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NVIDIA Releases $15,000 USD Linux-Powered Developer System

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  • NVIDIA Releases $15,000 USD Linux-Powered Developer System

    Phoronix: NVIDIA Releases $15,000 USD Linux-Powered Developer System

    Besides NVIDIA announcing yesterday the $999 GeForce GTX TITAN X graphics card that will soon be reviewed under Linux on Phoronix, NVIDIA also announced the Digits DevBox: a $15,000 USD Linux-powered system...

    Phoronix, Linux Hardware Reviews, Linux hardware benchmarks, Linux server benchmarks, Linux benchmarking, Desktop Linux, Linux performance, Open Source graphics, Linux How To, Ubuntu benchmarks, Ubuntu hardware, Phoronix Test Suite

  • #2
    What a monster...

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    • #3
      I suspect this is not really for deep learning research, but for companies that want an easy way to use deep learning:
      All librairies already installed, set up properly, etc: no need to pay a maintainer for that stuff, just pay your engineers train their models.

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      • #4
        all dem buzzwords

        i'd rather suggest the MIT course on machine learning, then this thing

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        • #5
          For the love of God, why Ubuntu?

          If it's a support thing doesn't Red Hat offer something?

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          • #6
            Originally posted by gens View Post
            all dem buzzwords

            i'd rather suggest the MIT course on machine learning, then this thing
            Of course you would need education to use such a thing. But machine learning without actual machines that learn is just waste of time and scientific nonsense.

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            • #7
              Originally posted by tuke81 View Post
              Of course you would need education to use such a thing. But machine learning without actual machines that learn is just waste of time and scientific nonsense.
              when you learn how it works you know how well it will do
              the actual processing can be done when sleeping or in some data center in your company/school

              point i was going for is that it is far more important to know what this does, as thinking that some program will process your data perfectly can lead to false belief

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              • #8
                Originally posted by kaprikawn View Post
                For the love of God, why Ubuntu?

                If it's a support thing doesn't Red Hat offer something?
                Ubuntu supports nVidia's proprietary drivers with packages in their main repos. Aside from that, Linux is Linux: there's no compelling reason not to use a distro with the largest desktop footprint (and therefore largest community support) that also offers paid support.

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                • #9
                  Originally posted by gens View Post
                  when you learn how it works you know how well it will do
                  the actual processing can be done when sleeping or in some data center in your company/school

                  point i was going for is that it is far more important to know what this does, as thinking that some program will process your data perfectly can lead to false belief
                  The nice thing about ridiculously big hardware like this is that you don't need to know as much about solving the problem. You can just throw ALL of the data into the system and let it figure out which data is relevant instead of needing a human to do it.

                  So what this would do will probably take just as long as older systems, but it will be able to look at more information and find more probability clusters in the data.

                  Comment


                  • #10
                    Originally posted by Zan Lynx View Post
                    The nice thing about ridiculously big hardware like this is that you don't need to know as much about solving the problem. You can just throw ALL of the data into the system and let it figure out which data is relevant instead of needing a human to do it.

                    So what this would do will probably take just as long as older systems, but it will be able to look at more information and find more probability clusters in the data.
                    ofc
                    but there are many ways to process that data and if you don't understand them you can't choose which one to use and how to set it up

                    something like this would be useful for, idk, computer vision

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