• Hirom@beehaw.org
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    4 months ago

    They were years ahead of the curve with AI hardware, and they’re well placed to benefit from the AI craze.

    Regardless of whether a company’s AI product is useful, or profitable, they need lot of hardware to make it run.

    • DdCno1@beehaw.org
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      4 months ago

      To illustrate your point, my old GPU, a GTX 1080 from 2016 (basically ancient history - Obama was still president back then) remains a very useful for ML-applications today - and this isn’t even their oldest card that is still relevant for AI. This card was never meant for this, but thanks to Nvidia investing into CUDA and CUDA being useful for all sorts of non-gaming applications, the API became a natural first choice when ML tools that run on consumer hardware started to get developed.

      My current GPU, an RTX 2080, is just two years younger and yet it’s so powerful (for everything I throw at it, including ML) that I won’t have to upgrade it for years to come.

    • veroxii@aussie.zone
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      4 months ago

      What’s missing in the shield? I have a gen 1 and it still plays anything I throw at it. High bitrate HDR 4k video etc.

      • Scrath@lemmy.dbzer0.com
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        4 months ago

        I believe its missing h265 and av1 hardware support and while it probably has enough performance to handle those codecs in software, I wasn’t willing to drop more than 100 euros on a 5 year old device without hardware decoding for them

    • DdCno1@beehaw.org
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      4 months ago

      I mean, one of the core ideas behind these things is that these are highly capable devices that are receiving updates for several times as long as normal tech, so you can just keep using them for ages.

      Apart from the very latest codecs, what else should they do that they aren’t already doing?