graboid

Anki checks two of these boxes, but the data is stored in SQLite. It is a nice program, open source and actively developed, with many online resources available and a large community.

My advice would be, if you happen to already write your notes in some plain text format, to create your flashcards in your notes. E.g. if you use one of the fancy new PKM tools like Logseq/Obsidian/etc. you can use one of the available plugins to sync to Anki (or roll your own script, thats what I do). For me thats a solution with which I feel very comfortable (and I am rather picky and have tried out a lot of tools and workflows). Main advantages for me:

1. your notes and SRS questions are not separated

2. you have full control over your data

3. you don't have to use the editor of any SRS app, instead you can use whatever tool/editor you are most comfortable with

4. By syncing to Anki, I get all the nice stuff that comes with Anki: mobile clients+sync, nice statistics, endless styling customizability.

Thanks! That link especially contains some really helpful write-ups. I never really needed to think much about performance, as my C# usage always was constrained to simple CRUD stuff in server backends, which is a shame really, as it is such a nice language.

Can you recommend any resource on how to get into writing high-performant C#?

I got a question. How can researchers who are not working at the largest tech companies even "compete" with models like GPT-3? From what I understand, these currently best performing models need an amount of training data and specialized hardware that is not obtainable for 99% of ML researchers. If you think you came up with a better architecture for a language model, one that could in theory beat GPT-3 on benchmarks, wouldn't you face the problem that you cannot actually prove that it would perform better?