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Cake day: August 9th, 2023

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  • I actually had my most difficult time ever setting up Linux on my 5800X3D and 3070 recently.

    PopOS wouldn’t save my resolution on reboot, and then after fixing it all of my games were running at the wrong resolution or breaking in various frustrating ways. All Linux native games too. Jumped to Fedora and every single game flickered like mad and then once I got that fixed my package manager inexplicably broke. I was about to install Ubuntu before saying fuck any chance of instability and going to Debian.

    I had to manually install way more than any of the other distros, but everything just worked once I got my graphics driver installed. I was really disappointed given I’ve been using Linux on and off for 8 years, and my Steam Deck has been nothing but solid. I’m honestly just disappointed things have trended in a bad direction, and I hope this was just a one off experience and not the norm now.


  • Ask and ye shall receive

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  • Aggregate data doesn’t mean no client side data. It’s possible they’re collecting aggregate level client data too. They could go further and collect data on individuals that is not identifiable or useful to law enforcement in any way. I can think of a few ways to get anonymous usage data that allows you to improve your service while protecting your users. I don’t know their scheme but they clearly don’t need overly invasive forms of analytics as they have a solid service.



  • If you have the technical knowledge (or ability to follow instructions) you can setup your torrents behind a VPN using qBittorrent and gluetun in one docker container, and Plex/Jellyfin in another with a shared volume between them. It provides you near bullet proof protection due to the isolated environment and prevents accidentally clicking those .mp4.exes since it abstracts file management away from you. It’s also super user friendly once set up even if you’re not running a media server 24/7 and just want it for your desktop.

    If you wanna get fancy you can use the *arr suite of software to do some magic fairy shit including automatic indexing (searching dozens of torrent sites simultaneously), but that can quickly become a deep rabbit hole. Once setup though it’s seamless and kicks ass.







  • JDubbleu@programming.devtoComic Strips@lemmy.worldCall me 4chan
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    5 months ago

    Almost every personal computer that isn’t a MacBook is poorly secured due to the lack of filesystem encryption as a default. No one encrypts their data at rest, and as such you just have to pull their drive and read it with another computer. Hell, I don’t encrypt my entire file system despite being aware of this because of the inconvenience of added boot time, but everything that matters is encrypted and backed up across multiple devices.

    The best thing anyone can do is keep the amount of critical, digital data they have to a minimum, keep that data encrypted and backed up, and use a password manager properly. That alone makes it exceedingly unlikely you will ever be a victim of cybercrime solely because you’re more of a pain in the ass to compromise than 99.9% of the world.

    I personally have almost 10TB of data between all my systems, but of that maybe 10 MB is actually valuable to anyone but me.



  • That was a pretty interesting read. However, I think it’s attributing correlation and causation a little too strongly. The overall vibe of the article was that developers who use Copilot are writing worse code across the board. I don’t necessarily think this is the case for a few reasons.

    The first is that Copilot is just a tool and just like any tool it can easily be misused. It definitely makes programming accessible to people who it would not have been accessible to before. We have to keep in mind that it is allowing a lot of people who are very new to programming to make massive programs that they otherwise would not have been able to make. It’s also going to be relied on more heavily by those who are newer because it’s a more useful tool to them, but it will also allow them to learn more quickly.

    The second is that they use a graph with an unlabeled y-axis to show an increase in reverts, and then never mention any indication of whether it is raw lines of code or percentage of lines of code. This is a problem because copilot allows people to write a fuck ton more code. Like it legitimately makes me write at least 40% more. Any increase in revisions are simply a function of writing more code. I actually feel like it leads to me reverting a lesser percentage of lines of code because it forces me to reread the code that the AI outputs multiple times to ensure its validity.

    This ultimately comes down to the developer who’s using the AI. It shouldn’t be writing massive complex functions. It’s just an advanced, context-aware autocomplete that happens to save a ton of typing. Sure, you can let it run off and write massive parts of your code base, but that’s akin to hitting the next word suggestion on your phone keyboard a few dozen times and expecting something coherent.

    I don’t see it much differently than when high level languages first became a thing. The introduction of Python allowed a lot of people who would never have written code in their life to immediately jump in and be productive. They both provide accessibility to more people than the tools before them, and I don’t think that’s a bad thing even if there are some negative side effects. Besides, in anything that really matters there should be thorough code reviews and strict standards. If janky AI generated code is getting into production that is a process issue, not a tooling issue.



  • I mean if you have access but are not using Copilot at work you’re just slowing yourself down. It works extremely well for boilerplate/repetitive declarations.

    I’ve been working with third party APIs recently and have written some wrappers around them. Generally by the 3rd method it’s correctly autosuggesting the entire method given only a name, and I can point out mistakes in English or quickly fix them myself. It also makes working in languages I’m not familiar with way easier.

    AI for assistance in programming is one of the most productive uses for it.


  • Not OP, but my main preference for MacOS comes from the UI/UX of an absolute rock solid OS on top of a unix-like shell. I regularly go months without rebooting my machine with 0 issues like software hanging on wake.

    I know there are a lot of exclusive creative apps, but all I really use my MacBook for is code, typical browser stuff, music, slicer/web interface for my 3D printer, and to interact with my home server. I’m not an open-source/Linux purist by any means, but pretty much all the software I use is widely available on all platforms. It probably helps that I bought a MacBook after growing up with Windows/Linux, so I came into it with a set of software I was familiar with that already existed on other platforms.


  • This feels like when the Mighty Morphin’ Power Rangers combined to make the Megazord.

    I’m cautiously optimistic because despite their solution being simple in nature it will still take a fuck ton of work and community effort to get the proposed Protonfix DB going. With that said I have no doubt this will be awesome once it’s completed, and I cannot wait to try this out! Stuff like this makes me wish I was a systems/OS dev and not backend/API/cloud.