• 3 Posts
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Joined 3 months ago
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Cake day: June 4th, 2025

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  • AnarchoEngineer@lemmy.dbzer0.comto196@lemmy.blahaj.zonerule
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    8 hours ago

    You’re 100% right, unfortunately my brain doesn’t connect the feeling better to the eating vegetables and I totally forget I bought them by day 2 and then end up throwing away rotting vegetables a week later.

    But I did just buy a mini fridge so hopefully keeping food nearby will remind me it exists and my brain won’t be able to use the excuses of “it’s so far away” or “you might have to interact with people in the kitchen or on your way”



  • AnarchoEngineer@lemmy.dbzer0.comto196@lemmy.blahaj.zonerule
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    8 hours ago

    Bruh my meals, if I remember to eat anything, are basically just a protein shake and a cheese stick. Every day. Or occasionally just chocolate chips and milk because it’s fast and tastes good enough I can eat it even if my body doesn’t want to eat.

    If I had the motivation to buy and cook a frozen pizza for an actual dinner, I’d feel like I’d been cured of mental illness lol


    Edit: To alleviate any concerns, I’m well aware of the health detriment. This is the worst I’ve been in a while, but I am working on it.

    Also thank you to the comments because just remembering this post made me remember to eat food rn lol. I’m eating some fruit now and am going to make some ramen with carrots and an egg later (totally forgot I had carrots lol)

    In case anyone else reading this is like me this is your reminder to eat food today; do it now before you forget again


  • Large language models are designed to generate text based on previous text. Translation from audio to text can be done via a neural net but it isn’t a Large Language Model.

    Now, could you combine the two to say reduce error on words that were mumbled by having a generative model predict the words that would fit better in that unclear sentence. However you could likely get away with a much smaller and faster net than an LLM in fact you might be able to get away with using plain-Jane markov chains, no machine learning necessary.

    Point is that there is a difference between LLMs and other neural nets that produce text.

    In the case of audio to text translation, using an LLM would be very inefficient and slow (possibly to the point it isn’t able to keep up with the audio at all), and using a very basic text generation net or even just a probabilistic algorithm would likely do the job just fine.















  • Well considering the main creation story in other nearby cultures at the time also say the world was originally all water, I’d imagine it isn’t so much symbolism as it is the fact that water falls from the sky occasionally and typically looks blue.

    The Enūma Eliš mentions that originally there was just water. Much like the creation story in Genesis the gods eventually separate the waters and expose land. Also curiously, the story is recorded across seven tablets and has a few more similarities with Genesis and other aspects of Judaism like man being a fallen creature (though due to man being made from the corpse of an evil god or because the gods were worried, not due to women lol)

    Also, the oldest creation story I’m aware of is The Sumerian Creation Myth which also references the “cosmic freshwater ocean” and says man lives in the lower region of this ocean. The noise of humanity annoys the main god so he sends the flood from the upper ocean. But one god warns a man of this so the man builds a boat and fills it with animals. Remind you of any bible story?

    Point is that even the Torah is a likely derivative work combining more ancient myths from other cultures. Because the original cultures reference the waters more as an actual physical ocean in a non-symbolic way, Id say the Bible story was meant to be literal. Almost all symbolism derived from the stories therein is likely interpretation only.

    I suppose the Hebrew scholars collecting these stories could have viewed them in a more symbolic way, but the first text I referenced is a few years younger than the Torah and still references oceans in a more physical way. So, I’d imagine their meanings were initially similar.