, the process takes a lifetime. I don't know if people truly know what they're signing up for when install those apps and begin studying. It's a lifelong commitment. It's just something you do now, every day.
You can stop at any time of course, and most people do (more than 99% of them apparently).
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I think this is a brilliant idea! Surprised nobody has built it yet. I would definitely use it.
> Dozens of apps, thousands of lectures, and it turns out its not really a silver bullet.
I mean, you say that, but I did mandarin for maybe 6 months, I did reviews for maybe a year or two on and off, I haven't done a review of mandarin for 8, 9 years now and I can still recall quite a bit of it. So for me it's worked quite well.
I’ve been using Anki for about a decade now, and as far as I’m concerned, the only real improvements needed are design/UI based. It is functionally irrelevant if the algorithm is optimized or not when the actual user interface seems boring to potential users. While I do like that Anki has power user options, it’s also very unintuitive to the average person just looking into it.
Which is really a shame, as the spacing effect itself is such an underrated aspect of human learning that it almost feels like cheating.
AnkiDroid maintainer here: we're actively working on a new design for the reviewer (currently available in the Developer Options in the production app).
I don't think any of us are satisfied with how most things look, but we're severely under-resourced.
Feel free to email me if you'd be interested in getting involved with the Android side of things.
I love Anki but it’s an archetypal example of “designed by an engineer”.
It’s powerful, with a lot of depth to its features - but it’s also hideous, clunky and unintuitive, and it takes a long time to figure out how to use it effectively.
An HN-reading tech nerd can probably figure it out, but your average Duolingomaxxing normie? No chance.
>An HN-reading tech nerd can probably figure it out, but your average Duolingomaxxing normie? No chance.
Me, the person who reversengineered obfuscated code doing weird crypto primitives and submitted patches to linux kernel can't figure it out either. Maybe I'm not HN nerd enough, so I had to do the duolingo to pass my citizenship exams.
Anki seems like it works for a lot of people with a very specific flow, but I don't know what the flow is and why it doesn't work for me. It's weird.
Reminds me of how I'm using Anki on iOS to learn German, and my phone's configured language is German, except for the Anki app, which is ironically the only app I've configured to be in English because I couldn't understand what 80% of the buttons meant.
Those reasons are why I love Anki. I'd rather have a program that exposes every mechanism of how it works and allows me to access it than a program that doesn't and the program appears to appear to work by magic. Give me visible cogs that I can tune and a good manual any day of the week.
Anki is refreshing function over form design. It's beautiful.
I think the default settings are fine for 99% of the users. I've used them to "master" a language and I've been more than fine. Actually, I'd argue I was more effective than people who didn't use SRS.
Sorry, but what's clunky about it? All buttons in reach of your thumb on the mobile app and usable keybindings on desktop?
Is there not enough useless whitespace around every button?
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Ah i've been curious about what improvements folks would like to see most in SRS learning and this thread is gold! It does seem as though Anki’s core is undeniably solid, yet its power can also feel like a hurdle for non power users. Additionally, i'm not sure "boring" is necessarily bad, as i've heard and to agree that learning may be best when it feels like a strenuous workout.
I've been exploring some of these questions in my personal foray in design. If anyone’s interested, I posted an early experiment here: https://dribbble.com/shots/25737616-Descartes-Design-Flashca...
I’ve been reading about spaced repetition and Anki for years. Never got around to actually trying it on anything.
I wonder if there are any good recommendations for something to try it on?
Language learning is the classic use case, but I also use it from everything from historical facts to encyclopedia entries on a subject I’m trying to master.
Probably the simplest use case to get started is improving your English vocabulary. (Assuming English is your first language.) I try to add a card for any word I come across that I don’t know the meaning of, and it works very well.
Try to learn a different writing system, alphabet or not. Arabic, Cyrillic, Hangul, whatever. It has finite number of cards and you don't need large context to understand them.
A quick and easy one is learning the NATO phonetic alphabet. You can find premade decks for it.
Leetcode patterns, and common problem types to apply those patterns to.
My biggest gripe with it is how clunky the editor window is. That’s the main part that’s due for a redesign in my opinion.
It has other oddities too though, like the tab bar in the main window that doesn’t act like a tab bar. It should also really have two button mode (Again and Good only) for the review screen as a built in option, too — the addon that adds this is very popular and it’d be dead simple to implement.
Compared to i.e Duolingo, the app is quite boring. I still have been using it for years. But I sometimes wonder if adding a bit of gamification may help. For instance, streaks, sound effects, etc. Obviously, those should be optional
I've quit Duolingo because of the gamification. It's far, far too much, and it puts me in the wrong mindset for learning. Instead of concentrating on the knowledge, I'm gaming the system to improve my score the most. There were times I would stop learning because I knew if I saved it for later, I could use a multiplier for a higher score.
And the daily emotion-tugging streak reminders started to actually piss me off.
On top of that, at one point they were changing the icon regularly and made it really ugly. Despite a ton of complaints, they left it that way for a long time.
So I canceled my subscription and I'm done with them. I'll find another way to study that I like (I've already tried Anki and it works, but I don't like it) and isn't mentally abusive.
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I used to be something of an Anki evangelist and recommended it to anyone that would listen. But the minute I showed it to someone that isn’t already technically-minded, their eyes glazed over and they lost interest immediately.
I think it just needs a fresh minimal design, a tutorial, and some premade decks that aren’t just the half-baked free ones.
This doesn't work on mobile of course, but for desktop Anki there are plugins that go in this direction.
For example review heatmap will give you a streak.
There's an excellent heat map addon that helps with that. Some people have tried the "dopamine effect" style things (confetti when you answer a question etc), and it didn't work for me, but there are addons for it if you'd like to try it.
There are streaks, but they're hard to find. There is a heat map add-on that makes them a lot more obvious.
Yeah, you do Duolingo because you want to. And you control perfectly how much duolingo you do any give day.
You do anki because you feel like you must and you have very little control over it.
it'd be nice to have a better UI. but the reason people don't use Anki isn't because it's hard to use. it's because the time to value is high, and the value really only comes from long term discipline and motivation.
people that are motivated and will succeed with Anki regardless of design will power through an annoying UI. so with better design, you'll increase top of funnel but radically decrease conversion.
I wrote "Why Anki Doesn't Work for Me" (https://medium.com/@iandanforth/why-anki-doesnt-work-for-me-...) six years ago, which means it was before the new algorithm was implemented. While Anki likely still suffers from all the other issues I mentioned, this directly addresses my point (3). I'm going to have to give it another try and see if the other points are still too much friction, or if the frustration caused by the algorithm was a majority of my pain.
I had similar issues... anki would drill me hard while stuff was still in short term memory (single session) then push it back weeks or months before I had any retention. I'd get to it again and it'd be completely gone, queue re-learning it from scratch.
I brought it up around the time I tried it and got shouted down. Pretty much every spaced repetition app was treating anki like a holy emissary, so I gave up on spaced repetition entirely.
There is definitely an aspect of online language learning communities where certain sanctioned methods are treated as gifts from the gods, while other methods brand you as a no-good heretic who doesn’t really want to learn the language.
