@gnuntoo @fisherdude If you're talking about GTK4 apps, run them with MESA_GLES_VERSION_OVERRIDE=3.0, otherwise you'll have them use GL through llvmpipe.

@pankraz @maryjane @janvlug At least PureOS uses it by default for providing cellular- and Wi-Fi-based location. Data collection can be configured in Geoclue config, or done through geoclue-stumbler app: gitlab.com/kop316/geoclue-stum

@rysiek @mkljczk Yeah, I totally get that. I just wanted to react to hand-waving it as just your usual FLOSS infighting, bad communication, overpassionate nerds being overpassionate nerds etc. as that's very much not what it is.

This is why GiovanH's blog article is a must-read.

People assume that accessible hacks of invasive systems will always exist, and users hacking their devices is to be expected.

THIS SHOULDN'T BE A NORM. THIS IS AN ARMS RACE AND WE'RE OUTMATCHED. /7

blog.giovanh.com/blog/2025/10/

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@rysiek @mkljczk So has the one I do, it gets tons of flak, but it hits somewhat different when it's not some random confused "fan" but the main face behind a well-known project that threatens you personally to hamper your professional carrier just because they didn't like getting their bullshit corrected.

And I wouldn't bother to reply if it was just about me. It's an established pattern.

@rysiek @mkljczk Well, obviously, you haven't been on the receiving end of that.

@rysiek @mkljczk In this particular case it really goes much further than just "shit-slinging between projects".

@mkljczk @rysiek Yeah, there's a reason I have their accounts blocked everywhere 🙃

@rogatywieszcz Kopia z 2024 pliku zmodyfikowanego w 2021?

Każdą z tych dat można edytować, manipulują nimi różne narzędzia, przechowują je też archiwa.

@elly Frankly, if I wanted to switch to Android I'd probably have many of the same problems with adjusting that people switching the other way tend to have.

@elly 2008 happens to be exactly when I started using GNU/Linux on my phone and never stopped 😁 I changed my phone twice since (not counting replacing units of the same models), though I always used ones where WiFi, audio and (eventually) cameras have worked fine (well, except the first one, there was physically no camera there 😄)

a decade or so ago, I was writing a H.264 decoder (needed a custom one for stupid reasons which of course had to do with hardware reverse engineering).

the first order of business was to implement CABAC: the final entropy coding stage of H.264 (ie. the first layer I had to peel starting from the bitstream), a funny variant of arithmetic coding. the whole thing is quite carefully optimize to squeeze out bits from video frames by exploiting statistics. in addition to carefully implementing the delicate core logic, I also had to copy-paste a few huge probability tables from the PDF, which of course resisted copy-paste as PDFs like to do and I had to apply some violence until it became proper static initializers in C source code.

furthermore, testing such code is non-trivial: the input is, of course, completely random-looking bits. and the way bitstreams work, I’d have to implement pretty much the whole thing before I got to the interesting part.

so, a few hours later, I figured I’m done with CABAC and reconstructing H.264 data structures, and pointed my new tool at some random test videos. and it worked first try! the structures my program spit out looked pretty much as expected, the transform coefficient matrices had pretty shapes and looked just as you’d expect them to, and I was quite happy with that.

and then I moved on to actually decoding the picture from the coefficients, and this time absolutely nothing worked. random garbage on screen. I spent a long time looking at my 2D transform code searching for bugs, but couldn’t find anything.

and then it hit me exactly what “entropy coding” means. I implemented something that intimately knows and exploits the statistical properties of what video transform coefficients and other structures look like, their probabilities and internal correlations, and uses that to squeeze out entropy and reconstruct it on the other end. my “looks good” testing meant absolute jack shit: I could’ve thrown /dev/urandom into the CABAC decoder instead of actual H.264 video, and it would still look like good video data at this stage until you actually tried to reconstruct the picture.

and sure enough, it turned out I fucked up transcribing some rows from the PDF around a page break or something.

10 years later, I think of this experience every time I see a vibecoded pull request, or other manifestation of AI bullshit. all the right shape, and no substance behind it.

and people really should learn to tell the fucking difference.

@ron The real work happens in the 😼, the ⌨️ only follows on afterwards

I couldn't make any sense out of these logs so I yielded to a developer higher in seniority who is now carefully analyzing the issue.

This is a real time recording of my git server's web access logs. It's a constant stream of requests from "Claude" attempting to access every possible item on the site.

A couple of months ago, I set up a rule to return an error code for every request its user agent makes. It has not retrieved a single valid item for many, many weeks at this point. Every request is immediately and abruptly terminated.

It hasn't even slowed down as a result.

Tell me again how their operation involves "intelligence" of any kind.

:psyduck:

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