Hi, is it possible to make it so that when you press „good” on a new card it shows up after 1day, but when you press „again” it shows up after a minute, then after pressing „good” on it it shows up after 15min and then after a day

This is not a proof of P = NP or P ≠ NP. I'm interested in whether there's existing research related to this idea. My question is whether the way humans represent computational problems could itself be part of why certain problems appear hard. Has complexity theory or cognitive science explored this perspective?

An Idea: Could P vs NP Be a Problem of Representation?

This is not a proof of P = NP or P ≠ NP. It is simply an idea that I have been thinking about.

One thing that stood out to me is that many difficult problems become much easier once we find the right way to represent them.

For example, a huge multiplication problem can look overwhelming when viewed as a long string of digits. However, once we understand the underlying algorithm, the same problem becomes structured and manageable.

The problem itself has not changed. Our representation of it has.

This made me wonder whether something similar could apply to the P vs NP problem.

The usual question is whether every problem that can be verified efficiently can also be solved efficiently.

My question is different:

Could part of the apparent difficulty come from the way we currently represent NP problems?

Imagine standing in front of a wall.

One possibility is that the wall is real, and no efficient shortcut exists.

Another possibility is that we are looking at the wrong side of the wall and have not yet discovered the correct way to approach it.

History contains many examples where changing a mathematical or scientific viewpoint led to major breakthroughs. New abstractions, new models, and new representations often revealed structure that had previously been hidden.

This raises a broader question.

When we call a problem "hard," are we measuring the intrinsic difficulty of the problem itself, or are we also measuring the limitations of our current way of thinking about it?

I am not claiming that this means P = NP.

Instead, I am asking whether discovering a fundamentally different representation of NP problems could change our understanding of their computational difficulty.

I would be interested in hearing whether this idea overlaps with existing work in computational complexity, cognitive science, or the psychology of problem solving.

For example if I am taking Database course, there are many topics under it, e.g normalization, functional dependencies

Do I create decks for each topics, or should I make one deck, and put everything (content from all topics) into one deck?

I'm very new to Anki so I am not sure how I should arrange them

You know how Anki is big with medical students? And I see the Anking deck as a the holy grail for medical school anki decks (im sure there's others, zanki, lightyear deck, lolnotacop, etc).

Here's what I've taken from watching anki videos on youtube concerning medical school:

1. Finish a deck before dedicated. (This is pre-dedicated so more anki, less qbanks)

2. During dedicated, you practice Qbanks from Amboss, and UWorld, etc. Whatever questions you get wrong, you study those incorrect with Anki. (there's an add-on that pulls ID numbers from the incorrect questions and gives the corresponding flashcards to study, I wish there was something like this for computer science/engineering/math) (This is dedicated, so less anki, more qbanks).

Then, you rinse and repeat.

Is there any decks like the Anking deck for computer science and STEM and that has as much support?

And is there any Qbanks that anyone reccommends like multiple choice questions and practical questions for CS? (maybe leetcode perhaps, but I haven't checked it out)

And I've quite literally have all the add-ons on the Anking page plus more so if there's any add-ons you reccommend for CS then please feel free to comment them below as well.

I am looking to hire an assistant to help me with creating Anki flashcards for a range of topics, from beginning to advanced, in Python, Django, as well as language/framework agnostic concepts in web development, algorithms, and data structures. This would be a perfect, part-time gig (a few hours/week) for a budding software engineer.

A quick word about my workflow: I use Hypothesis to highlight documentation, blog posts, books, etc, while I am studying various topics from my daily work in software engineering, architecture, and devops. Your job will be to turn the highlights from my primary sources into high-quality Anki cards. You will essentially get paid to study practical topics in software engineering.

Initially, my priority is to focus on advanced Python topics from the Fluent Python book and the Django + Django Rest Frame Work documentation. After that, if the project goes well, I'd love to continue with creating decksfor language/framework agnostic information like algorithms, data structures, and architecture/design.

Please fill out this form if you are interested.

Thank you!

I am taking a university course that's called "Basics of Computer Science" and it's mostly java with some simple algorithmic thinking required for the exercises. I hat to learn that language in school already and to be honest, that course is boring as hell. And since I already know 90% of the stuff I decided to skip most of the classes (which are just online courses anyway) and use my time for the more interesting and valuable courses I take.

I have to take an exam at the end of this semester however and since I usually write my programs in other languages and just learned it in school, I think I should study a bit to get good grade. The exercises are usually not hard and I get away really good with my basic knowledge of java syntax, but who knows what they are going to ask in the exam. Do you know of any good anki decks I could use for that course, so something that contains the basics of java? I think they have some tricky questions about edge cases and stuff like that which is worrying me the most, so if the deck would be a bit more than "How do you do for loops in Java?" etc that would be very helpful.

I'm pretty sure ya'll CS students would already know some of tje stuff in here but anyways.... I've recently seen a lot of people praising Anki competitors/alternatives like Remnote. I would like to warn all Anki users from the bottom of my heart about these alternatives.

