lonk11

8 ms·

1.
Reducing "show less like this" by 11% with NSFW filtering(blog.foryou.club)
1 points by lonk11 4mo ago|0 comments
2.
by lonk11 4mo ago
Building a custom feed for Bluesky which uses collaborative filtering over the likes data: https://foryou.club How the algorithm works: it finds people who liked the same posts as you, and shows you what else they’ve liked recen
3.
by lonk11 5mo ago
My original title was: "Serving For You from my living room"
4.
Serving the For You Feed(atproto.com)
3 points by lonk11 5mo ago|1 comments
5.
by lonk11 1y ago
For You is based on your likes. If you get an empty feed then you probably haven't liked anything yet. Try liking a couple of posts in Discover feed and get back to For You.
6.
by lonk11 1y ago
Since For You is based on likes I would suggest liking more posts that you want to appear in your For You feed.
7.
by lonk11 1y ago
"likes by people you follow" is "Popular with Friends": https://bsky.app/profile/bsky.app/feed/with-friends The For You one uses only your likes: it finds people who liked the same posts a
8.
The Drivers of HRM's Performance on Arc-AGI(arcprize.org)
3 points by lonk11 1y ago|1 comments
9.
by lonk11 1y ago
This is definitely doable and anyone can build such a feed using Bluesky's APIs. As an example, I built a "For You" feed https://bsky.app/profile/did:plc:3guzzweuqraryl3rdkimjamk/fe... that finds t
10.
by lonk11 2y ago
Running one layer 4 times should fetch the weights of that layer once. Running 4 layers makes you fetch 4x parameters. The recurrent approach is more efficient when memory bandwidth is the bottleneck. They talk about it in the paper.
11.
by lonk11 2y ago
What you are describing is similar to how https://LinkLonk.com works (my side project) - when you "like" a link you get connected to the RSS feeds that posted that link and other users that also liked it. Then you get
12.
Being Productive(furidamu.org)
1 points by lonk11 2y ago|0 comments
13.
by lonk11 2y ago
My understanding is that the attention in all transformer layers is "causal" - that is the output of a transformer layer for token N depends only on tokens from 0 to N. This means that every attention layer can use previously calc
14.
by lonk11 2y ago
I think the commenter was thinking about the input embedding layer, where to get an input token embedding the model does a lookup of the embedding by index, which is constant time. And the blog post author is talking about the output layer
15.
by lonk11 3y ago
Just a directory of feeds could be of limited use. You don't know the signal-to-noise ratio of each feed for you. You subscribe to tens or hundreds of feeds and, boom, you have another problem - how do you prioritize which feed to read
16.
by lonk11 3y ago
I haven't used Artifact, but my understanding is it uses "AI" to personalize the feed of content and the sources of content it aggregates are based on an allow list of publishers. LinkLonk differs in these two aspects: 1. The
17.
by lonk11 3y ago
gorilla/mux supports parameters in the path as well. For example: "/posts/{id:[0-9]+}" Passing the parameters from the handler to the template could be left to the user of the library.
18.
by lonk11 3y ago
Yes, that would be useful. Basically, what you have in https://github.com/infogulch/caddy-xtemplate/blob/master/tem... - but without Caddy dependencies and with a way to use any router library (I use gor
19.
by lonk11 3y ago
Thanks for sharing! I liked the idea of defining the handle path in the name of the template and the auto-reloading on change functionality. I wish this was a stand-alone library that I could use in my custom Golang server. Do you know if s
20.
Underwater ears everywhere(computer.rip)
452 points by lonk11 3y ago|170 comments
21.
by lonk11 3y ago
At first I read it as a limit on the number of posts per day you can create , which seemed very generous. Realized that it was the number of posts you can read which is unreasonably low. Maybe it's a test to see how many power users
22.
by lonk11 3y ago
I recommend this podcast episode on the financial interests involved: https://www.michaelgeist.ca/podcast/episode-172-marc-edge-on...
23.
by lonk11 3y ago
What made a similar legislation "work" in Australia? Was it harder for Facebook and Google to block news there as well?
24.
by lonk11 3y ago
Yes, it requires keeping track of how much each user trusts each other user. And then when you rank content for user A, you use the trust table of user A as weights of upvotes. This is more computationally intensive than sorting by the raw
25.
by lonk11 3y ago
One issue is that the amount per upvote is only known at the end of the month - only then you know how many upvoted to split the $1 over.
26.
by lonk11 3y ago
Medium did this with "claps". Press once for a single clap. Press and hold to add multiple claps proportional to the time you hold it.
27.
by lonk11 3y ago
I'm building https://linklonk.com which works this way - you get content ranked based on what you upvoted. This is to make the incentives for voting aligned and help prevent abuse. I think the problem with karma/reput
28.
Mortal Komputation: On Hinton's argument for superhuman AI(inference.vc)
1 points by lonk11 3y ago|1 comments
29.
by lonk11 3y ago
The dilemma you face stems from the ambiguous nature of the upvote button: 1. As an "agree" button - you upvote to get the perspective you share to be displayed more prominently to other people. It is a way for you to influence ot
30.
by lonk11 3y ago
1. The article suggests running PageRank on a graph of users as nodes and edges as - "has user A upvoted a comment of user B" as an edge: """ Since it's likely that one user may upvote multiple comments from th

More ›