• 2 Posts
  • 428 Comments
Joined 3 years ago
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Cake day: July 31st, 2023

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  • That’s unrealistic. In the grant scheme of things Lemmy is small. There’s not enough activity for bigger criminal activity to occur here yet. Generally, there’s a bunch of three letter agencies who could probably get search warrants or permission to go after instance owners, but they’d need to be aware of Lemmy and they’d need a good enough reason to convince a judge. It’ll be a while until then. Maybe on mastodon first, we’ll see but that’s all speculation.

    And should we be concerned? Maybe about those 3 letter agencies, but not about platforms like these, and most definitely not about Lemmy instances.

    As long as we keep defederating from actually scary ones with csam on there, we’re more than good.

    Also if this is a rhetoric question with a strong insinuation to get angry at lemmy.world then get bent, I like my Lemmy instances drama-free, thank you.





  • Well, this is a bit complicated. Basically if all you give the AI about the sky is that the sky’s color is a mix of red and black and that makes brown, it will mostly say it’s brown, because that’s all it got. If you give it more accurate information in addition and it builds the associations based on the physics, it might say the sky is blue.

    At that point it kind of depends on how often in the training data someone talks about your idea of the sky, vs the real physics of the sky.

    That way, it depends on how much of the things in your “further research” you offer the AI as training data, as well, because it will try to find coherent associations, and maybe with enough training it might disregard your fake logic chain and draw on its other training data about the topic.

    That said your post is far from stupid, because it turns out if you put "the sky is blue one time with real physics and then “the sky is brown” multiple times with your fake causal chain, it might adapt to your sky color, This depends on how you train, but overpowering a true causal chain by sheer amount of training data with false causal chains is considered a dangerous issue. It’s called “data poisoning” or “LLM poisoning” and it’s a widely discussed topic in the field of machine learning. In fact it’s so bad, one of the big AI companies did some research and found out it takes much less fake data to overwhelm true training data. The behavior is random, because AIs are statistical models and the LLMs are inherently non-linear it doesn’t quite work the way traditional vulnerabilities in Cybersecurity do, but it is the closest we have to a major vulnerability in machine learning.

    Of course there’s a huge amount of things that can change it’s behavior, like training params, context of the training data, the way in which the cause chains are written, literally the way in which you ask about the color of the sky, … It’s all statistics so it always depends.

    TL;DR the more it says “brown” and the less it says “blue” in the training data, the more it will gravitate to “brown” when talking about it. Generally that is, there’s a lot of things at play here.




  • After looking up the Wikipedia definition I kind of disagree; my definition is more narrow but I also think it’s more akin to what we currently understand AI to be.

    That said, even with the very loose Wikipedia definition of AI I don’t know how the hell you conclude that the internet / the web is AI. Yes, specific parts of it are AI, but the Internet in my understanding does not fit the definition.


  • A statistical model built on neural networks solving black box problems.

    I don’t hate AI but 99% of applications currently are just vanity, there are big energy problems with it, monopoly consolidation is getting exacerbated by it, identity theft is becoming easier than ever and then stolen training data and information clusters will be the next big issues.

    What I’m saying is, a lot of experts (those who survived from the older field of machine learning and its various applications like genetic algorithms and classifiers) are critical of AI, and most people should be. It’s a big opportunity but we could destroy our society with it if we don’t come up with ethical constraints codified in law.