• kautau@lemmy.world
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    18 hours ago

    The most important part is that it’s a local LLM model running on your machine. The problem with AI is less about LLMs themselves, and more about their control and application by unethical companies and governments in a world driven by profit and power. And it’s none of those things, it’s just some open source code running on your device. So that’s cool and good.

      • Sixty@sh.itjust.works
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        6 hours ago

        Curious how resource intensive AI subtitle generation will be. Probably fine on some setups.

        Trying to use madVR (tweaker’s video postprocessing) in the summer in my small office with an RTX 3090 was turning my office into a sauna. Next time I buy a video card it’ll be a lower tier deliberately to avoid the higher power draw lol.

      • jsomae@lemmy.ml
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        12 hours ago

        Running an llm llocally takes less power than playing a video game.

          • jsomae@lemmy.ml
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            7 hours ago

            I don’t have a source for that, but the most that any locally-run program can cost in terms of power is basically the sum of a few things: maxed-out gpu usage, maxed-out cpu usage, maxed-out disk access. GPU is by far the most power-consuming of these things, and modern video games make essentially the most possible use of the GPU that they can get away with.

            Running an LLM locally can at most max out usage of the GPU, putting it in the same ballpark as a video game. Typical usage of an LLM is to run it for a few seconds and then submit another query, so it’s not running 100% of the time during typical usage, unlike a video game (where it remains open and active the whole time, GPU usage dips only when you’re in a menu for instance.)

            Data centers drain lots of power by running a very large number of machines at the same time.