I had a similar experience. In retrospect I felt like I was wasting my time trying to use it. I somehow ended up with memorization sessions that were too easy and impossibly hard and there seemed to be no way to kind of bridge the gap.
I switched to FSRS via the extension partway through my A levels. I also used the little google collab notebook to custom fit it to my learning patterns - I'm not sure if that's in the version that was merged into the main version.
It about halved the amount of reviews I needed to do, and they didn't come up in bursts, so they were a lot more pleasant. I didn't quite believe it at first, and worried that it would be less effective, but it worked just as well if not better.
I really recommend giving it another try!
> I also used the little google collab notebook to custom fit it to my learning patterns - I'm not sure if that's in the version that was merged into the main version.
It was! There's a little "Optimize" button in the deck settings that you're supposed to click once a month or so, which does what the old colab would do for you.
I’m doing my A-levels at the moment with economics and geography still to go, do you have any tips or advice for leveraging FSRS / tailoring it to my learning style that is more specific to A-levels, based on your experience?
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WaniKani has the best UI for any SRS software I've ever seen, but they suffer from the old algorithm. They're guilty of all of your points and the article's fourth heading concern:
> And the idea that you’ll literally never see a card again after the last interval is terrifying, as it means you’re constantly losing knowledge.
What I find interesting about spaced repetition is the underlying thesis that raw memorization, in certain contexts, is playing a more important role for learning than what some modern education ideas would make you assume. In mathematics or programming, for instance, there is this idea that understanding a concept is better than memorizing algorithms or recipes (derivation methods for instance). But spaced repetition challenges that, in a sense.
If you zoom out and look and the shift in educational systems from pre-industrial revolution to modernity, memorization is a key topic. Basically educational reformers wanted a switch from memorization-heavy classics-based education with lots of Latin and Greek – to one with less emphasis on memorizing and more technical focus, more “understanding” and so on.
Like other big cultural shifts from the time, the correction was necessary but also probably went too far in the opposite direction.
Which is a long way of saying that memorization is underrated and it mostly has a bad reputation from anti-Victorian reformers.
Most modern programming lives by the idea that you don't need to remember something as long as you remember where to look it up. Of course that's only true for some things: I can look up an API call, but I need a reasonably complete working knowledge of the concepts offered by my chosen programming language and its idiomatic design patterns. In most cases this is maintained through application (practice is unstructured spaced repetition), but if I wanted to get into say C++-based driver development then spaced repetition would definitely help build and maintain the necessary knowledge
It makes sense to memorize elementary operations that are reused frequently because that frees your mind to focus on the "higher level of abstraction" of learning. You probably learned the multiplication tables by heart before you were asked to do more complicated multiplication problems for example.
Memory is a prerequisite for understanding.
You can't understand something you can't remember.
I think the difference in recall- knowledgeable and logical-model-knowledge will be really interesting. LLMs appear to strongly be the first. But this is very hopeless on mathematics.
>But spaced repetition challenges that, in a sense.
Common sense challenges this honestly. Education systems that traditionally have put a strong focus on repetition, memorization and what you could call neuromuscular training (e.g China, the USSR, France) in particluar in STEM far outperform anyone else. Vietnam outperforms most rich countries.
In programming circles it's a cultural cliche because our profession is full of people who go by: "I am a genius, I work smart, not hard", probably the most damaging idea ever uttered in education, and in the humanities it's seen as culturally unsophisticated.
In reality, 95% of everything is mechanics. Starcraft, math, even literature and acting. Creative freedom is enabled only by a large body of effortless recollection.
The UK and Germany outperform France in average learning outcomes according to Our World in Data:
https://ourworldindata.org/grapher/average-harmonized-learni...
I'm sorry, I didn't read the article but I thought my experience would be a good anecdote.
I've used Anki for multiple years and learned around 18'000 Japanese words. It's difficult to say but I'd say I've learned how to read around 5'000 kanji. When I studied in Japan, my kanji reading—don't mix that up with comprehension!—was way above everyone else's. And most of my classmates were either Korean or Chinese.
That's what 10 minutes of free time—I did that during my daily train rides—can get you! Keep practicing. Being ignorant is the first step towards becoming more knowledgeable.
I've tried to get into anki a bunch of times but never stick with it. It's an on-and-off thing for me that I end up looking into again every few years, which I've gone through about 5 times now. Here's how it usually goes:
* Get interested in memorizing something / multiple things
* Find that the decks available to me are actually not so great
* Get reading online, people say that the real way to benefit from it is to make your own deck (which ups the time commitment significantly)
* Read online about how to get the most out of anki, find out that everyone universally agrees that the default settings are terrible but nobody quite agrees on how to set it for best results
* Try to hit a happy medium, but find that the overhead of 'rating' the difficulty of recall for cards (and how it interacts with the complex settings that I still don't have complete confidence in) adds an incredibly (to me) distracting amount of overhead and never get used to it
* Miss a few days, get overwhelmed with the amount of cards stacked up, don't feel good about my settings (which have implications for what cards show up like, a year + down the line)
* Ultimately fizzle out
I'm probably going to start the cycle over again soon. I really do want it to work out for me. Any tips to avoid this issue? I'm planning to actually pay for some decks this time to see if that gets me to the quality I want, and going to skip the whole 'trying to make my own deck' thing for now
Yeah, ignore the "defaults are terrible" people. Turn on FSRS, if it isn't on by default (I think it is), and forget about it.
I have seen this opinion offered hundreds of times and each and every time I reflect upon the irony that not one of these commenters having trouble navigating the UI, etc to their liking doesn't just ... Make Anki cards about Anki.
If that sounds silly, it shouldn't. I've made flashcards out of all kinds of other programs, from vim to shell shortcuts to Photoshop. Nobody ever expects an interface built for professionals to be something they can just waltz in on and understand perfectly on day 1.
Given what you've said:
* Make your own cards (unless there's an automated workflow [Japanese, sentence mining], really good shared decks, or you're studying for a standardized exam [USMLE])
* Deck Settings (scheduling): Enable FSRS. Press 'Optimize', then press optimize once per month.
* Deck Settings (workload): Wait 2 weeks before gradually increasing new cards per day (if you want to study for longer). Decrease it immediately if you feel you're getting overwhelmed.
* Deck Settings (backlog): Set max reviews/day to 9999
* App Settings: Disable 'Show next review time above answer buttons'
* Addons: https://ankiweb.net/shared/info/876946123 (you seem to have a problem with answer button selection)
* Recommended: Press 'sync', and create an AnkiWeb account. In app settings, set Anki to auto-sync on open/close. This is a free backup.
* Optional: Use a mobile client (AnkiDroid is free on Android, AnkiWeb is free on iOS)
You'll feel like you completed the first day far too quickly, and will want to do more. Avoid overstudying until you build intuition for how it impacts your daily workload.
Use Anki every day
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I made a tool based on this principle!
We spend hours a day browsing the web, so I made a browser extension[0] that translates sentences at your knowledge level into the language you're learning, so that you're always learning a little through immersion.
I also used the same "10 minutes a day on Anki" strategy with my A levels, and it made the revision process so so much nicer because stuff I'd learnt two years ago was as fresh as if I'd learnt it a couple of months ago, rather than years.
