• Reygle@lemmy.world
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    20 hours ago

    Am I living in an alternate timeline? They’ve been making GPUs for quite some time- and B580 was actually pretty good, incredibly good for the price.

  • Itdidnttrickledown@lemmy.world
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    17 hours ago

    The problem with intel. They never just keep going. They announce some new gpu/graphics product and when it falls short they don’t or wont stick with it. They abandon it and use it as a write off. They have done this multiple times and I have no reason to believe they will do anything different. The last time was just a few years ago and when sales and performance lagged they just quit.

      • imetators@lemmy.dbzer0.com
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        13 hours ago

        Intel ARC is a GPU brand by Intel that are half the price of a typical Nvidia card at almost the same performance. They been unpopular due to shaky drivers but they have never been canceled. So, stating that Intel will finally enter GPU market is just plain misleading.

      • treesquid@lemmy.world
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        21 hours ago

        English clearly isn’t their first language, but the intent is pretty obviously “As if they aren’t already making ARC GPUs?”

  • Wioum@lemmy.world
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    2 days ago

    I had to check the date on the article. They’ve been making GPUs for 3 years now, but I guess this announcement–although weird–is a sign that Arc is here to stay, which is good news.

  • Goodeye8@piefed.social
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    2 days ago

    Well that article was a waste of space. Intel has already stepped into the GPU market with their ARC cards, so at the very least the article should contain a clarification on what the CEO meant.

    And I see people shitting on the arc cards. The cards are not bad. Last time I checked the B580 had performance comparable to the 4060 for half the cost. The hardware is good, it’s simply meant for budget builds. And of course the drivers have been an issue, but drivers can be improved and last time I checked Intel is actually getting better with their drivers. It’s not perfect but we can’t expect perfect. Even the gold standard of drivers, Nvidia, has been slipping in the last year.

    All is to say, I don’t understand the hate. Do we not want competition in the GPU space? Are we supposed to have Nvidia and AMD forever until AMD gives up because it becomes too expensive to compete with Nvidia? I’d like it to be someone else than Intel but as long as the price comes down I don’t care who brings it down.

    And to be clear, if Intels new strategy is keeping the prices as they are I’m all for “fuck Intel”.

      • gravitas_deficiency@sh.itjust.works
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        2 days ago

        This is a big part of it, imo. They kissed the ring.

        The other part of it is that, per the article, this is an “AI” pivot. This is not them making more consumer-oriented GPUs. Which is frustrating, because they absolutely could be a viable competitor in low-mid tier if they wanted to. But “AI” is (for now) much more lucrative. We’ll see how long that lasts.

    • ZeDoTelhado@lemmy.world
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      2 days ago

      CPU overhead is quite well known and actually damages a lot the arc cards’ position on the budget class

  • tal@lemmy.today
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    2 days ago

    I don’t know if “GPUs” is the right term, but the only area where we’re seeing large gains in computational capacity now is in parallel compute, so I’d imagine that if Intel intends to be doing high performance computation stuff moving forward, they probably want to be doing parallel compute too.

    • AdrianTheFrog@lemmy.world
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      2 days ago

      Intel’s Gaudi 3 datacenter GPU from late 2024 advertises about 1800 tops in fp8, at 3.1 tops/w. Google’s mid 2025 TPU v7 advertises 4600 tops fp8, at 4.7 tops/w. Which is a difference, but not that dramatic of one. The reason it is so small is that GPUs are basically TPUs already; almost as much die space as is allocated to actual shader units is allocated to matrix accelerators. I have heard anecdotally.

        • AdrianTheFrog@lemmy.world
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          19 hours ago

          Yes, it works out to a ton of power and money, but on the other hand, 2x the computation could be like a few percent better in results. so it’s often a thing of orders of magnitude, because that’s what is needed for a sufficiently noticeable difference in use.

          basing things on theoretical tops is also not particularly equivalent to performance in actual use, it just gives a very general idea of a perfect workload.