The catarrhine who invented a perpetual motion machine, by dreaming at night and devouring its own dreams through the day.

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Joined 8 months ago
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Cake day: January 12th, 2024

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  • But there’s enough of a problem you can see even if you just start at Julius, which is what I was concentrating on in my previous comment. The parallels to Trump are terrifyingly on the nose.

    True that.

    Weirdly enough (or perhaps not surprisingly) I see the same here with Bolsonaro supporters; there’s a disproportionally high amount of them among classicists, even if humanities as a whole leans heavily to the left.


  • The alt right obsesses over the Roman empire, but ignores the republic, as if Julius Caesar and Octavius were the origin of everything. As such I’m not surprised that they don’t learn about what caused the fall of the republic. (A century or so of oppressed masses and greedy elites did it.)

    And, even when it comes to the empire, they’re busier cherry-picking examples that show that the grass was greener, the men were manlier, the women were chaster, and dogs barked quieter.


  • At least when it comes to languages, the eurocentrism and subjectivity are being addressed for at least a century. Sapir for example proposed that the “classical languages” weren’t just two but five - Arabic, Chinese, Greek, Latin, Sanskrit. And the definition became roughly “varieties with a heavy and outlasting impact outside their native communities”. (Personally I’d also add Sumerian, Quechua and Nahuatl to that list. But that’s just me.)

    Additionally plenty linguists see the idea of “classic” not as specific languages, but as a potential stage of a language, assigned retroactively to the period when its prestige and cultural production were specially strong. For example, Classical Ge’ez is defined as the one from centuries XIII~XIV.




  • Really my point is there are enough things to criticize about LLMs and people’s use of them, this seems like a really silly one to try and push.

    The comment that you’re replying to is fairly specifically criticising the usage of the word “hallucination” to misrepresent the nature of the undesirable LLM output, in the context of people selling you stuff by what it is not.

    It is not “pushing” another “thing to criticise about LLMs”. OK? I have my fair share of criticism against LLMs themselves, but that is not what I’m doing right now.

    Continuing (and torturing) that analogy, […] max_int or small buffers.

    When we extend analogies they often break in the process. That’s the case here.

    Originally the analogy works because it shows a phony selling a product by what it is not. By making the phony to precompute 4*10¹² equations (a completely unrealistic situation), he stops being a phony to become a muppet doing things the hard way.

    If it were the case that there had only been one case of a hallucination with LLMs, I think we could pretty safely call that a malfunction

    If it happens 0.000001% of the time, I think we could still call it a malfunction and that it performs better than a lot of software.

    Emphases mine. Those “ifs” represent a completely unrealistic situation, that does not show anything useful about the real situation.

    We know that LLMs output “hallucinations” way more than just once, or 0.000001% of the time. They’re common enough to show you how LLMs work.



  • I did read the paper fully, but I’m going to comment mostly based on the challenged that the OP refers to.

    My belief is that the article is accurate on highlighting that the Fediverse on its own is not enough to reclaim the internet. However, it’s still a step in the right direction and should be nurtured as such.

    Discoverability as there is no central or unified index

    Yes, discovery is harder within a federated platform than a centralised one. However the indices that we use don’t need to be “central” or “unified” - it’s completely fine if they’re decentralised and brought up by third parties, as long as people know about them.

    Like Lemmy Explorer for example; it’s neither “central” nor “unified”, it’s simply a tool made by a third party, and yet it solves the issue nicely.

    Complicated moderation efforts due to its decentralized nature

    This implicit idea, that moderation efforts should be co-ordinated across a whole platform, quickly leads to unsatisfied people - either because they don’t feel safe or because they don’t feel like they can say what they think. Or both.

    Let us not fool ourselves by falsely believing that moderation always boils down to “remove CSAM and Nazi” (i.e. “remove things that decent people universally consider as bad”). Different communities want to be moderated in different, sometimes mutually exclusive, ways. And that leads to decentralised moderation efforts.

    In other words: “this is not a bug, this is a feature.”

    [Note: the above is not an endorsement of Lemmy’s blatant lack of mod tools.]

    Interoperability between instances of different types (e.g., Lemmy and Funkwhale)

    Because yeah, the interoperability between Twitter, YouTube and Reddit is certainly better. /s

    I’m being cheeky to highlight that, as problematic that the interoperability between instances of different types might be in the Fediverse, it’s still something that you don’t typically see in traditional media.

    Concentration on a small number of large instances

    Yes, user concentration into a few instances is a problem, as it gives the instance admins too much power. However, there’s considerably less room for those admins to act in a user-hostile way, before users pack their stuff up and migrate - because the cost of switching federated instances is smaller than the cost of switching non-federated platforms.

    The risk of commercial capture by Big Tech

    Besides what I said above, on the concentration of users, consider the fact that plenty Fediverse instances defederated Threads. What is this, if not the usage of the Fediverse features to resist commercial capture?


  • It gets worse, when you remember that there’s no dividing line between harmful and healthy content. Some content is always harmful, some is by default healthy, but there’s a huge gradient of content that needs to be consumed in small amounts - not doing it leads to alienation, and doing it too much leads to a cruel worldview.

    This is doubly true when dealing with kids and adolescents. They need to know about the world, and that includes the nasty bits; but their worldviews are so malleable that, if all you show them is nasty bits, they normalise it inside their heads.

