• 0 Posts
  • 146 Comments
Joined 1 year ago
cake
Cake day: June 4th, 2023

help-circle






  • It really comes down to what you’re used to. If you use Windows tools then you already know many of the workarounds for Windows and you don’t know the tools that haven’t been ported there.

    For example, you know not to use Python directly, but that you have to install anaconda instead, or whatever the current problems with Python development on Windows are.

    The big obvious thing that you can’t get away from is that you have to do things differently if you have develop for two different OSs with a view to deploying on Linux.

    In particular support for shell scripts is crap on Windows. I could learn powershell or there’s workarounds using WSL and a bunch of other stuff that I don’t need to care about, but I’d rather not bother.


  • I mean coding is difficult enough as it is, I wouldn’t choose to use an OS that makes it even harder.

    I use Linux because it makes my life easier. It has better support for development. Some of the other stuff is maybe not as easy or polished, but the support for dev tools and the ease of deploying to from local machines to servers that are also running Linux makes up for it.

    If I wanted more effort I’d still be using Windows. It would force me to work on cross platform development and deployment. The idea that there’s value in making things unnecessarily hard is just weird. I want Linux to be as simple as possible to use, so I can spend that effort on things that actually matter.










  • You might want to look at Wittgenstein.

    In his early work he went hard on this approach, and insisted that “hey philosophy is dumb”, just agree on the definitions and then chase through the implications.

    In his later work he realised that this is impossible. Words have contextual meaning that is revealed by their usage and you can’t nail down full and complete definitions in advance.

    What you’re talking about absolutely can and will never work. We have tried it and seen it fail.



  • As someone working and publishing in the field this is more a cyber jerk about American exceptionalism than actually true.

    Chinese universities and companies publish a shit tonne at pure machine learning conferences. They absolutely do a large amount of research into the fundamentals of machine learning as well as the applied stuff. They’re probably the closest to the US in terms of having large firms that are prepared to bank roll the training of the very large language models.

    Alibaba in particular has been constantly doing cutting edge stuff in terms of multimodal language models that are worth paying attention to.

    The actual truth is that China does both kinds of work. Broad foundational and applied work lead by independent research groups in companies and universities, and focused application driven stuff for direct application by the state.

    Google still stands out in terms of the amount of research it does, but this is because Google is different to everyone -other US research institutes don’t compare to it either.