• themaninblack@lemmy.world
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    2 days ago

    These comments are almost there.

    You’ll end up working with passive aggressive geeks that are somehow defensive of their shitty code.

    They’ll be great at understanding the domain though

  • Karyoplasma@discuss.tchncs.de
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    3 days ago

    If you do what you love, you will never work a day in your life.

    Usually it’s because they’re not hiring, but some people are just that lucky.

  • xxce2AAb@feddit.dk
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    3 days ago

    …Maybe keep your kinks in the bedroom where they belong rather than get your jollies simping for a boss everybody else will have to put up with as well.

    • Jännät@sopuli.xyz
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      1 day ago

      Probably not a lot of open positions (well, not of the sort they’re looking for, at any rate) in the bedroom though

    • Sergio@piefed.social
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      3 days ago

      “Do you love being a scientist? Or do you love the IDEA of being a scientist?” - something I’ve been thinking a lot about recently…

      • Justas🇱🇹@sh.itjust.works
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        1 day ago

        Plenty of people thought that I will be a scientist but I did one standard deviation calculation for a test and noped out of the idea.

        • Sergio@piefed.social
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          24 hours ago

          I’ve worked as a scientist for around 10 years (and as a research programmer in various labs for 5-6 years before that) and have never done a standard deviation calculation.

            • Sergio@piefed.social
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              18 hours ago

              See, when I was in grad school I once had to calculate an agreement metric from a bunch of labels on a corpus. No problem I said, the math is easy, I can write a script in an hour or so. Fam that mfing script took me two freaking days bc there were always some little bugs or weird edge cases I hadn’t thought of. So the deal I made with myself was: I would use Matlab or a stats library or something like that, BUT I would make sure that I understood the math beforehand.

              But for whatever reason, I never had to calculate a standard deviation. Thinking about it, someone else might have done that for papers I was co-author on, though.

    • Frezik@lemmy.blahaj.zone
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      1 day ago

      Certain scientific applications are one of the better uses of machine learning techniques. For example, an extremely long black hole jet was found by having machine learning go over a ton of data from radio telescopes.

      It’s so long that the jet could not only hit another galaxy over, and not just a galaxy in a different cluster or even supercluster, but could go through the void in the filament structure of galaxies and hit another filament over.

      • Akrenion@slrpnk.net
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        1 day ago

        LLM are not the only way and more people need to realise that. There are good uses for LLMs but most use cases want different ML approaches especially when we want numbers.