Prompt-Engineering-Guide VS fsrs4anki

Prompt Engineering Guide is the holy grail of all guides, aiming to make it easier to stay up-to-date with prompt engineering guides, techniques, applications, and papers. If you are getting started, this is an excellent place to start.

Guides, papers, lecture, notebooks and resources for prompt engineering: https://github.com/dair-ai/Prompt-Engineering-Guide

this has been a great resource. approachable and great for practitioners. it's frequently updated with new papers and techniques https://www.promptingguide.ai/

The idea behind prompt engineering is to construct the queries given to the language models to optimise their performance. This helps to guide them to generate the desired output by fine-tuning their response. There is a plethora of research papers out there on different forms of prompt engineering. DAIR.AI published a guide on prompt engineering that you might find useful to get started.

Prompt Engineering Guide

Let's try to understand what is Prompt Engineering is all about. Here's the quote from Prompt Engineering Guide. DAIR-AI

I found this resource [0] handy for getting a grasp on all the different terms people use (zero/one-shot, tree of thoughts, RAG, etc). It's not super detailed, but was enough for me (a professional developer) to get started on some side projects with Mistral.

[0] https://www.promptingguide.ai/

There are better guides out there too

- https://www.promptingguide.ai/readings

- https://github.com/dair-ai/Prompt-Engineering-Guide/tree/mai...

- https://github.com/microsoft/promptbase (this one is less of a guide, but is likely the current SoTA)

For note-taking specifically, I've tried everything from plain old pen and paper to more modern solutions like Evernote and emacs (if you can call that modern), but nothing I've come across really beats Anki.

Although its main selling point is as a program for flashcards with spaced repetition, it comes with pretty much all the features of a good note-taking app, like tags, easy to organize, synchronization across devices (you can set up your own server), good interface for searching through your notes (which are stored in an Sqlite db if that matters), and yes, LaTeX. Not only that, it's also highly extendable with third-party plugins, so if there are features that you miss chances are there's a plugin for it. In other words, you can use it perfectly fine just taking notes. However, where it really shines is in all of this in combination the spaced repetition algorithm, which is now on steroids with FSRS[1][2]. The downside is that for this to be effective for the things you want to memorize, you'll have to write your notes to be suitable for a flashcard, but if you do it consistently you'll soon notice that you can store most of your notes in your head (needless to say, any student would greatly benefit from this). Now, if that's too much work, you can still just use the scheduling to have it remind you of your notes. Either way, even as someone who sometimes goes out of his way to shoehorn everything into Emacs, I can't see a reason not to use anki for note-taking.

[1]https://github.com/open-spaced-repetition/fsrs4anki/blob/mai...

[2]https://www.youtube.com/watch?v=OqRLqVRyIzc

I recommend the new algorithm of Anki: https://github.com/open-spaced-repetition/fsrs4anki

It would be nice if you could report this on Github. You can do it here: https://github.com/open-spaced-repetition/fsrs4anki/issues/n...

As for randomly getting a lot of reviews, honestly, no idea. You should submit an issue on github: https://github.com/open-spaced-repetition/fsrs4anki/issues/new/choose

u/PoppingWebster, here's a guide on how to use built-in FSRS in the latest version of Anki: https://github.com/open-spaced-repetition/fsrs4anki/blob/main/docs/tutorial.md

You can watch AnKing's video and read this guide.

Detailed info here: https://github.com/open-spaced-repetition/fsrs4anki/wiki/The-mechanism-of-optimization

use FSRS tho

More information on the new scheduling algorithm:

FWIW I've been using it for the last 10 days and it's finally resolved some of my pain points about having to trial-and-error adjust the old scheduling algorithm, since the content of each deck can greatly affect what the optimal retention is. Now you can just retrain the weights for each deck you have and it will adapt appropriately. The paper is also definitely worth reading if you want to see some rigorous analysis of large-scale real-world spaced repetition science.

[0] https://github.com/open-spaced-repetition/fsrs4anki

[1] https://dl.acm.org/doi/10.1145/3534678.3539081?cid=996605471...

[1] https://github.com/open-spaced-repetition/fsrs4anki/wiki/The...