• 2 Posts
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Joined 1 year ago
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Cake day: April 27th, 2024

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  • At this point, package management is the main differentiating factor between distro (families). Personally, I’m vehemently opposed to erasing those differences.

    The “just use flatpak!” crowd is kind of correct when we’re talking solely about Linux newcomers, but if you are at all comfortable with light troubleshooting if/when something breaks, each package manager has something unique und useful to offer. Pacman and the AUR a a good example, but personally, you can wring nixpkgs Fron my cold dead hands.

    And so you will never get people to agree on one “standard” way of packaging, because doing your own thing is kind of the spirit of open source software.

    But even more importantly, this should not matter to developers. It’s not really their job to package the software, for reasons including that it’s just not reasonable to expect them to cater to all package managers. Let distro maintainers take care of that.










  • smiletolerantly@awful.systemsto196@lemmy.blahaj.zonerule
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    1 month ago

    Hmm, it’s a bit cheaper here (I think - it’s been a while!), but yeah.

    Electricity is expensive here, I think the server setup draws 40€/month, but that is for the entire setup of course, not just pirating-related stuff; plus ~9€/month for the two usenet backbones, and a couple bucks for trackers.



  • smiletolerantly@awful.systemsto196@lemmy.blahaj.zonerule
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    1 month ago

    That’s mostly true, although you usually (in my case at least) I am aware of all shows I have available on Jellyfin, and it’s only ones I like.

    For discovering new shows to download, things like Jellyseerr actually do give recommendations… No idea how good they are though.

    But frankly, Netflix used to recommend a lot of things that sounded interesting on the surface-level, and then turned out to be utter shit. Probably not an entirely bad thing to be lacking recommendations :D


  • smiletolerantly@awful.systemsto196@lemmy.blahaj.zonerule
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    1 month ago

    For Non-English ones in my native language. There isn’t a lot of them. AFAICT the one I mostly use is free for a handful of requests/day, but generously lifts that limit in exchange for a “donation” 😄

    (It’s only around 20/year)

    Edit: and just to be clear, that one Tracker took us from “basically nothing is available in our language” to “literally everything is”, so it’s money well spent.


  • smiletolerantly@awful.systemsto196@lemmy.blahaj.zonerule
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    1 month ago

    For a very long time, I was one of the people who kep saying:

    “I used to pirate until Netflix came along; now I pirate because of the fragmentation of services; should a good service become available at a reasonable price again, I will be happy to switch back.”

    But at some point, that stopped being true. More precisely, my *arr-Stack + Jellyfin setup become so stable, I do no longer really think about it, while also getting better quality content, and often faster than I would due to global licensing shennanigans.

    Another factor also is that at some point, we crossed the “enough content to mindlessly scroll until we find something to watch” barrier, which my GF actually kinda missed from Netflix.

    The crazy thing though, is that we pay actual money for this: hardware cost; electricity; access to usenet trackers and two usenet backbones. All in all, I do not think it’s cheaper than getting Netflix+Prime+Disney.

    It’s just better. And we will not be switching back, ever.




  • No. I am not saying that to put man and machine in two boxes. I am saying that because it is a huge difference, and yes, a practical one.

    An LLM can talk about a topic for however long you wish, but it does not know what it is talking about, it has no understanding or concept of the topic. And that shines through the instance you hit a spot where training data was lacking and it starts hallucinating. LLMs have “read” an unimaginable amount of texts on computer science, and yet as soon as I ask something that is niche, it spouts bullshit. Not it’s fault, it’s not lying; it’s just doing what it always does, putting statistically likely token after statistically liken token, only in this case, the training data was insufficient.

    But it does not understand or know that either; it just keeps talking. I go “that is absolutely not right, remember that <…> is <…,>” and whether or not what I said was true, it will go "Yes, you are right! I see now, <continues to hallucinate> ".

    There’s no ghost in the machine. Just fancy text prediction.