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Joined 2 years ago
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Cake day: June 15th, 2023

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  • Matrix is notorious for its poor performance with large/numerous groups. They keep claiming to improve it, but it’s still bad.

    I mean, it’s great that it works for you, but be honest: isn’t your tolerance for technological friction a bit higher than the average bear’s? People complain that Mastodon is too hard, and Matrix is ten times worse to sign up for and use.

    I hate to say it, but Matrix is never going to be mainstream. Its UX is bad and it seems like it’s too bloated to fix. If I tried to get people to move from Discord to Matrix, they’d never take me seriously again. It was hard enough getting people to move from Facebook Messenger to Signal.




  • I’ve been using cryptpad.fr (the “flagship instance” of CryptPad) for years. It’s…fine. Really, it’s fine. I’m not thrilled with the experience, but it is functional and I’m not aware of any viable alternatives that are end-to-end encrypted.

    It’s based on OnlyOffice, which is basically a heavyweight web-first Microsoft Office clone. Set your expectations accordingly.

    No mobile apps, and the web UI is not optimized for mobile. I mean, it works, but does using the desktop MS Office UI on a smartphone sound like fun to you?

    Performance is tolerable but if you’re used to Google Sheets, it’s a big downgrade. Some of this is just the necessary overhead involved in an end-to-end encrypted cloud service. Some of it is because, again, this is a heavyweight desktop UI running in a web browser. It’s functional, but it’s not fast and it’s not pretty.




  • DNS over HTTPS. It allows encrypted DNS lookup with a URL, which allows for url-based customizations not possible with traditional DNS lookups (e.g. the server could have /ads or /trackers endpoints so you can choose what to block).

    DNS Over TLS (DoT) is similar, but it doesn’t use URLs, just IP addresses like generic DNS. Both are encrypted.



  • Honestly, that sounds great.

    My biggest problem with Flatpak is that Flathub has all sorts of weird crap, and depending on your UI it’s not always easy to tell what’s official and what’s just from some rando. I don’t want a repo full of “unverified” packages to be a first-class citizen in my distro.

    Distros can and should curate packages. That’s half the point of a distro.

    And yes, the idea of packaging dependencies in their own isolated container per-app comes with real downsides: I can’t simply patch a library once at the system level.

    I’m running a Fedora derivative and I wasn’t even aware of this option. I’m going to look into it now because it sounds better than Flathub.




  • In my experience, this is more a problem if you are fully running your own mail servers, not so much if you are using an established email service. My MX record reflects my email provider, and my outgoing mail goes through their servers. So I’m as trusted as they are, in general. Your mail provider should have instructions on how to set up DNS for verification.


  • If you’re willing to pay money for it, you can get your own domain for $2-$15 per year, then use it with pretty much any commercial email service. That way you can change email providers without changing your address.

    This is my plan going forward. I’m going to suffer the inconvenience of changing my address, but only one more time, not every time I want to change providers.




  • I’m not entirely sure how I need to effectively use these models, I guess. I tried some basic coding prompts, and the results were very bad. Using R1 Distill Qwen 32B, 4-bit quant.

    The first answer had incorrect, non-runnable syntax. I was able to get it to fix that after multiple followup prompts, but I was NOT able to get it to fix the bugs. It took several minutes of thinking time for each prompt, and gave me worse answers than the stock Qwen model.

    For comparison, GPT 4o and Claude Sonnet 3.5 gave me code that would at least run on the first shot. 4o’s was even functional in one shot (Sonnet’s was close but had bugs). And that took just a few seconds instead of 10+ minutes.

    Looking over its chain of thought, it seems to get caught in circles, just stating the same points again and again.

    Not sure exactly what the use case is for this. For coding, it seems worse than useless.


  • But any 50 watt chip will get absolutely destroyed by a 500 watt gpu

    If you are memory-bound (and since OP’s talking about 192GB, it’s pretty safe to assume they are), then it’s hard to make a direct comparison here.

    You’d need 8 high-end consumer GPUs to get 192GB. Not only is that insanely expensive to buy and run, but you won’t even be able to support it on a standard residential electrical circuit, or any consumer-level motherboard. Even 4 GPUs (which would be great for 70B models) would cost more than a Mac.

    The speed advantage you get from discrete GPUs rapidly disappears as your memory requirements exceed VRAM capacity. Partial offloading to GPU is better than nothing, but if we’re talking about standard PC hardware, it’s not going to be as fast as Apple Silicon for anything that requires a lot of memory.

    This might change in the near future as AMD and Intel catch up to Apple Silicon in terms of memory bandwidth and integrated NPU performance. Then you can sidestep the Apple tax, and perhaps you will be able to pair a discrete GPU and get a meaningful performance boost even with larger models.