Show HN: Never forget what you've learned | Hacker News Reader

Show HN: Never forget what you've learned

saveall.ai

12 pointsp-christ9 comments

Save All uses quizzes, notifications, and emails to stop you forgetting what you've learned. Unlike other spaced repetition apps, we've (really) prioritised making Save All as simple as possible - minimalist design, no distractions, and minimal cognitive load placed on users.

We achieve this simplicity by using machine learning (e.g. large language models like BERT, GPT) to reduce the number of decisions users have to make. You don't have to decide whether you remembered a card, we know whether you did. You don't have to decide how to be quizzed on your information, we'll decide for you.

We're VC funded & growing fast but would love to hear HN's critical feedback. Tell it to us how it is!

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Love to see new innovation in this area. I took the app for a spin, pasting in a passage I came across recently:

> In 1996, when Dolly the sheep was cloned from a single adult sheep cell, the world looked on in amazement. For some scientists, however, the most amazing thing about Dolly was the cell from which she had been cloned.

It appears that Save All cloze'd out 1996, but also "when Dolly the". This kind of unexpected behavior is familiar to me as my buddy and I built a similar NLP-based auto-cloze tool which gets tripped up trying to find important pieces of info to cloze out. In general, I'd say that clozing out dates is actually pretty low-value; personally, I (manually) clozed out these words in the passage:

> In 1996, when {{c1::Dolly}} the {{c2::sheep}} was {{c4::cloned}} from a single adult {{c2::sheep}} {{c3::cell}}, the world looked on in amazement. For some scientists, however, the most amazing thing about {{c1::Dolly}} was the {{c3::cell}} from which she had been {{c4::cloned}}.

Wishing you guys best of luck. When someone finally cracks this problem (generic content => nice flashcards), it's going to be huge.

thanks for trying it out! Completely agree that generic content ==> nice flashcards is going to be big, we really think it's possible now with advances in NLP and we are going to do it.

And yeah the green words aren't very good for that Dolly example. It's ML based so its output is somewhat random but usually it produces green words that are much better than that so i think you were a bit unlucky with that example. All the data we collect on the clozes gets fed back into the algorithm so overtime it should become more consistent aswell!

So Anki but 1 ) it's shinier and newer, and 2) you use ML to turn cloze deletion cards into multiple choice cards?

Seems interesting, although Anki is still free and incredible.

Would be helpful if you had some discussion of the spacing algorithm you use.

I'm also curious whether the multiple-choice-ifying actually improves recall or not?

fill-in-the-blank vs. multiple choice

free recall vs. recognition

harder vs. easier

Multiple choice is definitely problematic in some cases. For example, if you were say, learning chinese, certain chinese characters look very similar. If they happen to be next to each other in multiple choice, you'll probably get confused. Imo it's better to learn and think of them in isolation (perhaps even learning them months apart to reduce the chance of them getting jumbled up in your mind).

thanks for trying it out!

We use a similar spacing algorithm to Anki at the moment but eventually we will use a custom spacing algorithm per person & per card that uses machine learning to learn the optimum spacing algorithm per person & per card

Multiple choice questions are the least effective for memory but they help to keep people's motivation up and make the quizzing less taxing. We mixup the quizzes with multiple choice vs. type-in-the-answer so people are getting the right balance.

I'm pleasantly surprised that I can try this out right away without an account, instead of having to join some waitlist.

yeah, we thought it was important to let people try it as quick as possible from the landing page

How about get rid of your fake GAN-faced reviews?

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