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  • AdrianTheFrog@lemmy.worldto196@lemmy.blahaj.zoneCollapse rule
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    2 hours ago

    Yes, and webp lossless is really good. JXL lossless is usually better, but either are better than png.

    Random high quality jpeg I found of a screenshot of sheet music:

    Original: 53.3 kb

    JXL: 12.2 kb

    Webp: 25.9 kb

    AVIF: 22.6 kb

    PNG: 47.3 kb

    Most are not anywhere near as favorable, that happened to be the most recent thing in my camera roll. Let me try another:

    Original PNG: 19.0 kb

    JXL: 12.9 kb

    Webp: 15.7 kb

    AVIF: 14.9 kb

    Finally, some larger and photographic content:

    Original PNG: 318 kb

    JXL: 185 kb

    Webp: 247 kb

    AVIF: 201 kb

    Encoder efforts picked to be the highest that would finish in within a few seconds in Image Toolbox on my phone. Webp doesn’t go up as high so it was finishing quicker here, and PNG doesn’t have varying effort afaik

    BTW JXL effort 1 lossless is insanely fast to encode (the order of a gigapixel per second) and also basically always smaller than PNG
















  • Sure, I could definitely see situations where it would be useful, but I’m fairly confident that no current games are doing that. First of all, it is a whole lot easier said than done to get real-world data for that type of thing. Even if you manage to find a dataset with positions of various features across various biomes and train an AI model on that, in 99% of cases it will still take a whole lot more development time and probably be a whole lot less flexible than manually setting up rulesets, blending different noise maps, having artists scatter objects in an area, etc. It will probably also have problems generating unusual terrain types, which is a problem if the game is set in a fantasy world with terrain that is unlike what you would find in the real world. So then, you’d need artists to come up with a whole lot of datat to train the model with, when they could just be making the terrain directly. I’m sure Google DeepMind or Meta AI whatever or some team of university researchers could come up with a way to do ai terrain generation very well, but game studios are not typically connected to those sorts of people, even if they technically are under the same company of Microsoft or Meta.

    You can get very far with conventional procedural generation techniques, hydraulic erosion, climate simulation, maybe even a model of an ecosystem. And all of those things together would probably still be much more approvable for a game studio than some sort of machine learning landscape prediction.