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Comment by zozbot234 | Hacker News Reader

> Furthermore, if you skip a single day, you have twice as much the next day; and if life happens and you end up missing a week or a month, you come back with a giant jumble of cards, half of which you've forgotten, and it's really difficult to dig your way out of it.

The Anki system is actually really good at dealing with missed days. You end up recalling most of the cards that you skipped review for, and the system gives you extra credit for the increased interval before review, in that subsequent repeats for the same card will be spaced out even further. Cards that you outright fail to recall due to the missed reviews are a problem, but the best way to 'dig your way out' of that hole is to keep reviewing on a regular schedule and not to overwork or cram. The backlog gets cleared rather quickly.

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Sure, a single missed day isn't bad; but have you ever skipped a month?

I'd been using Anki for Mandarin flash cards for a couple of years, and decided I wanted to memorize the "outs" (probabilities) of various hands for Texas Hold 'Em Poker. So I made a separate Anki deck and used it for a few months. Then I got busy, and stopped studying the poker deck (while maintaining the Mandarin deck). When I tried to pick it up again, it was just impossible -- I'd forgotten so much, and the card list was so long, that if I said "I forgot this", it would be scheduled for the next day, but because it was behind 100 other cards, I wouldn't actually be shown it for a week or two. The system was just completely broken.

Contrast that to the system of my own that I developed, based on the "study value" (effect of studying now on the difficulty) rather than fixed timeouts. After working on and using my own system for about 4 years, I got a bit tired of it (and I was also in the middle of redesigning the database from the ground up), and so decided to give Duolingo a go for a bit, just to see what it was like. Six months later, I came back to my own system, and it was great -- just slowly eased me back into the vocab I had before. The same is true after missing a day, or a week: it's always welcoming to get back into, rather than terrifying to get behind.

> The system was just completely broken.

It's not broken, it's just doing its best to cope with your situation. Missing lots of days means that there will be lots of cards where it's just not clear if you're going to recall them or not. Figuring that out becomes the priority, then the system is effectively back to normal - possibly with some missed cards that will have to be learned again. I'm not sure how one could do better than that.

The comment you replied to described an edge case and explained why it's broken in that particular case. You haven't actually responded to the example provided.

> it's just not clear if you're going to recall them or not. Figuring that out becomes the priority

Presumably the priority ought to be (re)starting with a small subset of cards and gradually trickling the others back in. The algorithm needs to account for time spent by the given individual and adapt to changes in that over time.

I haven't used Anki for about a decade so I'm not familiar with the current state of things. At the time a major factor in my dropping it was that I found the algorithm to be more of a hindrance than a help.

It's not at all clear that "restarting with a small subset of cards" is better. It means that you're very likely to fail to recall almost every card outside the small subset, which increases the work you must do to memorize the deck again. Any card that you verify immediately is going to save you a lot of work down the line.

> It's not at all clear that "restarting with a small subset of cards" is better.

Sure it is. It could grow as quickly as allowed for given the time invested by the user. That could mean a return to the full subset within the span of a single day, or it could mean many months. Perhaps even never. It all depends on time invested by the user going forward. Starving regular review for the sake of verification is an example of an algorithm failing when faced with the real world.

At minimum it is clear from what was said that (better) prioritization between conflicting goals is needed. That somewhat matches my own experience with it from years ago. The algorithm was simply not flexible enough to fit my own usage patterns. In other words I was not part of the target audience, which I found frustrating because I very easily could have been.

Keep in mind that any unverified cards have been "starved of regular review" for longer than any of the cards that have been shown at least once already. It makes sense to prioritize them, at least once they've become "due" for review. The fact that some users might find this unfamiliar or even confusing (because it only happens after you've taken a break and then resumed using Anki, so quite rarely) doesn't make it broken.

> Missing lots of days means that there will be lots of cards where it's just not clear if you're going to recall them or not. ...I'm not sure how one could do better than that.

It's not clear to Anki because its model ("due" or "not due") and algorithm ("study the card that's been due the longest") are too simplistic. I know it can be done better because I built a system that does better with the same data by having a better model ("expected difficulty") with a better algorithm ("study the card which will have the highest long-term impact on difficulty").

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