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Cake day: July 12th, 2023

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  • It’s probably not a bluff. They’ve pretty much saturated the U.S. market; there’s not much room left to grow here. It would make more sense to focus their efforts on growing in other regions where they have plenty of headroom to increase their userbase and monetization. Depending on how things play out, they could match their current revenue in a matter of years and still have room left to grow. There’s also the potential to re-enter the U.S. market down the line. Why would they throw that all away and essentially create their own competitor by selling their core technology and diluting/confusing their brand with whatever U.S. company they sell to?










  • While we’re talking about asymmetric encryption, can someone explain to me why you can’t decrypt information with the same public key that encrypted it? I understand the analogies (locks on a briefcase, unmixing paint, etc), but I can’t “un-analogize” them to understand what’s actually going on. Encryption keys aren’t physical locks or paint. They’re numbers(?). So why can I encrypt something by multiplying by a known public encryption key, but I can’t decrypt it by dividing by that same known public key?





  • I’m not sure if the piracy megathread or FMHY megathread cover the *arr stack specifically, but they have lots of information so I’m recommending them broadly for anyone wanting to ingest information about piracy.

    Regarding what the arr stack even is:

    Tldr, you set up a list of public and/or private trackers in Prowlarr or Jackett. In Radarr and Sonnar you set up movies and shows respectively that you want to keep track of. Rad/Sonarr check those trackers for releases for your tracked media matching criteria (like resolution, size, language, etc).

    When it finds a matching release, it sends the torrent file or magnet link to your torrent client to download. When it finishes, Rad/Sonarr hardlink or copy the file to a library location and organize/name them according to rules you set.

    You can point Jellyfin or Plex to that library location and all the media will be organized so it can easily figure out what media is there and grab metadata for it (cover images, description, ratings, etc). Then you can watch that media through Jellyfin/Plex or an app that plugs into them.

    The *arrs also work with usenet if you’d prefer that over or in addition to torrenting with a vpn.


  • Radar and Sonarr are tools to track movies and TV shows respectively. You can add a movie/show to track, tell it the quality you want it in, and set up Prowlarr or Jackett to give Son/Radarr the access to the torrent trackers it needs. You can also use Usenet but I have no experience there.

    It will search those torrent trackers for releases matching your movies/shows in the quality and language you set for them and send the downloads to the torrent client you set up. When the client finishes downloading, Son/Radarr copies (or hardlinks) the files to your library folders.

    If Son/Radarr is tracking a show that you currently have downloaded in 480p, but the quality profile allows upgrades up to 1080p, it will search for 720p and 1080p releases and pick the best match it can find. When the torrent client finishes downloading it, Son/Radarr will automatically replace the 480p release with the 1080p release it just downloaded.


  • We used the 100 AI and 100 human White faces (half male, half female) from Nightingale and Farid. The AI faces were generated using StyleGAN2. The human faces were selected from the Flickr-Faces-HQ Dataset to match each of the AI faces as closely as possible (e.g., same gender, posture, and expression). All stimuli had blurred or mostly plain backgrounds, and AI faces were screened to ensure they had no obvious rendering artifacts (e.g., no extra faces in background). Screening for artifacts mimics how real-world users screen AI faces, either as scientists or for public use, and therefore captures the type and range of stimuli that appear online. Participants were asked to resize their screen so that stimuli had a visual angle of 12° wide × 12° high at ~50 cm viewing distance.