[0] https://nuenki.app
Looks not bad but a) billing/prices should imho be prominent and not hidden behind trial or get started. And b) not sure if 5/12/20 per month is not too much? The About section is nice. (I use two other paid language services, thus no need/interest in another)
Fascinating, great app. I wish it automatically adjusted the difficulty based on whether I understood the sentence.
There's a surprising gulf between word recognition and overall sentence comprehension. I'm learning Farsi with a combination of Anki and Youtube videos and sometimes I find myself in the weird state where I recognize every word in a sentence, but yet cannot assemble its overall meaning.
Yeah there’s a few different levels. 1) not knowing the words 2) knowing all the words but not what they mean together 3) not being able to keep up with the speed at which the sentence is spoken…
I completely get what you mean and I had the same trouble. But keep at it, it will click.
Not buying at all that you learned 18000 words and 5000 kanji in ten minutes per day. Thats 60 hours a year for say five year, or 300 hours. Thats leaves you with about 70 words and/or kanji per hour or less than a minute per word/kanji. A rate which far surpasses native speakers.
Anki works, it doesnt need these unrealistic takes.
Whoops, sorry if that was confusing.
Actually, it took me 20 minutes of time per day to do my reviews + new words. I had, on average, 200 cards to go through daily (180 review + 20 new cards).[1] Going through 18'000 words took me around 5 years. 5×365×20=36'500
> A rate which far surpasses native speakers.
Are you comparing me to babies? It took me 2 weekends to learn all kana, but it takes years for a toddler to learn just hiragana. It's not a fair comparison.
> Anki works, it doesnt need these unrealistic takes.
I wonder why you think it's unrealistic. It's not like I'm a genius or anything.[2]
[1] Two cards is one word; one for English -> Japanese, one for Japanese -> English.
[2] Some teachers definitely thought I was a genius because of my memory, but it was all thanks to Anki. And proof is that I was absolutely bad at text comprehension. Anki doesn't make you practice that.
I learned 17.5k words comprised of ~3k kanji in around 2 years at about an hour a day of review time. That's reviews + new cards, not including time immersing in order to find the daily quota of new vocab which itself was 2 to 3 hours of study.
So, by my calculations for just the Anki time alone it's about 17.5k words split across 730 hours, which comes out to about 23 words and hour or one word every 2.5 minutes.
I've seen a pretty wide variety of people do Anki, and I can say there's a distribution in length of time per card for basically the exact same types of cards among people. The slowest people average around 3x slower than the fastest.
That isn't terribly far off. I used Anki throughout my A levels, spending about 250 hours on it in total according to its statistics, and had something like 10k cards that I reviewed 50k times.
Now, those cards weren't alone - they were reinforcing content that I'd learnt in lessons. But if they were doing it for 10 minutes a day a few times a day, it seems quite plausible to me.
Sure, but I didn't read it as 10 minutes a day. The comment says ten minutes of free time. So could be 4 train rides, 10 mins after you finish your sandwich at lunch, 10 mins with your coffee in the morning, etc etc.
> ten minutes per day
...Maybe the poster meant "«10 minutes» per ride"? («That's what 10 minutes of free time - I did that during my daily train rides»)
Pretty OT: A few month ago I tried to marry my simple note system with anki. My goal was to be able to send simple front/backside cards to an api and it would get integrated and I can use it immediately. Ofc, when I edit cards via my notes-backend, the cards in anki should update too.
Long story short: not possible with anki. It took like an entire day for me to realize its just not possible without diving deep into ankis sqlitedb and having the client installed on my server to interact in a horrible way with decks. I wrote my own space repetition [1] backend in a week and never looked back to anki. Ill intergrate FSRS in my software.
1: https://github.com/entropie/ha2itat/tree/main/plugins/entrom...
I looked into this before too. Ankiweb (the place where cards created on Anki sync to) does not provide a rest API. The service is free though. It makes sense they may not want automated clients.
There is an implementation of their sync server, which you can self host. And it has a REST API
https://github.com/dsnopek/anki-sync-server
I think I ran into a blocker with it not supporting something I needed last time I tried to use it though.
If you use Obsidian there's a great plugin which allows me to make flashcards easily within my notes:
https://www.stephenmwangi.com/obsidian-spaced-repetition/
Wouldn't AnkiConnect be good enough here?
https://ankiweb.net/shared/info/2055492159
Anki can import .csv files and if one of the column content is matching an existing item, it will update the contents of the card while keeping the repetition history. Think of it like including a column with unique keys.
I know this is not precisely what you wanted, but yes, Anki can update card contents.
i use the python package genanki to accomplish this. I've found it to be extremely dependable -- just use the first field as a UUID and you're golden (future imports dedupe and auto update imported cards with the same first field)
Every anki card is just a webview. Its very possible to call an api
Then you should be able to link me to some docs.
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Edit: nevermind
Iam not sure what you are trying to tell me. Do you think I didnt use the original anki software? I think I have never heard of "AnkiApp" before.
I haven't seen it mentioned yet with CTRL-f and I haven't used Anki in a while, but has there been work put into modifications in Anki or other programs using spaced repetition along with interleaved practice to also see if that improves studying.
Interleaved practice explainer: https://openlearning.mit.edu/mit-faculty/research-based-lear...
I think it’s important to note that the original SRS algorithms are not for learning. They or for remembering or “not forgetting”.
The system assumes you have already learned the fact (for some unclear to me definition of learned)
Most users inserts new words in the hope that repeating them in anki will help them learn. It does to some extend, but it is not quite the right tool.
So for example, in Japanese, simply remembering how to read a word out loud is a task in and of itself. If you put words in context (which in language learning makes sense) the learner will quickly start to recall the meaning of the word based on the look of a sentence.
For a learning system this open up a lot of issues to solve. The best attempt I’ve seen was a web app that gave you full sentences and you clicked the characters word you didn’t understand and based on that it would give you different sentences.
There are two problems with that website: I don’t remember what it was called and it used google translate from 10 years ago. The second could be improved by expanding the corpus and use LLM to form sentences for the learner.
That tutorial guy on YouTube, Derek Banas, swears by Anki. He's quite the voracious learner as well as being a pretty good contractor. I've used it myself (sparingly, when taking on new projects with new technology stacks), and never really committed to it because of the somewhat static and predictable nature of the learning session (as described in the article; the algorithm). However, from learning about the upgrade (well, 2023 upgrade), I will try it out again: high hopes.
> Thankfully, the leading spaced repetition software, Anki, has incorporated FSRS as its default scheduling algorithm since version 23.10, released in 2023-11
I've used Anki for a long time and apply updates, but I don't closely track changes. Based on the above, I figured I'd be using FSRS, but I'm not. All of my decks have that setting turned off. Fair enough (no silent updates to existing data), but even when I create a new deck, I have to turn the FSRS setting on manually. I found the same even with a whole new profile. What aspect of this is "default"? Is there a global setting I'm missing?
I'm glad it's available, though, without any plugins!
FSRS is not a default yet: https://github.com/ankitects/anki/issues/3616
This was a mistake in the article. Sorry about that, and I've fixed it now!
