• 5 Posts
  • 123 Comments
Joined 1 year ago
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Cake day: June 21st, 2023

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  • At least for me, the whole “made by devs for devs” isn’t really the major downfall. It’s the fact that it can’t be trusted to remain functional in a dynamic environment. I like using the command line, but sometimes that’s just not enough.

    If I need a specific software package, I can download the source, compile it, along with the 100 of libraries that they chose not to include in the .tar.gz file, and eventually get it running.

    However, when I do an “apt update” and it changes enough, then the binary I compiled earlier is going to stop working. Then I spend hours trying to recompile it along with it’s dependencies, only to find that it doesn’t support some obscure sub-version of a package that got installed along with the latest security updates.

    In a static environment, where I will never change settings or install software (like my NAS), it’s perfect. On my desktop PC, I just want it to work well enough so I can tinker with other things. I don’t want to have to troubleshoot why Gnome or KDE isn’t working with my video drivers when all I want to do is launch remote desktop so I can tinker with stuff on a server that I actually want to tinker with.















  • I’m curious, why does this require OpenSSL in order to compile? I’m not aware of any audio formats that use encryption, but I could be wrong.

    My first thought was for connecting to https streams, but I don’t remember Winamp having this capability. “Back in the day,” I used Winamp for playing local audio and RealPlayer for what little streaming was available.


  • When it comes to writing code, there is a huge difference between code that works and code that works *well." Lets say you’re tasked with writing a function that takes an array of RGB values and converts them to grayscale. ChatGPT is probably going to give you two nested loops that iterate over the X and Y values, applying a grayscale transformation to each pixel. This will get the job done, but it’s slow, inefficient, and generally not well-suited for production code. An experienced programmer is going to take into account possible edge cases (what if a color is out of the 0-255 bounds), apply SIMD functions and parallel algorithms, factor in memory management (do we need a new array or can we write back to the input array), etc.

    ChatGPT is great for experienced programmers to get new ideas; I use it as a modern version of “rubber ducky” debugging. The problem is that corporations think that LLMs can replace experienced programmers, and that’s just not true. Sure, ChatGPT can produce code that “works,” but it will fail at edge cases and will generally be inefficient and slow.