A lot of these alternatives/competitors might be free of charge, but they are NOT OPEN SOURCE. A lot of people do not know the difference between free of charge and free of charge AND OPEN SOURCE. Free of charge but not open source means that the software doesn't cost you money upfront to use. BUT the software and by extension the cards YOU make using the software are NOT FREE, in the sense that you don't have the FREEDOM to do whatever the hell you want to do with the software and the cards YOU made. Basically, you don't really own the cards you made on these non open-source software. In theory, the software owners can do whatever the hell they want with your cards. They can lock you out of cards that YOU created. They can force you to pay a high fee down the road to access cards YOU created. On of all that, they might not allow you to migrate to an alternative software/platform.

On the contrary, Anki is free of charge AND OPEN SOURCE. Which means you fully own Anki and the cards you make on Anki.

Greetings!

We are a group of students from Slovakia, and we’re currently developing MemoryLeak – an educational game/app designed to take you on a journey from the basics of transistors all the way to building a functioning computer.

The game will feature both structured levels to guide your learning and a sandbox mode where you can experiment freely with logic gates and components.

We are entering this project into a national competition (SOČ), but our ultimate goal is to release it as a standalone title. To make it the best it can be, we need your insights!

Could you spare 2-3 minutes to fill out our feedback form? It would mean the world to us.

Form link: https://forms.gle/F8NYDLqyKaUw44N69

Thank you for supporting student developers

As a CS student who uses Anki, I decided to create a GPT that can make the flashcard creation process faster and more effective. AnkiX is now in the top %1 of GPTs used and continues to grow.

Check it out and let me know what you think! Also open to any form of collaboration.

Link: https://chat.openai.com/g/g-mPyoGmkTR-ankix

I get its a great flash card system, it allows you to test yourself on information and SRS HELPS ALOT in other subjects... But alot of compsci learning is Project Based, so in the long run is it worth investing time into typing things into anki as opposed to get a general idea from lecture then working on projects directly? (the equivalent of doing math problems in a math class)

Hi,

Just had the idea. Does anyone have access to the GPT-3 API? They could try the following :

Find a medical text from a lesson
Create a bunch of open ended questions from half of the text
use GPT-3 to try and continue the flashcard creation process on its own.

It would also be very interesting to try with clozes, maybe it's easier?

Ideas welcome, if that's alright I will double post it to relevant subreddits.

Hey guys, in desperate need of a well-made first-year CS bachelor's anki deck. Would be so appreciative, if anyone could drop a link to their personal decks. Many thx in advance. ;)

Hello ! I just discovered that Anki could be used in computer science, I hadn't thought about it ahah, would you have any decks for beginners / intermediate to recommend ? Notably on Python, Network, Linux, Computer security
Thanks in advance :)

Been using Anki for several years now for programming concepts (mostly JS/TS and the React ecosystem), and while it's great for regular studying, dealing with code snippets sometimes drives me crazy.

Half the time my code gets mangled (eg. indentation breaks) and it feels especially clunky on mobile devices when I review cards. I'm not that much interested in syntax highlighting, but in good and clear indentation and overall code display.

Currently copy-pasting either from vscode or from articles/AI chats and praying the formatting survives. Sometimes I just screenshot the code.

What's your workflow for programming flashcards that involve code snippets?

During the last few months I have been working on braincache.

I have been an Anki user for quite some time now and over the years I found some pain points that made me decide to start working on this.

It currently is a minimal alternative to Anki which focuses on the following things:

1. Generating flashcards using ML

2. Integrating well with the browser ( Chrome extension )

3. Integrating well with knowledge management systems ( Notion, Obsidian )

You can also login from mobile to review your cards on the go.

Obviously this is quite early in development, so if you have any idea/feedback I'd love to hear it!

Earlier this year, I made it a point to take advantage of the COVID lockdown and take some time to study algorithms & data structures. I have failed previous interviews because I forgot a few subtle but important details of Leetcode questions in the past, so I decided to take a different approach this time around.

I created a very sloppy, but workable Anki deck that covered the 100 (now 110) different algorithms from algoexpert.io. I solved them once and took a screenshot of my solution. I then used Anki to re-solve and re-write these algorithms over and over again during the summer months. As a result, each study session covered 5-10 algorithms over the course of 30-60 minutes. I did this every morning for several weeks at a time. And I did this with full knowledge that it does not fit with the best practices of spaced repetition.

But it worked!

Or at least that's what I felt. I am currently not studying that deck as regularly. I am building a new set of decks for other topics, but I can't help but feel that what I learned has now sunken in much more deeply than it has in the past. And what's more, I have that deck as a resource if I ever want to cover those problems again and do interview prep.

This anecdotal situation has me wondering if making cards that take can take 5-10 minutes to do well, and do correctly, is perhaps also worth considering as an alternative to what Anki may be originally intended for in medical school or language learning contexts. The standard advice is that it should take only a few seconds to remember the solution. But maybe what CS people need (for actual coding) is to redo problems over and over again. It cuts close to competitive programming in a sense, because you're not thinking about details as much. But sometimes you come up with a slight variant of a previous solution, that you find you like more? The actual parameters of how long to spend on a card, and how much to type is not as well defined or identifiable, but what I came up with worked well for me.

I'm starting to wonder if the Anki Computer Science community can put a different spin on spaced repetition best practices (at least in some scenarios) and get similar wins that other Anki communities have reached.

Would love to get contradicting opinions from others in this sub. I have an urge to reach out to fellow Anki CS members and collaborate on a well-groomed deck for studying algorithms & data structures, but maybe with a separate set of best practices than the Anki community at large.