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I found it a little annoying that SRS is immediately explained to mean Spaced Repetition System, but then the F is added without explaining what it stands for. Most references of the article do neither. Except https://github.com/open-spaced-repetition/fsrs4anki/wiki/The... which says the F means Free. Seems a little too easy? I found nothing else. Chatgpt says it means Flexible, which actually makes more sense? Anybody else can chip in?
What does the 'Free' mean in the name?
The algorithm (FSRS) supports reviewing in advance or delay. It's free for users to decide the time of review. And it will adapt to the user's memory.
Meanwhile, spaced repetition is one essential technology to achieve free learning.
FSRS runs entirely locally and has no risk under others' control.
source: https://github.com/open-spaced-repetition/free-spaced-repeti...
When "FSRS" is first used it's a clickable link, and the first sentence on that link is:
> FSRS (Free Spaced Repetition Scheduler) is a modern spaced repetition algorithm that was developed by Jarrett Ye.
If I do a search of "flexible spaced repetition software" I get no results, which strongly suggests the dumb guesser you're using guessed something plausible to placate its user. This is common behaviour for this type of software.
In summary, I politely suggest you critically review how you interact with knowledge on the internet.
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I was working on a product which has FSRS implemented, and is heavily inspired by anki. The change we made was that rather than rate yourself, you have to type your answer and its graded by an LLM. It also has a button to explain the concept to you as if you are 5 (eli5) and you get feedback on your answer. You can also create the flashcards by uploading a pdf and then generate them from it.
I've stopped working on it and am now building something highly similar aimed towards high school students, but any feedback is welcome. This version was built for uni students
mimair.com - I never got around to adding any payment option so its completely free
> graded by an LLM
This seems impossible to me. In anki, there's "hard", "good", and "easy" which are all for "I got this right".
For my usage, "hard" is "I got it right, but I was only like 60% sure", "good" is "I had to actively think", and "easy" is "effortlessly correct, no real thought required".
There's no way for an AI to tell if my identical input is the result of a 50/50 guess, or a little thought, or effortless recall. "delay to answer" also isn't a good approximation, I have a habit of alt-tabbing and chatting with a friend on random cards of any difficulty.
I find distinguishing those levels of easy for totally identical answers ends up making SRS more effective, and AI just can't know my inner thoughts. Maybe once we have brain implants.
Yes, this is also something I have been thinking about, can an LLM really know how well I know something. There is the issue with the grading with again, hard, good and easy that I can cut myself some slack and say "I knew that" even when I didn't(and I have a strong memory of having done this myself). And there is the possibility of bullshitting the LLM and just all you know about the subject rather than the exact definition of the flashcard. I'm leaning towards any knowledge rather than specifying that the exact answer should be graded. Whats your take?
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One way it could grade you automatically is by the speed of flipping the card (or entering the correct answer). If it took less than a second to confirm then evidently it was easy.
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Rating yourself is an important trait of SRS, it forces you to think how you are doing, what is good enough and what not, what is more or less important, etc.
Me too. I made a specialized Kanji learning app. My different approach is in the cards. I used free dictionary data to create a card for each kanji with all the relevant data in a single card. So a common kanji might have dozens (and even hundreds) of words (each word with 0-2 example sentences) to help you remember.
I like the anki way of self rating, so I kept it. I want to be able to say: “hey, I know I screwed up the stroke order this time, but it won‘t happen again, promise” and hit “Good”.
https://github.com/runarberg/shodoku
https://shodoku.app/
RemNote (https://www.remnote.com/) solves the problems people are mentioning about
1) The time it takes to make cards. RemNote allows you to take Notion-style block notes and quickly turn bullet points into flashcards using symbols. For example, you might be in class and make a bullet point in the format
- The quick brown fox jumps over >> the lazy dog
which you can later review as a flashcard that is automatically separated front/back by the >>.
2) The old and unintuitive UI - again, basically just Notion with flashcards. You can easily view all your notes in a bullet hierarchy and then switch over to SR flashcard practice. Even has rich code blocks, image occlusion, tables etc. A much better implementation of Anki's notes/cards metaphor in my opinion.
I am not sponsored by RemNote, just a university student who has bounced off Anki and really likes the app.
As a longtime Anki user I just want to say THANK YOU! Just downloaded RemNote for the first time and gave it a spin. I’ve been using Anki for years for language learning (Ukrainian and Russian and Arabic), but also for poetry memorization. Weird coincidence: a few days ago I was looking for an AI-powered flashcard creator: I get regular emails from curated sources that have lots of useful information, but I am too lazy to create the cards to remember the points. I just downloaded RemNote and tried the AI-generation feature: fed it an article from UkrainianLessons.com and I was amazed at how it gave me a list of useful flashcards instantly. This is a game changer. The ability to study and create “in context” is also amazing since not all information needs to be a flashcard. The Notion-like/Workflowy/Roam interface also looks like a joy to work with. Really hope this is not a fly-by-night startup, as I am really looking forward to a decade of learning with this thing after a previous decade with Anki.
RemNote founder here - been building RemNote for the past 8 years (4 in private for myself, 4 in public), and we're not going anywhere! SRS is the future.
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What spacing algorithm does RemNote use?
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RemNote is incredible.
I wonder how it compares with the current SuperMemo.
I experimented with SuperMemo around 18 months ago, and it made me fall in love with SRS again. The main reason being the algorithm is less punishing when I skip a day. Maybe it has better defaults?
I once skipped a whole week and could get back on track in the next week, in Anki that feels unbearable.
Another thing I really liked about it is that you can edit a card as you are studying without having to open a separate window, helps me stay in the flow when studying.
But… With a better algorithm I might give it a try in the future… Being FOSS is the real advantage here.
Currently under debate. FSRS is likely better than SM-17. No data on SM-18
Q&A/discussion: https://supermemopedia.com/wiki/SuperMemo_dethroned_by_FSRS
Repo: https://github.com/open-spaced-repetition/fsrs-vs-sm17
Discussion: https://discord.gg/qjzcRTx => https://discord.com/channels/368267295601983490/136895216717...
Am I reading this right, did users go through >10k repetitions on average?
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I really wish there was a FOSS equivalent to SuperMemo. Spaced Repetition is cool and all, but Incremental Reading that uses principles similar to SRS to augment learning novel content and then retain pieces of it through more standard spaced repetition is really next level.
A while back I built https://readboost.io/ but so far never advertised for it. The idea: Embed Q&A into your ePubs and optionally download Anki cards for your book. Probably gets buried here, but maybe someone finds some value in it.
They have gotten better and I think it's clear they'll continue to get better :). FSRS is already good (I use it both in Anki and for periplus.app), but looking at the benchmarks [1] there's a lot of room left for improvement.
One direction could be to incorporate semantics, which afair FSRS doesn't do at all yet. A good flashcard deck will have a lot of semantic overlap, e.g., a card for the vocab word itself, that word in a sentence, etc. Struggling with one component is a strong signal you'll struggle with another.
The same thing could be done for just better spacing, so you don't "cheat" by having too closely-related cards next to eachother in a review (the review signal will be less noisy).
[1] https://github.com/open-spaced-repetition/srs-benchmark
Yes, we can improve FSRS in that way. But it requires to collect a lot of review data with cards' content, which breaks Anki's privacy policy. And FSRS is my side project which has squeezed all my free time... I'm not very motivated to improve it now.
