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Cake day: June 23rd, 2024

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  • Of course. You need about 1 hair per 2x2 pixels on a 1080p screen and 4x4 on a 4K screen. That totals about 10,000 hairs per icon in the simulation, which can be precomputed into animations. Third-party icons will be 2D (or 2.5D if the FG/BG layer of the icon is handled separately, doubling the animation data). Now it’s “just” a matter of drawing 10,000-20,000 lines with precomputed shading and textures from the icon’s 100x100 bitmap render.

    Also, the GPU is only used by apps while they’re in the foreground, so the launcher might be able to use all of its power. And it could cache animations for existing icons (who cares if the system uses 32 GB of storage? Buy the higher option, peasant!)










  • Being FOSS is not a prerequisite of E2EE but a prerequisite of knowing it’s E2EE for sure. Like, I can give you a black box that prints PGP key pairs and says “includes RPGP, MIT-licensed PGP library” but you can’t trust that the machine doesn’t use modified, low-entropy RNG or exfiltrate the results. The communication you do with these PGP keys is technically E2EE − a third party server relaying your messages will not be able to read them, unless I provide them with the potentially not-so-secret “random” data my box generated.

    But you’re right: if my black boxes are also used to encrypt/decrypt the messages with “your” keys (made by them) and I run a non-transparent ssrvice that delivers the messages, there is a case for not calling it E2EE.




  • To be fair, we don’t have any pics of exoplanets. Technically, we could measure their surface temperature and basic chemistry through spectroscoopy but I don’t think they reflect enough photons for our equipment. They are usually identified by dimming their star slightly when passing in front of it. This can give an estimated size and distance from their star. And maybe atmosphere composition if it refracts! So they’re not naming this kind of picture but a bunch of data with big error bars.






  • ChaoticNeutralCzech@feddit.orgtoProgrammer Humor@programming.devLavalamp too hot
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    5 days ago

    Nah, too cold. It stopped moving and the computer can’t generate any more random numbers to pick from the LLM’s weighted suggestions. Similarly, some LLMs have a setting called “heat”: too cold and the output is repetitive, unimaginative and overly copying input (like sentences written by first autocomplete suggestions), too hot and it is chaos: 98% nonsense, 1% repeat of input, 1% something useful.