Comment by JackDanMeier

Comment by JackDanMeier 13 hours ago

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?

TheDong 12 hours ago

Bullshitting the AI maliciously doesn't matter, if you don't want to study effectively, you won't study effectively, and that's not a problem for the app.

> any knowledge rather than specifying that the exact answer should be graded

I don't understand what you mean. The important thing is to feed back into the SRS algorithm "How much does this card need to be studied", and if you mean "any knowledge means we can study it less often", then I doubt the SRS will be able to be effective.

What are you suggesting to feed back into SRS? How will you ensure cards the user knows very well quickly get pushed way back (so the user isn't overwhelmed with a boring slog), and cards they only sorta know bubble up more quickly to start to cement the knowledge?

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JackDanMeier 12 hours ago

My understanding of what is important to feedback into the SRS is, was I able to retrieve the memory, and does the representation in my memory align with what I recalled.
As an example Term: "What is the capital of France and how many inhabitants does it have?" Correct definition: "Paris, which has 2 000 000 inhabitants."
For me there is a difference in not having the answer at all, which falls into "again". But what about if I'm able to retrieve that Paris is the capital, but I remember that the population is 1 500 000. This is where the gray zone begins

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- TheDong 12 hours ago
  
  If you want to remember the population correctly, then that isn't a gray zone, that's an "again". That's entirely unambiguous to me, and if you let yourself slide on that, you're hurting yourself.
  There's a lot more room for gray zones in language learning, where you might have the french card "doubler" and answer it as "to pass", and then see the actual answer is "1. to overtake, 2. to double", in which case you have to read your heart and decide whether missing the second definition was careless because it's so obvious, or if it merits an "again"
  An AI also can't really know, btw, if your answer of "to pass" was "to pass (overtake)" (correct), or "to pass (like a note in class)" (incorrect).
  That's not the best example, but there are a ton of ambiguous english words, and you only know in your own heart which meaning you meant.
  
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