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systemS? There is only one program out there that is viable: AnkiDroid.
Anki runs on desktop: you have to be chained to a desk rather than taking advantage of idle moments when you are on-the-go. Even if you have it on a laptop, you still need a place to sit; SRS on mobile can be used anywhere, like standing-room-only public transit.
The AnkiMobile companion app for iOS is a paid app that is somehow chained to the desktop version, whereas AnkiDroid is a full-featured clone of Anki that you could use air gapped without ever syncing anything to or from another device. It has integrated management of decks and note creation/editing.
Every other SRS app out there is just playing very distant catch-up to Anki/AnkiDroid. They usually mention Anki in their pitch, trying desperately to explain why some very minor and very subjective negative point about Anki is worth switching to their massively inconvenient solution.
Do any of these algorithms use vector embeddings to determine the semantic similarity between cards? Seems like that might be a useful parameter for tuning the algorithm, since you’re likely to forget something similar on a topic you’ve forgotten things about.
That was actually my very first python project, I made this to go through medical school: https://github.com/thiswillbeyourgithub/AnnA_Anki_neuronal_A...
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I probably need to go read the studies but of SRS is so great, why aren't all schools just SRS farms (or are they?)
Especially for language study, as a friend put it, speaking a language is like learning a musical instrument, no amount of book studying will teach you how to play the instrument. The way you learn to play is to play. And similarly, the way you learn to speak is to speak. Sure, you can fill your vocabulary, but I question a little how much it helps in context. Obviously it's not zero. I'm sure curious, if there are better methods than SRS for language learning given that hearing, creating, understanding, and speaking whole sentences is the goal, not individual words. I can generally learn a new word in my native language with one exposure, no SRS needed.
This is why they added more and more exams into class. Basically, a test for content from the last class is a type of SRS.
I'm building a language app based on using LLMs and spaced-repetition.
We generate cards that respond to speech to evaluate card recall and pronounciation (via speech recognition). We don't market it as AI but behind the scenes we use LLMs to explain the context behind every word and phrase, offer additional usage examples and cultural notes, and also generate roleplays based on specific topics & scenarios.
Happy to pass along invite codes to anybody who wants to check it out. https://getdangerous.app
Are there any algorithms/plugins that are optimized for an on-/off-review style (ie, potentially months-long gaps between sessions)? I know that the ideal would be to do reviews every day, but I'm doing this for pleasure and I'd rather tweak the algorithm to what works for me than the other way round.
I made this a long time ago, it uses embeddings to prioritize diversity: https://github.com/thiswillbeyourgithub/AnnA_Anki_neuronal_A...
I'm not ready to share a link to my actual implementation yet, but I've been working on an SRS system for Chinese and been using it as my daily driver for about 3-4 years now, after previously using Anki and getting frustrated with how reviews pile up after a couple of days off.
I've done lots of tweaking to the algorithm over the years to make it feel like I'm less surprised by the scheduling, and less like a slave to it. One very stark difference between mine and Anki is that I have a large number of "overdue" cards, but the system still prioritises when to show me the overdue cards with quite a few different metrics based on how overdue it is, how new it is, how long the current interval is, etc. So, like Anki, I still just double the interval for correct cards, but for incorrect cards, the reviews are repeated same day until they're correct, and then the interval is reduced a lot more than Anki. So, the cards then become overdue sooner, but because the scheduling of overdue cards is better, they get pushed later if your overdue queue is too large, and sooner if you've not got anything more useful to review.
FWIW, my typical session is 40 minutes per day during my daily lunchtime walk, and I'll get through about 150 cards in that time. If I'm on a long train journey, I'll often clear out double that or more, but the disaster situation of being on holiday for a month might leave the queue with a couple of thousand extra cards, but they never seem unmanageable. Even after a 2 month break when I was travelling last year, and only doing reviews on flights and trains, I'd definitely forgotten some words from not reviewing at the appropriate time, but the percentage of totally forgotten cards felt better than I used to experience after just missing a few days with Anki.
One thing the article mentions that I don't massively concern myself with is desired retention. I'm not sure I'd want to express it as a target percentage, but I've definitely been thinking about how I want to change things to deprioritise stubborn words without just suspending them or deleting them. I definitely find that having them keep showing up, so I might see a pattern of them wrong twice each day before finally getting them right, after a few days of that they do usually suddenly stick for good. But sometimes I look at the word and think I don't really care if I remember it or not.
Does anyone have tips for how to use space repetition to be a better knowledge worker? I feel like i could use it to have a better memory of business processes, but i dont know how to get started.
I gave up on spaced repetition systems, even my paid memrise subscription, because I couldn't find good flashcard sets. To create good flashcards, you need some domain knowledge. An AI can pick facts from wikipedia and quiz you on them, but it takes a real human to identify what knowledge is relevant and worth learning.
I would pay for an e-ink tablet dedicated to notes and spaced repetition. (I know there are e-ink note taking tablets, but none of them have spaced repetition.)
I'd like to be able to take freehand notes, and then be able to block out, or blur, certain sections and each blocked or blurred area becomes a spaced repetition entry.
Or, in more detail. I'd like to look at a page of notes and loop select a certain area. That selected area becomes a spaced repetition item. After the initial loop selection I can do another loop selection to blur one or more areas that would be blurred. Etc, etc.
There's a number of happy Onyx Boox users using AnkiDroid.
You can probably do what you want with the in-built image occlusion feature. Might be worth downloading an Android emulator and seeing if we meet your workflow requirements.
I find with spaced repetition that it works really well for some well-known things like vocabulary (EDIT: well-known meant as "spaced repetition is well-known to work for this use-case, not well-known as "the subject is well understood"), medical etc. but for everything else it becomes a struggle for a long time.
I have been trying for years to fined a way to use it for mathematics and physics - with the former being more of a focus and didn't really get anywhere. For definitions it works, but it's quite hard to write proofs in a way where there is a short obvious memorization based answer. Either you spend far too much time on a card or the card gives you too much information so you don't really test the knowledge.
I also tried it for computer shortcuts - it seems to me that they are really useful only when part of the muscle memory - so practicing them works better then memorization.
Math Academy provided a self-service learning system with a novel spaced repetition algorithm which could take the hierarchical body of math into account.
It's someone I wondered, what is the point of memorizing a proof if it only ever proves something you already know. The answer is you hope it generalises. There is a possible way you can do it in SRS, being inspired by RL training. Instead of cards you'd show options within a game or simulation. But this would need a lot of expert knowledge for a single concept.
Sure, but if you are memorizing the proof instead of understanding it, you aren't going to be able to generalize it.
In general, math is not a subject where memorization is going to get you ahead. The "why" matters much more than the "what".
i've learned entire math topics calc 1, calc2, calc3, statistics, linear algebra with anki. It's really easy. Just add the parctice problems at the end of the chapter to the front and the answer on the back.
Yeah you're basically just using the algorithm to schedule review, just like going through old problem sets.
It's the next best thing to getting an infinite stream of new problems of a type of problem.
> it works really well for some well-known things like vocabulary
And mathematics and physics, which are (at undergraduate level) even more well-understood than vocabulary.
I feel like its asking a lot to use flash cards to learn things that aren't about memorization.
