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Joined 11 months ago
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Cake day: July 31st, 2023

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  • What you are proposing may seem nice, but any ethics committee would shut this down instantly, anywhere in the world.

    But let’s imagine we can do this, somehow, and that all the ethical issues are resolved. Harvard might be able to grow their “thing”, or order it from some specialized company; how do you not condemn all research in developing countries?


  • The thing is, new chemical compounds are being developed all the time for all kinds of applications. What you’re saying is not really “we should let sick people die rather that try to get a cure”, horrible enough as it is, but rather “let’s dump whatever shit we come up in the environment without testing its effect first”, and while things are bad currently, there is no depth to how worse things could get if we didn’t even bother trying to prevent the worst from happening


  • This being your only option would be poverty, not an alternative to it. And highly dangerous jobs aren’t comparison here, testing drugs before animal testing is is no way a level of danger comparable to being a woodcutter

    Human testing is necessary, and while the disenfranchised are already subject to it, skipping animal testing and directly proceeding on the most vulnerable would be truly despicable.

    Furthermore, if the issue is consent, then this “solution” does not resolve it at all. What you get from subjecting poor people to the choice of cold & hunger or being a test subject is not consent, and once again minorities, disabled people, LGBT and women would be the primary victims


  • CommanderCloon@lemmy.mltoVegan@lemmy.mlHumans need to stop being cruel
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    1 month ago

    Ah, yes, testing drugs pre-animal trial on the poor and disenfranchised sound so much better, truly the end of a dystopia

    Edit: Not to mention, the meat industry produces despair of the same level while being entirely superfluous (something animal testing, unfortunately, is not) and on a scale which would be an ocean compared to the drop that is animal testing




  • Shorts fucking suck. It keeps recommending to me exactly four types of videos:

    • stuff I have already watched, liked and commented – sometimes a few minutes prior
    • videos I’m wildly uninterested with and systematically mark as irrelevant or instantly skip, yet it keeps bringing up videos of the same subject
    • very old old “news” shorts
    • stuff of people I’m subscribed to – which is fine, just not what makes great algorithms

    Meanwhile, in a very short time, tiktok has managed to make me discover communities I had no idea I’d like to watch content from, while subtly managing to stop showing me some of the content from those communities I don’t enjoy



  • I don’t know which kinds of AIs you’ve worked on but my description (although using the incorrect terms) is certainly valid. I’ve described how GANs work, I’m not pulling this out of thin air 🤷‍♂️

    The generative network generates candidates while the discriminative network evaluates them. The contest operates in terms of data distributions. Typically, the generative network learns to map from a latent space to a data distribution of interest, while the discriminative network distinguishes candidates produced by the generator from the true data distribution. The generative network’s training objective is to increase the error rate of the discriminative network (i.e., “fool” the discriminator network by producing novel candidates that the discriminator thinks are not synthesized (are part of the true data distribution)).

    Wikipedia

    So yes, whichever method you design which allows the product of an AI to be detected can be used by a discriminative network for a GAN, which defeats the purpose of designing the method to begin with


  • You don’t understand that tech; when making an AI model, you do code both a generator of whatever it is you want to make, as well as a “detector” which tells you whether or not the result is convincing.

    Then you change the genertor slightly based of the results of the “detector”

    You do that a few million times and then you have a correct AI model, the quality of which is dependant on both the quantity of training and the “detector”.

    If someone comes up with a really strong “detector”, they will do work as intended for a few days/weeks, and then AIs will come on the market which will be able to fool the detector