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Joined 2 years ago
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Cake day: June 25th, 2023

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  • The issue with Lua’s and/or in this context is that they don’t work if false or nil are valid values. In a and b or c, if b = false, the result is always c.

    I also love null-related operators like ?? and ?. for this, since they explicitly check for null, letting you handle any non-null values for optional/default values. The syntax can get a bit cursed, like maybeNull?.maybeMethod?.(args) in JS, but I still prefer that to writing out multiple field accesses in an if condition… And arguably the code is only less readable if you aren’t acclimated to it.

    All that said I do really appreciate Lua’s simplicity, as a language that provides tooling to create the features you want instead of building them into the language, though I wish it had some conventional regex instead of its own patterns.



  • That actually sounds like a fun SCP - a word that doesn’t seem to contain a letter, but when testing for the presence of that letter using an algorithm that exclusively checks for that presence, it reports the letter is indeed present. Any attempt to check where in the word the letter is, or to get a list of all letters in that word, spuriously fail. Containment could be fun, probably involving amnestics and widespread societal influence, I also wonder if they could create an algorithm for checking letter presence that can be performed by hand without leaking any other information to the person performing it, reproducing the anomaly without computers.




  • If the password is securely hashed, and the attack only includes data exfiltration, then there’s theoretically no risk of breaking into users’ accounts anyways. However, the issue is that if somebody can log into your Plex account, that means they got your password somehow - and if they did get that password, they can use it elsewhere. So if there’s any reason to change your password on Plex, then there’s just as much reason to change that same password elsewhere.




  • I really hope not, that feels like crypto all over again, with inconsistent payouts and varying electricity prices… And on top of that probably awful service since people tend to have the weirdest internet connections.

    Though if you remove the part where it’s used to stream games to other players, that sounds too niche to be viable, but could be cool. If going in that direction, I’d imagine it more likely to be gaming servers for businesses, like VR gaming spots, where they have multiple gaming computers hooked up to headsets.


  • I will point out that it generally takes more effort to make one sandwich, than it takes to make one sandwich out of a hundred. Getting fresh bread and (fresh?) spiced mayo is extra work that you only need to do once per multiple sandwiches, but it doesn’t really get easier when only making one.

    All I’m saying is, enjoy things made by specialized professionals, economies of scale mean that it’s more efficient for one person to make sandwiches for their surroundings anyways!



  • Apertus was developed with due consideration to Swiss data protection laws, Swiss copyright laws, and the transparency obligations under the EU AI Act. Particular attention has been paid to data integrity and ethical standards: the training corpus builds only on data which is publicly available. It is filtered to respect machine-readable opt-out requests from websites, even retroactively, and to remove personal data, and other undesired content before training begins.

    We probably won’t get better, but sounds like it’s still being trained on scraped data unless you explicitly opt out, including anything that may be getting mirrored by third parties that don’t opt out. Also, they can remove data from the training material retroactively… But presumably won’t be retraining the model from scratch, which means it will still have that in their weights, and the official weights will still have a potential advantage on models trained later on their training data.

    From the license:

    SNAI will regularly provide a file with hash values for download which you can apply as an output filter to your use of our Apertus LLM. The file reflects data protection deletion requests which have been addressed to SNAI as the developer of the Apertus LLM. It allows you to remove Personal Data contained in the model output.

    Oof, so they’re basically passing on data protection deletion requests to the users and telling them all to respectfully account for them.

    They also claim “open data”, but I’m having trouble finding the actual training data, only the “Training data reconstruction scripts”…






  • I think I was using an NVidia GPU up until about 3 years ago, when I switched to AMD when upgrading, so my knowledge on that front is a bit outdated.

    The arch wiki has more information if you’re curious, but I’m aware of official proprietary drivers, official partially opensourced drivers, separately packaged legacy drivers, and the unofficial opensource Nouveau drivers which weren’t really usable back then.

    What you’re describing sounds odd to me, but looking it up, sounds like Fedora doesn’t package official drivers? I’m having trouble finding proper information on this, but it could be for ideological reasons, since those drivers are proprietary - so the default drivers might be Nouveau, which might be rather broken, both because of lack of workforce and NVidia blocking unofficial drivers from using their devices properly.

    If that’s the case, it’s basically a conflict between ideology and usability within that distribution - it might seem like a great distro for users, and it might be competently made, but when somebody doesn’t care about the ideology and just wants their device to work, they’ll end up with confusion and work to do.