lalord

Hi we just released version 1.0 of https://feyn.app!

About 3 years ago we launched the initial version of Feyn with this reddit post. We’ve been quietly collecting feedback and adding more features to it ever since. Today we believe we reached the point in which we have a top quality app, and wanted to share it with you.

Feyn was built as a response to there not being a well designed and easy to use iPad flashcards app. We wanted to open a book, place an iPad next to it, and just start making flashcards as easily as if we were just using pen and paper. We ended up building it, and continued to add features to it until it reached the point where we now believe it's the best iOS flashcards app for both iPad and iPhone.

The idea behind the app is quite simple, choose which concepts you want to remember during your study sessions, write flashcards for them using Feyn, and then just wait for Feyn to ask you to review them whenever it deems it optimal.

You can think of it as off-boarding the process of memorization to an app. Just make the cards and you’ll eventually memorize them.

We made quite a few interesting design decisions along the way (vertical card aspect ratio, emphasis on drawing, minimalistic UI), which we think make it stand out quite a bit when compared to other flashcard apps.

It was originally designed for the iPad + Apple Pencil, but it has now become a great iPhone experience as well.

Hi, we recently released our tracking library built to facilitate the experimentation of adding custom trackers on top of detectors, and thought people here may find it interesting, cheers!

Hi, author here, thanks for taking the time to read the article!

The objective of the demo was not to see which language could sum up a bunch of numbers the fastest. You could keep optimizing that until you are left with just `print(<the resulting number>)`. The objective was to have a simple example of looping over an array a bunch of times. The only reason I ended up summing the numbers in the array and printing them was so that LLVM wouldn't optimize it away and be unfair towards python. I actually wrote it first in Python tbh.

Yeah I agree that the tooling at the moment is inadequate, specially on linux, but both Apple and Google are working towards improving it.

Regarding the tensorflow dev summit, it was supposed to be 2 days long initially, with the S4TF talk taking place on the second day. One week before the summit, the whole day 2 got scraped due to covid19 though. So the intention was there at least.

Yeah, they have to be semantically continuous, ie floats but not ints.

Hi, author here! The git thing is regarding model versioning. The managing of a ton of very large and slightly different binary blobs is not git's strong point imo.

There are a ton of tools trying to fill this void, and they usually provide things like the comparison of different metrics between models versions, which git doesn't provide.

Hey Jeremy, I'm a really big fan. I got really interested in Swift based on your initial blogpost on it, and managed to get the company I work at to invest a bit in researching how suitable it could be for real time ML on video.

If it's not too forward, do you know at the moment if FastAI will continue to invest in Swift? I know development was a bit stalled due to the work needed for FastAI 2.0, but I was wandering if it'll resume, or if Richard Wei and Chris Lattner leaving changes anything?

Cheers and thanks for FastAI!

PD: Was working a bit on SwiftCV, added the videoio and highgui modules. Was wondering if I should PR it to fastai's or vvmnnnkv's version of the repo?