• 1 Post
  • 34 Comments
Joined 1 year ago
cake
Cake day: July 10th, 2023

help-circle



  • The real example of a health check trait really brings this issue to life, it’s linked within op’s article as well

    Is this a reasonable summary?

    Say you want a trait where a method returns a task that you would like to sometimes run within your own thread and sometimes move it to a separate thread to be executed, that means the Send constraint isn’t necessary to add to your trait but it would be nice to add that constraint within another method’s parameter definition so that it can accept structs that implement the trait and further constrain that implementation to be Send’able. That’s now possible with this new rust language feature, though it was previously possible through a crate, now it’s no longer needed.







  • 0x01@lemmy.mltoLinux@lemmy.mlVLC Player
    link
    fedilink
    arrow-up
    67
    ·
    5 months ago

    We don’t deserve our open source heroes, so grateful for the incredible free software ecosystem

    Gimp, 7zip, blender, vlc, open office, the kernel, thousands of others, I feel like our lives have been universally improved by these inverted charity projects. The few taking care of the undeserving many.


  • I’m a 10 year pro, and I’ve changed my workflows completely to include both chatgpt and copilot. I have found that for the mundane, simple, common patterns copilot’s accuracy is close to 9/10 correct, especially in my well maintained repos.

    It seems like the accuracy of simple answers is directly proportional to the precision of my function and variable names.

    I haven’t typed a full for loop in a year thanks to copilot, I treat it like an intent autocomplete.

    Chatgpt on the other hand is remarkably useful for super well laid out questions, again with extreme precision in the terms you lay out. It has helped me in greenfield development with unique and insightful methodologies to accomplish tasks that would normally require extensive documentation searching.

    Anyone who claims llms are a nothingburger is frankly wrong, with the right guidance my output has increased dramatically and my error rate has dropped slightly. I used to be able to put out about 1000 quality lines of change in a day (a poor metric, but a useful one) and my output has expanded to at least double that using the tools we have today.

    Are LLMs miraculous? No, but they are incredibly powerful tools in the right hands.

    Don’t throw out the baby with the bathwater.