Hmm, I have Anki and I don't see an option for this algorithm. Anyone know how to enable it? The preferences say I'm on the "V3 scheduler" but have no option for an algorithm. I don't think I'm on the algorithm described in the blog post because whenever I don't know a card it goes back to 1 day as if it was new. Or maybe I am on it and I'm just misunderstanding how this works? I'm on Mac, Version 2.1.66 (70506aeb).
Go into the deck preset options (any deck is fine). Look for the FSRS section and check if the toggle is enabled. If it's not there you probably are on an old version.
https://docs.ankiweb.net/deck-options.html#fsrs
You're on an old version of Anki.
Once you upgrade, FSRS is available under the deck options.
I have been using Supermemo daily (except for when I miss a day or two, vacations with no desktop, etc) since about 2010. I have found the newer algos to be pretty good. I have not had any bugs or a messed up collection. Its one of the pieces of software that is keeping me on Windows. There is still no foss replacement for incremental reading/writing [1]. Also, Supermemo has two modes that lets you skip a few days without being overloaded [2][3]. So you don't go from 20-30 cards to 200 if you skip a day.
That being said, its just another tool in the toolkit for learning stuff. I don't think I'm that much smarter or better at anything just because I have used Supermemo often for awhile. Honestly, I just like making cards and throwing articles I want to read later into Supermemo for processing. Most of what I use Supermemo for is incremental reading, which I have never been able to find a good replacement for. I like being reminded of cool stuff I have read and ideas that I have had. I would recommend also learning and practicing various mnemonic techniques alongside spaced repetition.
Most of the other algos/apps I have tried have been okay, I have not tried FSRS because I don't really use Anki anymore. I used Anki when I was in college for about 2-3 years because I would do flashcards using the mobile app. I was still using Supermemo daily during the same time period though.
I also use Clozemaster for language vocab with Supermemo. I put the sentences and some explanations into Supermemo after I do them in Clozemaster. I do not really consider myself to be a language learner or learning a language. I pick up new vocab very slowly and do not do anything else to practice the languages I am learning vocab from. I have also been using Math Academy almost daily for about seven months which is nice, but definitely not a full replacement for learning math. Using Math Academy actually made me start working with math textbooks and online resources again.
[1] https://www.help.supermemo.org/wiki/Incremental_reading [2] https://www.help.supermemo.org/wiki/Postpone [3] https://www.help.supermemo.org/wiki/Mercy
I’m sure the algorithm can play a huge role in the effectiveness of learning but for me the difficult part was always creating the cards and actually opening the app to practice.
I've built Komihåg [1] to try and combat this: Select any text on your iOS device and a flashcard is automatically created for you, and the app is then showing you the cards on the Home Screen / Lock Screen / Apple Watch Face.
I haven't gotten to implement any sophisticated scheduling algorithm yet but will definitely do that eventually.
[1] : https://komihag.com
Cool idea. I’ll check it out. It would be cool to do something like this for single word highlights on an e reader. If I have highlighted a singe word it is because I want to add it to my vocabulary.
I was looking to use this with the iOS Books app, but I can’t share text to your app from there (but something like safari works). Any idea why?
I found this: https://developer.apple.com/forums/thread/762784
Looks like share extensions are not generally available inside the Books app, which is why my app is not showing up.
Thank you for making me aware of the issue!
Language vocab seems a good use case. What other things are people here using spaced repition for?
A few uses for me:
• Memorizing Geoguessr metas. Made it to Master I rank this way.
• Memorizing new words. When I come across a word I don't know, I make a new flashcard for it.
• Memorizing things about people. My wife's favorite ice cream flavors, which spices each of my children dislikes, etc.
Anything I want to memorize but wouldn't be exposed to frequently enough in my day to day life. Flashcard review takes only a few minutes each day.
I'm using it to memorize all of the Paris métro stops and study for the French drivers license test. It was also a huge boon when I prepared for my citizenship interview.
I tried it for a while with my eldest child (then aged 3) to help her remember numbers, letters, etc. She didn't find it very fun past the first couple of times, so I figured I wasn't going to hoist it on her.
My "Daily Life" deck is pretty small. But I fill it with things whenever I try to recall something and am embarrassed to not know it. Now I know them!
- Population of Tokyo / Tokyo metro area / Japan (where I live)
- Japan emergency numbers (like 911/411 in the US)
- kg <-> lb and km <-> mi conversion ratios
- My Japanese phone number (and my wife's)
- Number of neurons / synapses in a typical human brain
- Number of parameters in SOTA language models
- How many people work in my office
- Last 4 digits of a couple important credit cards, so I can identify them when UIs present me a choice of pre-saved CCs.
Anything you wanna the retain the knowledge of. Basic usage is remebering shortcuts, names of people, apis, you name it. More advanced usage is you can break down complex concepts into atomic cards, which helps you remember how things work.
I used it to get my Amateur Radio license, since a superset of the questions that can be in the test are public.
I downloaded an existing deck and modified it so that only the correct answer is shown instead of multiple choices.
I still can remember some of the content even though I deleted the deck short after receiving my license.
HamStudy.org is exactly this, an SRS site/app that already has the questions and some explanations to go with it (the site is free, but they also have an app which is a couple bucks and almost the same but in my opinion slightly better). I used that a couple months ago I studied for the technician class license and got a perfect score when I took the test. Then I studied the general class license and got one wrong (34 out of 35 = 97%. You only need 26/35 = 74% to pass.) I could probably go for the third one next but maybe it would be more useful if I actually go get a radio and start using it first.
I used it whenever i studied anything, but with a 'recursive' twist.
Every time i did repetition, i've made a shorter note about the subject.
Then next repetition cycle, i'm reading the note, and making shorter note based on it. and so on.
once few cycles i'm re-reading the main starting note i made.
For language learning I find that using longer phrase fragments is better than single words.
If the phrases are found by yourself in context from your own exposure to the language, it is even better.
I got introduced to this idea a few years ago from AJATT [1] and my personal experience is that it works very well.
[1] https://web.archive.org/web/20100406173634/http://www.alljap...
The advice with gendered languages is to always learn the word alongside some context that includes its gender, e.g. "Der Tisch" (The masculine table) rather than merely "Tisch->Table".
It's surprising how much easier to translate a foreign when it's given in a sentence. Also helps when there are multiple translations for a word depending on context.
Everything, I use it to memorize anything that doesn't stick the first time.
I just don't use an app. I will challenge myself to remember things or practice things manually.
It's probably sub optimal compared to structured spaced repetition, but it works well enough for me.
Used to use it in university (CS) for cramming before tests, mostly when there were lots of definitions to memorize. Also summarizing stuff and writing your own cards for it helps already with learning itself.
I’ve been meaning to build a unix shell deck for a while. There are so many tools that are so powerful but I just don’t use them regularly enough to remember how they work when I need them.
Mine has all sorts of shit in it. Mac keyboard shortcuts. Nautical terms. Cyrillic characters. Credit card verification codes. Phone numbers. Airport codes. Ionic component names. Names of my friends’ kids. A surprising amount of Z Specification. Anything I think it would be useful to remember.
How do you manage the data? Multiple decks or just one with everything? Do you directly use the app to add new phrases, or do you have some sort of automation / tooling on your phone or laptop?
