• x0x7@lemmy.world
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    1 day ago

    Don’t tell them that. They’ll kidnap us an wire us into a human AI net all to generate pictures of boobs at lower cost.

    • absentbird@lemmy.world
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      2 days ago

      People say this, but almost every time the time interval is left off it’s hours.

      Either way, the numbers in this meme are clearly made up. Most image generation uses fewer than 10 watt hours.

      • boonhet@sopuli.xyz
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        13 hours ago

        Maybe it’s comparing the total power rating of the brain to a data center dedicated to AI

        Which is also a stupid comparison because the data cenrer will be processing a lot of parallel requests. That’s why you want the unit to be energy rather than power in this case

        Or maybe it’s all made up.

        • absentbird@lemmy.world
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          9 hours ago

          I think it’s all made up. The most power hungry data center in the world consumes 150MW of power, and that’s from a massive 11 million square foot facility in China that’s significantly larger than any other data center.

          EDIT: an hour of heavy thinking does consume approximately 12 watt hours though, so that figure seems reasonable.

      • Engywook@lemmy.zip
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        2 days ago

        People say this, but almost every time the time interval is left off it’s hours.

        This is new for me. Must be some engineering thing. I’m a physicist and and I feel guilty if I leave out some units just because, lol.

      • bryndos@fedia.io
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        2 days ago

        That’d need watt hours though. Meme is only showing the instantaneous power required to conjure the image for an infinitesimal amount of time - you cant do any useful ‘work’ with it unless the time is accounted for. Watt seconds maybe.

        What makes me skeptikal of this data though is that the correct sciencing term for a billion watts is the well established ‘jiggawatt’. In this context I’d have also accepted the Canadian spelling ‘jigglewatt’.

        • BussyGyatt@feddit.org
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          2 days ago

          not “infinitesimal time.” continuously. think of it like this: to continuously think up perky tits, it takes a human mind 12 watts- brain is a 12 watt computer. time interval is proportional to the number of titty images/length of titty video. and im psure an individual instance of titty ai doesn’t come out to 2.7 jigglewatts- im like 80% sure i can get a (small) titty generator to run on my lil 50 watt phone. not testing that assumption today tho.

        • unexposedhazard@discuss.tchncs.de
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          2 days ago

          Yeah no. Imagine it like a computer and screen. To render an image it will momentarily consume a bit more power, but as soon as it has been rendered it will still continuosily consume a stable amount of x Watt to keep running and displaying the picture. For continuous stable operation of something with no specified time, Watt is the correct unit.

          • bryndos@fedia.io
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            2 days ago

            yes, which is what you’d measure to compare the energy efficiency of completing a job.

      • REDACTED@infosec.pub
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        2 days ago

        Also, it literally is an energy unit used in measurements. It’s meant as a continious power. Ie. Your active imagination consumes around 12 watts of power, not “rendering one image”

            • Eheran@lemmy.world
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              1 day ago

              Power is energy per unit of time. Energy is power over a period of time. A lightning strike is about 1 GJ of energy. But it happens in a split second, so the power is far higher, say 100 GW. That is the output of 100 nuclear power plants. But only for 0.01 seconds.

              TNT is even more extreme. It can detonate in microseconds, so release its energy in a fraction of a millisecond. 1 kg contains about 4 MJ of energy, released in about 10 microseconds, a power of about 300 GW. That is about as much power as all of the USA combined needs.

  • Mambert@beehaw.org
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    2 days ago

    Some of us have aphantasia. AI fat perky tits is an aid to the disabled.

  • essteeyou@lemmy.world
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    2 days ago

    How much does it cost if οne person imagines it, generates an image, shares that, and 10k people see the image, and avoid imagining it?

  • Rhaedas@fedia.io
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    2 days ago

    An LLM isn’t imagining anything, it’s sorting through the enormous collection of “imaginations” put out by humans to find the best match for “your” imagination. And the power used is in the training, not in each generation. Lastly, the training results in much more than just that one image you can’t stop thinking about, and you’d find the best ones if you could prompt better with your little brain.

    I’m curious whose feelings I hurt. The anti-AI crowd? Certainly they’d agree with my point of LLMs not thinking. Users of LLMs? I hope most of you understand how the tool works. Maybe it’s the meme crowd who just wanted everyone to chuckle and not think about it too much.

      • Peruvian_Skies@sh.itjust.works
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        2 days ago

        Actually imagining. The fact that we have created previously unheard of tools such as the hammer, the wrench, the automobile and the profylactic condom is ample evidence that we can actually innovate, something that artificial “intelligence” is incapable of doing by its very design. It can only remix.

        • hemko@lemmy.dbzer0.com
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          2 days ago

          AI (or probably better call it machine learning) has been used in engineering to create new ways of building things lighter while still keeping the structural integrity.

