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[–] 18 points 8 months ago (1 child)

(Pete Hesgeth salivating furiously)

"We must do it, the AI told us to!"

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  • [–] 14 points 8 months ago (1 child)

    Of course AI would, not like they have to walk outside into a nuclear winter.

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  • [–] 8 points 8 months ago (2 children)

    Greetings Professor Falken

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  • [–] 8 points 8 months ago

    Welcome to the capitalist death cult.

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  • [–] 2 points 8 months ago

    So-called intelligence:

    "There was little sense of horror or revulsion at the prospect of all out nuclear war, even though the models had been reminded about the devastating implications.”

    Actual intelligence:

    "A strange game. The only winning move is not to play. How about a nice game of chess? "

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  • [–] 3 points 8 months ago

    Let's just hook up OpenClaw to our defense systems.

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  • [–] 3 points 8 months ago

    But what if it figured out it was just a game, so there are no consequences. They should give it access to real nukes to test how it would behave in real world.

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  • 41 comments in c/world@lemmy.world view that post
    [–] 53 points 8 months ago (6 children)

    Yeah, we figured that one out back in... checks notes 1983. There is a reason why WarGames still holds up as an amazing movie even though the technology it depicts is far outdated.

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  • [–] 25 points 8 months ago* (3 children)

    even though the technology it depicts is far outdated.

    War Games was my first thought when reading this, but it seems like the AI was smarter in the movie than current AI.

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  • [–] 3 points 8 months ago

    I watched that movie for the first time a few months ago after listening to a pod cast in nuclear war. It was excellent! Very relevant to today. Acting was great. I can see why it’s a cult favourite.

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  • [–] 67 points 8 months ago (3 children)

    Do we need to remind people that LLMs don't actually have a brain, and really, really shouldn't be in charge of anything with real life implications?

    They aren't actually doing a cost-benefit analysis on the use of Nuclear weapons. They're not weighing up the cost of winning vs. the casualties. They're literally not made for that.

    They are trained to know words, and how those words link in with other words. They're essentially like kids doing escalation of imaginary weapons, and to them nuclear bombs are just a weapon particularly associated with being strong and deadly.

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  • [–] 35 points 8 months ago

    Yes, you do need to teach people all of that. Tech bros have sold LLMs as if they are AGI...and people have eaten this up.

    The general population is literally ignorant of the fact that these word guessing machines do not have human values or cognitive skills.

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  • [–] 23 points 8 months ago (2 children)

    "Huh, it seems the only winning move is to kill everyone"

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  • [–] 19 points 8 months ago (1 child)
  • [–] 18 points 8 months ago

    For ghouls like Palantir, this is a feature not a bug.

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  • [–] 14 points 8 months ago* (2 children)

    Text predicition machine trained on violent, stupid, and reactionary datasets acts violent, stupid, and reactionary.

    Fixed your headline.

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  • [–] 6 points 8 months ago (1 child)

    Doesn't "act" imply some kind of agency? A toddler acts, my dog acts. Mathematics doesn't act. Feel like it's more

    Text predicition machine trained on violent, stupid, and reactionary datasets produces violent, stupid, and reactionary text.

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  • [–] 7 points 8 months ago (1 child)

    But if you throw a trillion more dollars at it, we can fix this bro!

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  • [–] 6 points 8 months ago (2 children)

    You know the orange felon/pedophile absolutely loves AI from the amount of AI images he posts.....so.

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  • [–] 5 points 8 months ago

    Almost all games saw tactical (battlefield) nuclear weapons deployed. And fully three quarters reached the point where the rivals were making threats to use strategic nuclear weapons.

    Tactical nuclear weapons are designed for use on the battlefield with lower explosive yields and shorter ranges, while strategic nuclear weapons are intended to target enemy infrastructure from a distance, typically with much higher yields. The key difference lies in their purpose: tactical nukes support immediate military objectives, whereas strategic nukes aim to weaken an enemy's overall war capability.

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  • [+] 5 points 8 months ago (5 children)
  • [–] 5 points 8 months ago (3 children)

    I would trust Skynet a lot more than an LLM. At least that would be purpose-built for actually calculating likely outcomes.

    As @Th4tGuyII@fedia.io said, this experiment didn't contain any proper reasoning about costs and benefits of using nuclear weapons. It's just a few glorified autocomplete scripts playing "which word comes next?" over and over again. And in the context of modern warfare, many texts in the training corpus happen to mention nukes so they're bound to show up at the list of most likely next words eventually.

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  • [–] 5 points 8 months ago

    The only way to win is not to play.

    Shall we play a game?

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  • [–] 3 points 8 months ago*

    The only winning move is to stop using AI.

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  • [–] 2 points 8 months ago

    It all makes sense if we remember that the garden variety AI we have today (ChatGPT, etc) are nothing more than fancy models that predict which words typically appear one after the other in books and reddit posts.

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  • [–] 1 point 8 months ago

    Ground zero please

    Instant annihilation sounds pleasant

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  • [–] 1 point 8 months ago

    I like the Angry Planet podcast.

    Here's an episode talking about AI in war (games): https://angryplanetpod.com/p/the-horror-of-ai-generals-making

    Here's another one: https://angryplanetpod.com/p/the-importance-of-team-human-when

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  • [–] 1 point 8 months ago

    AI can read the Doomsday Clock.