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I used it all throughout my legal studies, for remembering legal terms, concepts, tests and any other thing I had to learn. It served me very nicely.
There's an anki deck built from the jeopardy archive with 400,000 questions, so I'm studying trivia that way. I enjoy trivia.
I think I've used that deck for a few weeks. Mind sharing the link so I may take a look at it? :)
I would love to get my hands on this, please share if you can :)
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Used it to memorize the 16 times table in decimal and hexadecimal.
I use it to practice Leetcode problems
For anyone looking to read more about spaced repetition, Gwern's Spaced Repetition for Efficient Learning is worth checking out.
https://gwern.net/spaced-repetition
This is something I’ve been tackling myself in the language app I’m making https://store.steampowered.com/app/3220820/Bilingual_Crosswo.... Right now, I’ve added a set of front loaded intervals: 2M, 5M, 10M, 20M, 40M, 2H, 6H, 1D, 2D, 4D, 8D, and so on eventually stretching to a full year.
I’ve always felt this setup was a bit arbitrary and considered it a temporary solution. Thanks for saving me some time on research!
Take a look at https://github.com/open-spaced-repetition/
As a quick hack, increase the factor to 2.5 once you reach 1 day. That's what Anki's SM-2 used to use (if only pressing 'good')
This looks like a fun app!
Interesting. I was never really happy with any spaced repetition algorithm, so I recently implemented my own dumb system which simply asks you for the number of days after which the card shall be shown again: https://github.com/kldtz/vmn
Usually my intuition about how well I know something is not too far off. If you don't specify anything, it doubles the time since the last review.
I had a similar problem where I can't remember the answer to the card, but after revealing it, it seemed too easy to make it due in a few days, so I would lie to the program and press Hard/Good. Later I removed scheduling times on top of buttons and decided to trust the algorithm. I believe it helped me to stop caring about schedule times and loosing progress on a certain card. After all, these algorithms were made for ordinary people with ordinary memory behavior.
I think my problem is that I'm not using the system as intended. I learn new vocabulary mainly by reading texts or watching videos in the target language and use spaced repetition to keep track of my progress. If I can't remember a word (as indicated by SR), I'll reread the text/rewatch the video where I've first encountered it. I don't want to keep reviewing the same word in my spaced repetition program, especially not in the same session.
What’s a good way to learn to understand concepts in a spaced-repetition way? I’ve used anki before for remembering facts or answers to specific questions, but is there a standard way to setup spaced repetition flashcards to learn, for example, when to apply a certain software pattern or something?
I’m solo-building a free Anki alternative using the Ruby FSRS gem: http://cadence.cards/welcome
Would love any feedback—I’m aiming for a more focused, restful take on what I like most about Anki. Styling is done with Tailwind.
One could train a language model to predict task difficulty (and other parameters) here, which would be great for the initialisation of new cards
The folks at SaySomethingIn, that originally started with Welsh and other Celtic languages, have recently expanded to Japanese. I haven’t tried it myself, but I’ve found some decent success with one of their other courses. It’s all about spaced repetition and focuses exclusively on listening and speaking.
https://www.saysomethingin.com/en/
I like WaniKani because it forces me to type the right answer. When I tried Anki, it was too easy for me to "cheat" and press space for something I "kinda" remembered.
I do agree with the author's phrase of "...a daily ritual of feeling bad about what you’ve forgotten..." though, and would like to try the new algorithm. Is there a way to configure Anki to force you to type the correct answer?
You can set up Anki to force you to type answers; use Basic (type in the answer) when creating cards.
20 second video: https://www.youtube.com/watch?v=mxEqRe1Pp1w
It's possible to batch convert your cards to this format using Anki's "Card Templates" feature.
https://docs.ankiweb.net/templates/fields.html#checking-your...
I do think that Wanikani and Bunpro are kind of in a catch-22 on this compared to Anki. They've built their gamification features and UI on the idea that cards have specific buckets that they're in and something like FSRS is a lot more varied than that. Especially Wanikani, which has a system of unlocking more items based on your current items reaching a specific stage.
So I haven't integrated FSRS, and of these two, I've only used Wanikani, and have been playing with a reimplemention for Chinese hanzi: https://hanzi.bpev.me
But seeing how it's implemented, I think they could totally integrate something like FSRS to at least just replace their scheduling (how long until an item is next shown). The unlocking system can be implemented as a separate gatekeeping mechanism, and the buckets can be coded for certain step thresholds (instead of wanikani's "stage").
Basically, this is their entire srs system: https://docs.api.wanikani.com/20170710/#spaced-repetition-sy...
I dream of building a WaniKani competitor that uses FSRS. Unfortunately it's one of those projects where 10% of the work is building, and 90% of the work is marketing/community building/evangelism. (And the 10% is not trivial work either!)
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Super insightful. FSRS sounds like the upgrade I didn’t know I needed for my Anki habit!
Super nice, thank you for this post! Based on this I've updated the vocabulary learning scheduling in DuoBook (https://duobook.co) to FSRS based. We should be up to date with the science based learning :)
Just added FSRS to my free mac flashcard app. If interested, check it out https://apps.apple.com/us/app/flashcard-max/id1430950704
Why does everybody want to learn Japanese? What makes Japanese so enticing? Why not Mandarin or at lead Spanish?
Japanese media is quite popular, and many fans want to watch/read their favourite thing in its original language. This is probably the reason most people learn a language, and a huge reason why so many kids around the world speak English. Chinese culture doesn't have the same impact, yet. As to Spanish, most kids who want to learn Spanish can do so at school so there is no need to go above and beyond to learn Spanish on your own.
> Chinese culture doesn't have the same impact, yet.
At this rate if 2/3rds of their popular media(manhua, games, animation) continues being cultivation fantasy featuring the exact same power system, tropes, character archetypes, often even setting(murim) and content, it never will.
Animanga were always poised to make it big, because for all their shortcomings, they have interesting, exotic(to us) themes/tropes/vibes, and go really hard on hyping scenes up.
You learn Japanese for the media and culture; Mandarin for the financial opportunities; Russian for the reverse-engineering community; Spanish, French or Arabic to be able to speak with large diverse groups of people, typically for travel; Klingon, Na'vi, Esperanto or Elvish to fit in certain communities
Accordingly, the stereotypical CS major is attracted to Japanese and Klingon, the stereotypical Business major to Chinese. Even though few follow through because of the amount of work and perseverance required
For me, it's about the media. I'm interested in Japanese anime and manga, and now light novels.
I'm not at all interested in anything I've seen in other non-English languages, except possibly Korean now, since they seem to be producing a lot of stuff.
However, almost everything that I'd enjoy gets translated to English for both Japanese and Korean now, so there's a lot less incentive to learn them.
I'd say it's confirmation bias. In my personal circle, not a lot of people are interested in the Japanese language, but I know a few who took at least a few lessons on Mandarin or Spanish.
I've learned Japanese and part of the reason is that I thought kanji were attractive. I remember watching anime on TV when I was a kid and seeing the opening credits with Japanese characters looked soo cool.
When I was a kid, most of the foreign culture I was exposed from came from the US, and then Japan followed with a small amount.
