Given its extremely high energy and water consumption, the increased minimum system requirements driving premature hardware obsolescence, among other very problematic social and political issues, genAI/LLMs are not compatible with the values and goals of KDE Eco.

KDE is a diverse community and the opinions and projects of some KDE contributors are not representative of the entire community or KDE Eco projects.

  • mmmm@sopuli.xyz
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    1 month ago

    This sounds like KDE Eco is a thing apart from KDE and not a core initiative or value for KDE as a whole. Which is kinda sad imho. I’d imagine a project promoting stuff like eco-friendly FOSS won’t let fly shit like the “ai-native desktop” bs, but here we are.

    • ulterno@programming.dev
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      1 month ago

      That’s just a side effect of it being open. Much more so as compared to Gnome.
      So, while I may have my reservations regarding AI, I’ll not be trying to push out people making AI related KDE software.


      Oh shit. I just read the context that post was made in.
      Now I’m gonna have to filter through KDE applications myself, to determine which ones are usable.

  • illusionist@lemmy.zip
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    1 month ago

    To put it into perspective how much energy does a promt consume?

    I asked an ai. Are the numbers roughly right?

    Full Day of Heavy Agent Work (Multiple autonomous runs, multi-agent builds) is ca. 1,000 to 3,000+ Wh which is like 3 to 10 hours of GTA 5

    • punchmesan@lemmy.dbzer0.com
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      1 month ago

      There are some things “AI” isn’t fit to answer, like questions with nuance. And a “prompt” in itself isn’t a quantifiable unit. I can tell you that my gaming rig with 96 GB of RAM and an RTX 2080 could only run a quantized model – the model weights will eat up my RAM and keep my system drinking electricity. My CPU could handle it like a champ but let’s be real, all of that is to get a crappy-performance model doing work.

      I could believe that, like, a full day of heavy agent work consumed that much power running the agentic workload on my device, but there’s no way that number is accounting for the power consumed in hosted model inference, let alone training.

      • ulterno@programming.dev
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        1 month ago

        Sounds like the real problem is just data centres being in the wrong places, sucking the wrong resources.

        • AwesomeLowlander@sh.itjust.works
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          1 month ago

          In a way. And that is mostly due to capitalism. Had they taken the time to slowly scale up and use renewables, they wouldn’t have triggered this level of lashback. But no, they had to race to be first.