lonk11

8 ms·

31.
AI Reflections(blog.piekniewski.info)
6 points by lonk11 4y ago|5 comments
32.
by lonk11 4y ago
The article is about a solution to make lithium metal anode more stable. They discovered a coating that prevents the formation of dendrites, which are the cause of short cycle life of previous attempts at lithium metal anodes.
33.
We May be Surprised Again: Why I take LLMs seriously(inference.vc)
3 points by lonk11 4y ago|0 comments
34.
by lonk11 4y ago
To help with discovery of new RSS feeds I use this mechanism for https://linklonk.com - when you upvote or submit a link, you connect (subscribe) to all users that upvoted and to all RSS feeds that posted that link. For example
35.
by lonk11 4y ago
The feed ranking algorithm I implemented for LinkLonk does reduce the weight of your vote the more you vote. If I upvote what you upvoted then your votes get more weight for me. This incentivizes each user to upvote what they truly found us
36.
by lonk11 4y ago
One kind of collaborative filtering algorithm is "Personalized PageRank" (PPR). Like the regular PageRank you do a bunch of random walks on the graph of users and items where the upvotes are the edges of the graph. What makes it &
37.
Attack Techniques: Phishing via Local Files(textslashplain.com)
2 points by lonk11 4y ago|0 comments
38.
by lonk11 4y ago
Likely depends on the language. With Go I like using https://sqlc.dev/ - it generates Go-code from a SQL script. You get the benefits of static typing for parameters and return types + it removes much of the boilerplate inv
39.
by lonk11 4y ago
Related coverage with more graphs: https://erictopol.substack.com/p/the-new-obesity-breakthroug...
40.
Near Infrared Light (940nm) Improves Covid Outcomes: Randomized Control Trial(youtube.com)
3 points by lonk11 4y ago|0 comments
41.
by lonk11 4y ago
A simple algorithm is to sort content by the signal-to-noise ratio (SNR) of the source feed. Basically, the more you "liked" past content from a given feed - the more priority is given to new content from that feed. A more detail
42.
by lonk11 4y ago
You can get an RSS feed of posts of any Mastodon user. Just add ".rss" to the profile url. For example, mstdn.social/@feditips -> mstdn.social/@feditips.rss Details: https://mstdn.social/@feditips&#x2F
43.
by lonk11 4y ago
The process you are describing can be automated a bit. Imagine your feed reader automatically subscribes you to feeds of articles you liked (star/thumbs up/favorite). Let's say you start subscribed to an HN feed of items that
44.
by lonk11 4y ago
What you are describing is similar to how my hobby project works: https://linklonk.com When you upvote content (+1) you make your connection stronger to those who posted that content and also those who also upvoted it. When you
45.
by lonk11 4y ago
LinkLonk supports comment notifications for any item that you have subscribed to. You get notified through browser notifications and email. And you can mute/follow individual branches of the comment tree. Details: https://li
46.
by lonk11 4y ago
The way I am trying to solve this is by building a different kind of content feed. One that is not optimized for "time-spent-on-site" but for "will you be happy to have spent time on it". This is how https://l
47.
by lonk11 4y ago
I'm building https://linklonk.com - a news aggregator that prioritizes content from sources (RSS and other user channels) that you upvoted before. The server part is written in Golang (sqlc, pgx, gorilla/mux) and I thi
48.
by lonk11 4y ago
This also seems to be gameable. Suppose you have blue and green camps as described in the linked paper. And if content gets ranked high when it gets approval from both blue and green users then one of the camps may decide to promote their o
49.
by lonk11 4y ago
I built a social rss reader that ranks content based on how much you liked other content posted by the same feed or user: https://linklonk.com I haven't marketed it much except for a Show HN. I spent $20 on Google Adwords t
50.
by lonk11 4y ago
I used Material for my hobby project [1] and got this feedback: "Maybe I'm the only one, but I don't like the UI. It seems like a demo for a Material design app. I think the site has lots of potential, but without an original
51.
by lonk11 4y ago
"TLDR is that with just a new anode made from carbon nanofibers and sulfur" The new material they discuss is for the cathode side (not anode). That's side where the lithium ions go when the battery is charged. The cathode of
52.
by lonk11 4y ago
"Art 6: “… actively disseminate positive energy, and promote the application of algorithms to be good.”" It depends on who it is "positive" and "good" for. For the society, the government, or the user? I would
53.
by lonk11 5y ago
Indeed, RSS is a great minimal API and we need more tools that can create and consume feeds. For example, you can create a feed in siftrss.com and submit it to LinkLonk so it could rank content from feeds you follow based on their signal-to
54.
by lonk11 5y ago
Yes, that's the focus right now. Make it a good tool and then make it a good network. The functionality that supports single-player mode is: - bookmarking - you can search your past liked items - subscribing to rss feeds Please let me
55.
by lonk11 5y ago
Your assumption is correct, user retention is difficult. I've been running LinkLonk for a year now and out of >1000 users that created accounts we have ~9 daily active users on the site and 43 users are getting recommendations by em
56.
by lonk11 5y ago
LinkLonk can also send new link recommendations by email. There is also https://refind.com
57.
by lonk11 5y ago
At the end the author talks about curated link collections as a solution - create them using Pinboard.in and consume them via RSS. I think the part that is missing is how to discover the link collections to subscribe to. I'm building
58.
by lonk11 5y ago
Hello future! Glad you like it. Do you have any suggestions on how it could work better for you?
59.
by lonk11 5y ago
Yes, this is a very natural conclusion to make. We all have definitely seen people upvoting content as a way to promote their opinion, even if the content is not accurate or an outright lie. This happens on Facebook, Twitter, Reddit. If peo
60.
by lonk11 5y ago
How about a recommendation algorithm that works like this: - When you upvote an item, the algorithm connects you to other people who upvoted it and shows you what else they upvoted ("more like this") - When you downvote - the algo

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