The article presents a binary search implementation that works on collections that use the Eytzinger layout. It's faster than the classical binary search implementation in this case.
In Twitter, I had mastered the lists.
here, I'm a little bit late, I had been off my PC for 6 months and I don't do well on mobile devices.
I've been setting up my NEWS, FRIENDS, CHAT MOST, those type of lists, making it easier to find people. #Mastodon#Lists#Sorting#Setup#Cats#Conversation#News#Humour etc
Next up: I got this from Irreal, which I know all of you Emacs people read. However, I just wanna repost it cuz I think I just spoke with this guy yesterday on IRC. Also, he has a cool blog.
New study, impressive result: "Here we show how #AI can go beyond the current state of the art in [#sorting efficiency] by discovering hitherto unknown routines…We formulated the task of finding a better sorting routine as a single-player game. We then trained a new deep reinforcement learning agent, AlphaDev, to play this game. AlphaDev discovered small sorting algorithms from scratch that outperformed previously known human benchmarks." https://www.nature.com/articles/s41586-023-06004-9
The lack algos would make it reasonable to lengthen and widen the Explore-sortiment of boosted/favourited toots, to get "viral" toots more properly exposed.
There could be categories like:
Popular within the last:
6 hrs
24 hrs (default)
Week
Month
...
Sorting options for those could be e.g.:
🔃 By popularity (=boosts+favs)
🔃 By account name
🔃 By date/time
🔃 Random
...