    It’s all about temperance. And yet temperance is exactly the opposite of what those self-reinforcing algorithms do. If you engage too much with content showing nasty shit, the algo won’t show you cats being derps to “balance things out”. No, it’ll show you even more nasty shit.

    It gets worse due to profiling, mentioned in the text. Splitting people into groups to dictate what they’re supposed to see leads to the creation of extremism.


    In the light of the above, I think that both Kaung and Cai are missing the point.

    Kaung believes that children+teens would be better if they stopped using smartphones; sorry but that’s stupid, it’s proposing to throw the baby out with the dirty bathtub water.

    Cai on the other hand is proposing nothing but a band-aid. We don’t need companies to listen to teens to decide what we should be seeing; we need them to stop altogether deciding what teens and everyone else should be seeing.

    Ah, and about porn, mentioned on the text: porn is at best a small example of a bigger issue, if not a red herring distracting people from the issue altogether.



  • When it comes to the code itself you’re right, there’s no difference between “bug” and “not a bug”. The difference is how humans classify the behaviour.

    And yet there’s a clear mismatch between what the developers of those large “language” models know that they’re able to do, versus what LLMs are being promoted for, and that difference is what is being called “hallucination”. They are not intelligent systems, the info that they output is not reliably accurate, it’s often useless rubbish. But instead of acknowledging it they label it “hallucination”.

    Perhaps an example would be good here. Suppose that I made a text editor; it works nicely as a text editor and nothing much else. Then I make it automatically find and replace the string “=2+2” with “4”, and use it to showcase my text editor as if it was a calculator. “Look, it can do maths!”.

    Then the user types down “=3+3”, expecting the “calculator” to output “6”, and it doesn’t. Can we really claim that the user found a “bug”? Not really. It’s just that I’m a phony and I sold him a text editor as if it was a calculator.

    And yet that’s exactly what happens with LLMs.


  • This article shows rather well three reasons why I don’t like the term “hallucination”, when it comes to LLM output.

    1. It’s a catch-all term that describes neither the nature nor the gravity of the problematic output. Failure to address the prompt? False output, fake info? Immoral and/or harmful output? Pasting verbatim training data? Output that is supposed to be moderated against? It’s all “hallucination”.
    2. It implies that, under the hood, the LLM is “malfunctioning”. It is not - it’s doing what it is supposed to do, to chain tokens through weighted probabilities. Contrariwise to the tech bros’ wishful belief, LLMs do not pick words based on the truth value or morality of the output. That’s why hallucinations won’t go away, at least not for the current architecture of text generators.
    3. It lumps together those incorrect outputs with what humans would generate on situations of poor reasoning. This “it works like a human” metaphor obscures what happens, instead of clarifying it.

    On the main topic of the article. Are LLMs useful? Sure! I use them myself. However only a fool would try to shove LLMs everywhere, with no regards to how intrinsically [yes] unsafe they are. And yet it’s what big tech is doing, regardless of being Chinese or United-Statian or Russian or German or whatever.


  • The video is great. A shame that it’s getting downvoted.

    In fiction there’s the concept of suspension of disbelief. Wikipedia describes it better than I could, but to keep it short - when you’re reading/watching/etc. a fictional story, you avoid applying your critical thinking and logic reasoning to certain story elements, in order to enjoy it.

    I feel like a similar but not identical principle operates with game mechanics. I’ll call it here suspension of scepticism. That suspension of scepticism makes you willing to trust that the information provided or implied by the game about itself is factual, accurate, and relevant.

    For example, if it shows you a six-sided die, you treat it as a fair die, and you treat your odds of getting a 1 the same as getting a 6, a 5, or any other number. You won’t save the game, throw the die a hundred times, and see if it’s actually fair or not.

    Those “design lies” use that suspension of scepticism to deliver a better experience. And it works - for the reason mentioned in the video, it makes playing more enjoyable.

    However just like the suspension of disbelief can be broken, so does the suspension of scepticism. It’s OK if the game designer is a liar, but he must be a good liar; if you lie too often or too obviously, the player will smell the lie from afar, and the suspension of scepticism is broken. And with it, the enjoyment of the game goes down the drain.


  • That’s a good text. I’ve been comparing those “LLM smurt!” crowds with Christian evangelists, due to their common usage of fallacies like inversion of burden of proof, changing goalposts, straw man, etc.

    However it seems that people who believe in psychics might be a more accurate comparison.

    That said LLMs are great tools to retrieve info when you aren’t too concerned about accuracy, or when you can check the accuracy yourself. For example the ChatGPT output of prompts like

    • “Give me a few [language] words that can be used to translate the [language] word [word]”
    • “[Decline|Conjugate] the [language] word [word]”
    • “Spell-proof the following sentence: [sentence]”

    is really good. I’m still concerned about the sheer inefficiency of the process though, energy-wise.





  • Choosing weaker forms sounds sensible - my criticism is which ones.

    Many people react that way but think about it a little more. It’s a fact. Mutliuple Black people have proven it repeatedly.

    Yup, I know that it’s a fact. You aren’t being fallacious, but the way that you phrased it sounds like that fallacy, so it’s a matter of clarity.

    It’s the same deal as the “post less”, you know? People are misunderstanding you.

    [from the other comment] That’s a great point, can I quote you on having seen it on Lemmy quite a few times?

    Feel free to do so! However keep in mind that I didn’t really keep track of them, so if someone says “do you have proofs?” I have no way to back it up.