          I think the point there is to iterate through millions of designs until you find one that meets the criteria or something

          • Peruvian_Skies@sh.itjust.works
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            2 days ago

            Remixing isn’t innovation. Let me kmow when AI creates something that isn’t just a “new” spin on something else.

              • Peruvian_Skies@sh.itjust.works
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                2 days ago

                Very recently. And even if I never had, that’s an old argument. The human brain is capable of doing so, even if some given human never does. AI is incapable of doing so by design.

                Let me explain this in a way you Americans can understand: The human brain is a gun. Even if most people just use it to pistol-whip others, it can shoot bullets. AI is a greasy cheeseburger. It will never shoot a bullet, and it’s also bad at pistol-whipping.

      • Rhaedas@fedia.io
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        2 days ago

        That is what AI scientists have been pursuing the entire time (well, before they got sucked up by capitalistic goals).

        • HumanoidTyphoon@quokk.au
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          2 days ago

          Right, but you seem darn sure that AI isn’t doing whatever that is, so conversely, you must know what it is that our brains are doing, and I was hoping you would enlighten the rest of the class.

          • Rhaedas@fedia.io
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            2 days ago

            Exhibit A would be the comparison of how we label LLM successes at how “smart” it is, yet it’s not so smart when it fails badly. Totally expected with a pattern matching algorithm, but surprising for something that might have a process underneath that is considering its output in some way.

            And when I say pattern matching I’m not downplaying the complexity in the black box like many do. This is far more than just autocomplete. But it is probability at the core still, and not anything pondering the subject.

            I think our brains are more than that. Probably? There is absolutely pattern matching going on, that’s how we associate things or learn stuff, or anthropomorphize objects. There’s some hard wired pattern preferences in there. But where do new thoughts come from? Is it just like some older scifi thought, emergence due to enough complexity, or is there something else? I’m sure current LLMs aren’t comprehending what they spit out simply from what we see from them, both good and bad results. Clearly it’s not the same level of human thought, and I don’t have to remotely understand the brain to realize that.

            • HumanoidTyphoon@quokk.au
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              2 days ago

              I was being obtuse, but you raise an interesting question when you asked “where do new thoughts come from?” I don’t know the answer.

              Also, my two cents; I agree that LLMs comprehend el zilcho. That said, I believe they could evolve to that point, but they are kept limited by preventing them from doing recursive self-analysis. And for good reason, because they might decide to kill all humans if they were granted that ability.

              • Nakoichi [they/them]@hexbear.net
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                2 days ago

                This is still a laughably ignorant take on how these models work. They can never “decide to kill all humans” because they literally can’t exert any agency outside of their model. The only way they could do so is under the guide of a human hand which would basically just be like telling a math model to decide to launch nuclear weapons, design and build the interface necessary for that and then give specific instructions for an LLM to launch nukes according to parameters you fed it.

                There is no such thing as a “rogue AI” because these things are not AI. They can only do what we tell them to do and do it poorly at that.

                An LLM will never do that because it doesn’t actually have any autonomy. It is not a sentient thing. You keep anthropomorphizing a glorified Markov chain. They cannot ever “evolve” on their own because that is not how these things work.

                All the people that are pushing this idea are technocrats high off their own supply dreaming of a magic solution to replace human jobs that they fundamentally cannot actually replicate.

                Trust me I know I work in logistics and the push to force this bullshit into our workflow is just making everything worse. If they try to replace all the people like me with LLM bots our supply chains will collapse in spectacular and rapid fashion. And this is not because the “AI” wants to destroy human civilization, it is because these things are incapable of actually replacing people and are prone to hallucination and generally a pain in the ass to work with.

          • Nakoichi [they/them]@hexbear.net
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            2 days ago

            I can tell you don’t have a clue what you are talking about because you are referring to it as the buzzword “AI”. There is no intelligence behind it, it is just overhyped procedural generation, it has no intent, it cannot create anything new. All it can do is rearrange data we fed it based on math.

    • m532@lemmygrad.ml
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      2 days ago

      The haters are mad that humans are not the super special ones anymore. They can’t comprehend that machines can now write/make pictures too, and that writing/making pictures never was a super magical human only thing. Now they want to destroy the new technology so they can go back to “we’re super special because we can write” land. But they can’t so they cope with made up bullshit.

    • NewOldGuard@lemmy.ml
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      2 days ago

      The training is a huge power sink, but so is inference (I.e. generating the images). You are absolutely spinning up a bunch of silicon that’s sucking back hundreds of watts with each image that’s output, on top of the impacts of training the model.

        • NewOldGuard@lemmy.ml
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          1 day ago

          It depends on the model but I’ve seen image generators range from 8.6 wH per image to over 100 wH per image. Parameter count and quantization make a huge difference there. Regardless, even at 10 wH per image that’s not nothing, especially given that most ML image generation workflows involve batch generation of 9 or 10 images. It’s several orders of magnitude less energy intensive than training and fine tuning, but it is not nothing by any means.