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Cake day: 2023年6月11日

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  • It’s “whataboutism” in the sense we’re interrogating focus. Why do you think white ethnonationalists spend so much time asserting “white lives matter?” Because there’s only so much air in the room, and they know giving air to one cause deprives another.

    I think it’s worth wondering why people spend so much time discussing Israel/Palestine and so little discussing other issues that are at least as large from a “people impacted” perspective. Obviously there’s also an African infantilization (that is to say, racist) double standard here — we simply don’t expect Africa to have human rights. But I would say there is certainly also an Israel double standard, and it is antisemitic in the same way saying “well of course Sierra Leone is a hellhole, there’s no news there” is racist.

    You are not a news outlet. But you choose what you’re spending your time and effort on. And it is this. I think many people don’t interrogate why they get so involved and what their opinions actually mean in terms of what their focus accomplished and what it broadcasts.

    I apologize for choosing you as the vehicle for this message; I don’t mean to attack you personally. There are a ton of people doing this and your message was as good as any other to demonstrate my point.








  • Veraticus@lib.lgbttoTechnology@lemmy.mlGPT-4 Understands
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    8 个月前

    The Anthropic one is saying they think they have a way to figure it out, but it hasn’t been tested on large models. This is their last paragraph:

    Again, all your quotes indicate that what they’ve figured out is a way to inspect the interior state of models and transform the vector space into something humans can understand without analyzing the output.

    I think your confusion is you believe that because we don’t know what the vector space is on the inside, we don’t know how AI works. But we actually do know how it accomplishes what it accomplishes. Simply because its interior is a black box doesn’t mean we don’t understand how we built that black box, or how it operates and functions.

    For an overview of how many different kinds of LLMs function, here’s a good paper: https://arxiv.org/pdf/2307.06435.pdf You’ll note that nowhere is there any confusion about the process of how they generate input or produce output. It is all extremely well-understood. You are correct that we cannot interrogate their internals, but that is also not what I mean, at least, when I say that we can understand them and how they work.

    I also can’t inspect the electrons moving through my computer’s CPU. Does that mean we don’t understand how computers work? Is there intelligence in there?

    I think you’re maybe having a hard time with using numbers to represent concepts. While a lot less abstract, we do this all the time in geometry. ((0, 0), (10, 0), (10, 10), (0, 10), (0, 0)) What’s that? It’s a square. Word vectors work differently but have the same outcome (albeit in a more abstract way).

    No, that is not my main objection. It is your anthropomorphization of data and LLMs – your claim that they “have intelligence.” From your initial post:

    But also, can you define what intelligence is? Are you sure it isn’t whatever LLMs are doing under the hood, deep in hidden layers?

    I think you’re getting caught up in trying to define what intelligence is; but I am simply stating what it is not. It is not a complex statistical model with no self-awareness, no semantic understanding, no ability to learn, no emotional or ethical dimensionality, no qualia…

    ((0, 0), (10, 0), (10, 10), (0, 10), (0, 0)) is a square to humans. This is the crux of the problem: it is not a “square” to a computer because a “square” is a human classification. Your thoughts about squares are not just more robust than GPT’s, they are a different kind of thing altogether. For GPT, a square is a token that it has been trained to use in a context-appropriate manner with no idea of what it represents. It lacks semantic understanding of squares. As do all computers.

    If you’re saying that intelligence and understanding is limited to the human mind, then please point to some non-religious literature that backs up your assertion.

    I’m disappointed that you’re asking me to prove a negative. The burden of proof is on you to show that GPT4 is actually intelligent. I don’t believe intelligence and understanding are for humans only; animals clearly show it too. But GPT4 does not.






  • Veraticus@lib.lgbttoTechnology@lemmy.mlGPT-4 Understands
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    8 个月前

    I was in this case – but the overall point I made is still correct. If winning this minor battle is what you were seeking, congratulations. You are no closer to understanding the truth of this or what we were actually talking about. Not that that was either your point or within your capabilities.


  • Veraticus@lib.lgbttoTechnology@lemmy.mlGPT-4 Understands
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    8 个月前

    I am upset: you don’t know what you’re talking about, refuse to listen to anything that contradicts you, and are inflammatory and unpleasant besides. If I wasn’t clear enough – go talk to an LLM about this. They have no option but to listen to your idiocy. I, of course, do have a choice, and am blocking you.


  • Veraticus@lib.lgbttoTechnology@lemmy.mlGPT-4 Understands
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    8 个月前

    You clearly don’t actually care; if you did, you wouldn’t select your sources to gratify your ego, but actually try to understand the problem here. For example, ask GPT4 itself if it is intelligent. It will instruct you far better than I ever can. You clearly have access to it – frame your objections to it instead of Internet strangers tired of your bloviating and ignorance.


  • Veraticus@lib.lgbttoTechnology@lemmy.mlGPT-4 Understands
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    8 个月前

    Here, let’s ask GPT4 itself since you’ve decided it’s suddenly an okay source:

    Your statement is correct in asserting that the vector representation in a language model is not an abstract representation. It’s purely a mathematical construct. However, saying it’s “unrelated to anything that actually exists” might be an overstatement. These vectors do capture statistical patterns in human language, which are reflections of human thought and culture. They’re just not capable of the deep, nuanced understanding that comes from human experience.

    I accept it’s an overstatement. But it is neither “incredibly wrong,” nor is it thought. (Or intelligence.)



  • Veraticus@lib.lgbttoTechnology@lemmy.mlGPT-4 Understands
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    8 个月前

    Oh, you again – it’s incredibly ironic you’re talking about wrong statements when you are basically the poster child for them. Nothing you’ve said has any grounding in reality, and is just a series of bald assertions that are as ignorant as they are incorrect. I thought you would’ve picked up on it when I started ignoring you, but: you know nothing about this and need to do a ton more research to participate in these conversations. Please do that instead of continuing to reply to people who actually know what they’re talking about.