ddgr VS the-algorithm-ml

Using the shell commands plugin and ddgr, I managed to create a nice trick, which allows you to add the link to selected text without having to google it (hard to describe, but the gif should give you the idea). Here is how it works: - install the shell commands plugin https://obsidian.md/plugins?id=obsidian-shellcommands - install ddgr https://github.com/jarun/ddgr - add the following code as shell command: bash query="{{selection}}" link=$(ddgr --num=1 --json "$query" | grep "url" | cut -d'"' -f4) mdlink="[$query]($link)" echo -n "$mdlink" - in the settings for that shell command, set the stdout to "current file: caret position" - you are good to go. (Maybe give it a hotkey)

search from the CLI is hardly new.. some examples by jarun: - google: https://github.com/jarun/googler - duckduckgo: https://github.com/jarun/ddgr

Leveraging filter commands (i.e. :!) to easily/quickly manipulate lines or entire buffers/files. For example, :!date will run the external date and show you results, but :.!date (which is done by typing !! then date will run the external date command and put the result on the current line. But, also, if you have the word date on a line, then you can run :.!bash (which is done by typing !! then bash), which will execute the command date and replace the current line with the result. There are infinite uses for this, like :!sort (for sorting text), :!column -t (for aligning/tabulating text), :!awk for text manipulation, :!ddgr duckduckgo cli, ...etc

I like ddgr https://github.com/jarun/ddgr. Duckduckgo for the terminal. googler (https://github.com/jarun/googler) was great but google seem to have crippled it, at least for me. ddgr --site youtube.com QUERY .... You can use the builtin URL handler, or the JSON output, to pass the URL to a video player like mpv. yt-dlp is required for mpv to launch the video from URL.

Here is link number 1 - Previous text "Yes"

I said “parts of the recommender system code.”

This is the kind of highly emotional reaction that’s not helpful.

Yes, I am quite familiar with building ML models, both training and building my own for which I’ve been paid large sums of money, and I’m here to tell you that you don’t know what you’re taking about.

There’s so much more information about an ML system than just the trained model that is important for understanding the effects of the system on a society, and its legal, ethical, and social ramifications.

Just seeing the type of RS being used, the ranking approach, and the information on SimClusters is enough for RAI folks to start to understand the ecosystem effects and how that can show up downstream in social effects.

https://blog.twitter.com/engineering/en_us/topics/open-sourc...

Blog summarising the change: https://blog.twitter.com/engineering/en_us/topics/open-source/2023/twitter-recommendation-algorithm

People who don't share your interests (or at least what Twitter thinks your interests are). This blog post explains it in detail.

Twitter's announcement | Main GitHub Repo | ML GitHub Repo | Engineering Blog Post

where? I searched through the repo and couldn't find it.