No wonder my second language was English and third language Japanese.
Never heard a single word of Mandarin in any media I was exposed to. I can understand Spanish very well but I do not count it as a learned language as it is too close to Portuguese (my first language).
I live in Japan.
Online everyone learns Japanese, in real life i have never encountered anyone learning it, while i know multiple people learning French.
1. Generally people using such systems to learn language only need to do so if they aren't immersed in the country where it is being spoken. I stopped using Anki for German after a while of living here, even though I'm still learning. Therefore, most language learners are doing so not because they want to live in the country but because they want to consume media written in that language
2. Japanese is becoming one of the most popular languages for foreign media, probably even surpassing English at this point. Anime is really huge now, particularly in the US. It has shifted from being a nerd thing to being of interest for the "cool kids" (if there is even such a thing now). Japan also had a huge and very interesting media industry in the 80s and 90s including some very novel video game concepts, most of which has not been translated
Ego.
Chinese evil. Communist. Bad. Bad Chinese. Bad bad. Cheap products.
Japanese. exotic. mystical. Samurai. Ninja. Anime. Good. Sony. Good. Good cars. Zen. Good.
Me good. Me learn Japanese. Me exotic and mystical. Super power. Me good. Me smart. Me learned Japanse. Me great.
Me me me. Me me me. Me me me.
The author bashes other algorithms for being "arbitrary", but I don't see how FSRS is any less arbitrary.
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I just loaded Hacker News after a WaniKani session.
Any recs for moving this into Anki? I already use Anki for cards I created while going through Genki with my tutor, and world capitals.
I just let chatgpt quiz me anki style on topics I'm learning
ChatGPT isn't a spaced repetition system, so... it's missing the fundamental aspect that makes it "Anki style". This comment doesn't make sense.
As I understand, anki's use of spaced repetition comes from how it presents you cards in increasing or decreasing frequency based on how you have answered it previously. In this way, I prompt chatgpt to ask me questions, and it revisits previous questions or topics for me based on how I've answered previously. I continue the same conversation periodically prompting it for questions to ask me.
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How are people using Anki for maths? Any nice decks you could share?
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how to ace any uni theory course
> download all pdfs
> merge pdfs into one
> compress
> write a very specific prompt for gemini to turn these into anki cards separated by a semicolon
> do 50 anki cards a day for 3/4 weeks before exam
not a single lecture attended top of my class (ku leuven). feels like cheating honestly
You are so right. I just began doing this today for my exams, and it really feels like cheating with how easy it is. That, and also creating a podcast with NotebookLM with all the pdfs as source and using as a prompt "Make this a long summary for studying".
Has anyone tried to use an LLM to test questions / concepts in a broader way via spaced repetition instead of just memorization? Just wondering.
Point of feedback: I know it says it in the link, but it would be nice if an article almost entirely about FSRS actually spelled out what it stood for even once in the body of the article.
(Free Spaced Repetition Scheduler, in case anyone was wondering)
This should be a first class feature in iOS. Hey Siri teach me what elide means.
What's the go-to SRS app now (I'm still on Anki)
I wish there was some SRS-like tool but for learning music.
Makes sense. But is it same as “by heart”? If not, what is the difference?
Anki is a good piece of software. But I couldn't come up with a worse scheduling algorithm if I tried (old and new one). It's like "here's the thing you just added one second ago. Here it's again immediately after. Ok you got it, you'll see it once again in a month or so lol".
It makes it unusable and every time I tried I went back to my own self written program that just lets me set/adjust the intervals myself.
When was the last time you tried? Anki used a static algorithm (SuperMemo 2) before the new FSRS - which is dramatically different.
In the short term (first day), I think it's still better to set your own intervals (typicall 1 minute, then 5, then 10). But after that, the algorithm optimizes for reminding you just before forgetting. Highly recommend giving it a try.
I try Anki every couple of years because it has an app and can sync. I also tried fsrs and rage quitted after a few tests. These people can get high and mighty on their algos and research. If they'd just add a manual interval mode they'd contribute a lot more to humanity.
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What is everyone using spaced repetition to memorize?
The current version of the supermemo algorithm is SM-18. The author thinks SRS has gotten way better since the author was previously using an out of date version of the algorithm, SM-2.
SM-17 is linked from the benchmark repo: https://github.com/open-spaced-repetition/fsrs-vs-sm17, though I get the impression those numbers come with a dash of subjectivity. It seems fair to compare to older versions of the algorithm though because SM-17 is only used in the SuperMemo software (and Anki) and isn't widespread.
Note that SM-17 is only used in proprietary SuperMemo software. Anki was stuck on SM-2, the latest version that was open.
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I'd love to have a system that shows me what I already know well as rarely as possible, because that's the most frustrating part.
SM-2 is very easy to implement and is still an effective memorization tool.
A lot of the difference in that graph seems to come from 70% vs. 90% retention.
> If we step back, we realize that this scheduling system (called “SuperMemo-2”) is pretty arbitrary. Where does the rule of 1, 6, 2.5times correct + 1, reset back on failure come from? It turns out it was developed by a college student in 1987 based on his personal experiments. Can’t we do better?
Note that Anki uses (used) such an old algorithm because it derived it from an ancient open source version of SuperMemo, a software which started the spaced repetition trend. Anki just added a usable GUI instead of the convoluted mess that is SuperMemo. Newer versions of SuperMemo improved the algorithm, but they are no longer open source. I wonder how FSRS compares to current iterations of the SuperMemo algorithm.
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language learning is 100% memorization. eventually your brain memorizes all the phrases that click into “situation-space,” for every possible situation there is a memorized response. language can be broken down into situational meta-phonemes. using flash cards and grammar is just a way to bootstrap yourself into memorizing all the appropriate responses for any given kind of situation.
Hi Duolingo.
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LLMs should only be used where hallucinations can be tolerated (either low stakes, like a video game; or where competent human review exists). What you describe is neither of these scenarios. You may be trying to memorize something that's not low stakes (and if it's low stakes why bother memorizing? Just make it up as you go), and if you're using study tools you're probably not (yet) competent enough to check for mistakes.
Yeah, my immediate thought when reading this was that it's great they've replaced a formula with a better formula, but couldn't it be replaced by something smart? An LLM could in theory be content-aware, taking into account that this card reinforces these associations, which makes this other card easier to recall but this third card harder to recall. And it may even be able to say, this card is related to a more central concept, it should get priority because that will help in the longer run.
In the long run, the appeal of machine learning to me is that we can move up the stack of what we optimize for, so instead of targeting a proxy metric, say a certain recall ratio, we might actually be able to target directly the thing we care about, say ability to use these things in practice. Moving upwards in the teleological hierarchy.
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Repeatedly memorizing the same thing over and again does not make one smart.
Ofocurse it does help you win stupid games.
Like scoring good marks in exams.
So that you can spend the next 30 years of your life doing jobs you hate for money to just end up dead for infinity.
You're free to choose not to memorise things, but please don't be an arsehole about people who do want to do so for whatever reason. Having said that, you seem to misunderstand the point of spaced repetition, which is that you don't memorise the same thing over and over again; instead, you memorise it enough times to learn it, and not many more.
When was I being an asshole. Your ego took whatever I said personally.
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