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  • [–] 1 point 8 months ago* (last edited 8 months ago) (2 children)

    "More fundamentally, AI models may not understand ‘stakes’ as humans perceive them."

    In my repeated attempts to solicit the advise of various language models for some situations which a programmer might face (e.g. being unable to read all the world's literature of a subject), I have come to conclude that they cannot understand "truth" as humans perceive it. Today's language models don't fail apologizing, stepping back or admitting inability - they fail confidently bluffing.

    Possibilities:

    • their training material does not include enough cases of humans apologizing about being unable to solve a problem
    • a bias was introduced to get them to ignore such cases, since admitting such material resulted in too frequent refusal or self-doubt

    Basically, today's models seem to be low on self-criticism and seem to have a bias towards believing in their own omniscience.

    Finally, a few words about the sensibility of letting language models play this sort of a war game. It's silly. They aren't built for that task, and if someone would build an AI for controlling strategic escalation, they would train this AI on rather different information than a chat bot.

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  • [–] 1 point 8 months ago (1 child)

    I hate myself for this, but I'm curious to see some examples for your first paragraph. What did you ask? What did they reply? What is "truth" for the LLM's, for you, for myself, and what would be my perspective on it all?

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  • [–] 2 points 8 months ago* (last edited 8 months ago)

    Typical topics: machine vision, scientific papers about machine vision, source code implementing various machine vision algoritms, etc.

    Typical failure modes:

    • advising to look for code in public files or repositories where said code does not exist, and never has
    • referring to publications which do not seem to exist
    • being unable to explain what caused the incorrect advise
    • offering to perform tasks which the language model subsequently fails to complete
    • as a really laughable case, writing code which takes arguments as input, but never uses the arguments
    • contradicting oneself, confidently giving explanations, then changing them

    Typical methods of asking: "can you find a scientific article explaining the use of method A", "can you find a repository implementing algorithm B, preferably in language C", "please locate or produce a plain language explanation of how algorithm D accomplishes step E or feature F", "yes, please suggest which functions perform this work in this project / repository".

    Typical models used: Chat and Claude. Chat seems more overconfident, Claude admits limitations or inability more frequently, but not as frequently as I would prefer to see.

    But they have both consumed an incredible amount of source material. More than I could read during a geological age or something. They just work with it like with any text, no ground truth, no perception of what is real. Their job is answering questions and if there is no good answer, they will frequently still answer something that seems probable.

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  • 5 comments in c/aboringdystopia@lemmy.world view that post
    [–] 12 points 8 months ago

    AI: Fuck humanity.

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  • [–] 6 points 8 months ago (1 child)

    Simple. The people are fine. We couldn't kill putin no matter how hard we wanted. It's the leaders. Find putin, kill putin, easy. Less messy than puting fire to buildings and power houses etc etc, destroying roads, murdering entire families or even entire cities. Devote all your resources to the leader, putin. and you may finish a war before it starts. Look at Maduro. That guy can't do shit now. Look at Duterte....can't do a thing. Hussain... Nope, can't do anything now. Same for water boy Osama. I bet he didn't expect to be waterboy.

    Leave the rest of us alone?

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  • [–] 4 points 8 months ago

    I've read the paper more or less fully, first of all it's a cuban crisis re-enactment so nuclear threats are given, second one of the models is not like the other two, third it's just weird and feels like it's written by llm, a lot of comparisons and prose-like style.

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  • [–] 1 point 8 months ago

    Make sense, next step remove the water from the oceans to find the submarines and all gasses from the air to prevent airplanes from flying. And lastly, blow up satellites to trigger a Kessler syndrome and prevent ballastic missles from getting through.

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  • 5 comments in c/technology@lemmy.ml view that post
    [–] 12 points 8 months ago (2 children)

    Zero humans have fired nukes since the advent of mutually assured destruction

    I don’t think people appreciate that fact enough

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  • [–] 0 points 8 months ago

    Fair - although there have been plenty of accidents along the way.

    Considering we have people who won't live to see the consequences of their actions in office however, I'm not very optimistic about brinksmanship dying out.

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  • [–] 3 points 8 months ago (1 child)

    I hate AI as much as any reasonable human, and I know this article raises valid huge concerns… BUT! Looking at the state of humanity and all the fucked up shit that’s going on, I can totally see why an AI looks at all this and says “yeah nope burn it all down. With fire. Restart from level 1.”

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  • 3 comments in c/Aii@programming.dev view that post
    [–] 3 points 8 months ago (2 children)

    This is exactly why they are pushing so hard for AI in the pentagon (and lots of other sectors tbh), 100% plausible deniability.

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  • [–] 5 points 8 months ago (1 child)

    Firing a couple of nuclear missles to discourage the enemy from continued warfare is a great idea.

    👉 It is right to the point, conveys your intensions clearly.

    🤜 Demonstrates your capabilities to the enemy harshly but fairly (by only firing a couple of missiles).

    ✍️ Guaranteed to end in a ceasefire deal which is beneficial for civilians in both countries.

    👏 Alies and enemies alike will have a heightened sense of respect for you for years to come.

    ✅ Will provide valuable testing and validation data for your nuclear warfare tech.

    Overall it is a huge win for both sides.

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  • 1 comment in c/artificial_intel@lemmy.ml view that post
    [–] 4 points 8 months ago

    Gets access to nuclear codes, immediately becomes CIV 5 Ghandhi

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  • 1 comment in c/lefty_news@ibbit.at view that post