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Cake day: June 25th, 2023

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  • Because religion evolved to thrive in us.

    It’s like a parasite, and our mind is the host. It competes with other mind-parasites like other religions, or even scientific ideas. They compete for explanatory niches, for feeling relevant and important, and maybe most of all for attention.

    Religions evolved traits which support their survival. Because all the other variants which didn’t have these beneficial traits went extinct.

    Like religions who have the idea of being super-important, and that it’s necessary to spread your belief to others, are ‘somehow’ more spread out than religions who don’t convey that need.

    This thread is a nice collection of traits and techniques which religions have collected to support their survival.

    This perspective is based on what Dawkins called memetics. It’s funny that this idea is reciprocally just another mind-parasite, which attempted to replicate in this comment.



  • Spzi@lemm.eetoEurope@feddit.deFuck Facists, never again
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    6 months ago

    If we omit all the steps which aren’t key, we likely fail at key steps. Some steps are important support.

    Giving the people a way to show themselves what their spirit is is important to encourage further steps.

    In that sense, I do think keeping up morale was important in freeing France.







  • That’s kind of two of my main points:

    1. Treat your volunteers well, or why should they continue volunteering?
    2. Kernel maintainers have plenty of other opportunities.

    I don’t know if they are volunteering or being paid. The other person said they are being paid.

    Either way, no one deserves being talked down to like that, even if they made a mistake. It’s a matter of respect and self-respect. And as a skilled person like a kernel developer, it should be trivially easy to find other work in a more appropriate environment.

    That being said, maybe I’m missing something. Torvalds has been known to be like that for a long time (although that seems to be over now). And still, Linux has been developed over decades. So apparently, skilled people flocked around Torvalds, or maybe rather his project. Not entirely sure why, but I’m taking it as a hint I might be missing something.






  • Spzi@lemm.eetoProgramming@beehaw.orgFeeling overwhelmed
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    9 months ago

    Yes, I feel you.

    And yes, that’s how it is. It’s an insanely complex industry if you really want to understand how things work.

    Which you don’t need to get things done.

    Which you still can if you really want, if you’re willing to invest the time and energy to study it thoroughly for many years if not decades.

    But even then, chances are you’ll be touching libraries, concepts or technologies which you did not study in-depth yet. I think you need to be both aware and tolerant of limited knowledge, and willing to learn continuously.



  • Right, thanks for the corrections.

    In case of GAN, it’s stupidly simple why AI detection does not take off. It can only be half a cycle ahead (or behind), at any time.

    Better AI detectors train better AI generators. So while technically for a brief moment in time the advantage exists, the gap is immediately closed again by the other side; they train in tandem.

    This does not tell us anything about non-GAN though, I think. And most AI is not GAN, right?



  • And this is why AI detector software is probably impossible.

    What exactly is “this”?

    Just about everything we make computers do is something we’re also capable of; slower, yes, and probably less accurately or with some other downside, but we can do it. We at least know how.

    There are things computers can do better than humans, like memorizing, or precision (also both combined). For all the rest, while I agree in theory we could be on par, in practice it matters a lot that things happen in reality. There often is only a finite window to analyze and react and if you’re slower, it’s as good as if you knew nothing. Being good / being able to do something often means doing it in time.

    We can’t program software or train neutral networks to do something that we have no idea how to do.

    Machine learning does that. We don’t know how all these layers and neurons work, we could not build the network from scratch. We cannot engineer/build/create the correct weights, but we can approach them in training.

    Also look at Generative Adversarial Networks (GANs). The adversarial part is literally to train a network to detect bad AI generated output, and tweak the generative part based on that error to produce better output, rinse and repeat. Note this by definition includes a (specific) AI detector software, it requires it to work.