• MonkderVierte@lemmy.zip
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    1 hour ago

    It’s not artifical intelligence. A Large Language Model is not intelligent.

    And yes yes, scientifically, LLM belongs there and whatnot. But important is, what the people expect.

  • krooklochurm@lemmy.ca
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    9 hours ago

    See, the thing is, I watch piss porn. Hear me out. I told my friend that the thing is, to do piss porn, you kind of have to be into it. You could try and fake it, but it wouldn’t be very convincing. So, my contention is, piss porn is more genuine than other types of porn, because the people partaking are statistically more likely to enjoy doing that type of porn. Which is great, I think, because then they really get into it, which is hot. It’s that enjoyment that gets me off. Their enjoyment.

    She said, “Krooklochurm, you’re an idiot. Anyone can fake liking getting pissed in the face.”

    So I said, “Well, if you’re so adamant, get in the tub and I’ll piss in your mouth, and let’s see if it’s as easy as you claim.”

    So she said, “All right. If I can fist you in the ass afterwards.”

    Which I felt was a fair deal, so I took it.

    My (formal) position was strengthened significantly by the former event. And I can also attest that I could not convincingly fake enjoying being ass-fisted.

    What does that have to do with anything, you ask? Genuinity. The real deal. That’s what.

  • Drun@lemmy.world
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    3 hours ago

    You need a nuclear power plant not for a single AI, but for several million instances of it.

    Don’t forget that you can run full OSS ChatGPT on a single Mac Mini.

    AI is sick, and only silly people can deny that. Yes, future is little scary, but scary things should not stop us from progress.

    Yes, we do have a lot of AI slop, but don’t forget that AI can be an exceptionally good tool in right hands, and its spheres of usage grow every month. I can’t wait for generative tools for gauss splattering things, for example - because it can lead games developing process on another level.

  • mechoman444@lemmy.world
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    8 hours ago

    Ya evolution is pretty cool.

    And on that note the human physiology sacrifices quite a bit for its intelligence.

    For example the reason humans come out as babies is because if they came out with a full sized brains they’d kill the mother!

    It’s all about the most proficient use of energy.

  • Electricd@lemmybefree.net
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    8 hours ago

    Compare 1 human to one LLM session, instead of one human to all LLMs on Earth, and you’ll see that we’re way less efficient

  • Una@europe.pub
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    16 hours ago

    So, you are saying, I should mix my cocaine with twix bars for maximum efficiency? (Would still be stupid, but now more efficiently)??

  • the_q@lemmy.zip
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    16 hours ago

    To be fair a lot of people think they’re intelligent and they really really aren’t.

    • Aneb@lemmy.world
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      13 hours ago

      I’m not trying to grade on potential but betting on human potential vs AI potential feels like it rewards ourselves for being better vs a machine. Would we have Albert Einstein if we didn’t have Isaac Newton?

      • applebusch@lemmy.blahaj.zone
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        2 hours ago

        That’s kind of a false dichotomy. They may be separate today, but there’s no reason to believe we won’t augment human minds with artificial neural networks in the future. Not in the magical cure all fix all way techbros like to sell it, but for like really boring and mundane things initially. Think replacing a small damaged part of some brain region, like the visual or auditory cortexes, to repair functional deficiencies. Once they get the basic technology worked out to be reliable, repeatable, and not require too much maintenance (cough subscriptions and software licenses), there’s no reason to believe we won’t progress rapidly to other augmentations and improvements. A simple graphical interface for like a heads up display or a simple audio interface for direct communications both come to mind, but I’m sure our imaginations will be comically optimistic about some things and comically pessimistic about others. All that to say that any true AI potential will be human potential in time. We won’t stop at making super intelligent AGI. We will want to BE super intelligent AGI. Since we already know highly efficient and capable intelligence is possible (see yourself) it’s only a matter of time until we make it ourselves, provided we don’t kill ourselves somehow along the way.

  • But_my_mom_says_im_cool@lemmy.world
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    12 hours ago

    I think the entire idea of ai and the Internet in general taking up power and water needs to be fleshed out and explained to everyone. Even to me it’s a vague notion, I heard about it a few years back but can’t explain it to someone like my parents who would have no idea the Internet requires water to run

    • asmoranomar@lemmy.world
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      11 hours ago

      It’s not too hard. AI requires a LOT of work. Work requires energy. Some energy is wasted during this and the byproduct is heat. The heat has to be removed for many reasons, and water is very good at doing that.

      It’s like sweating, it cools you down. But you need water to sweat.

  • justadudeingear@lemmy.world
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    9 hours ago

    All it really takes is the Limitless pill. The protagonist in the movie Limitless gets so much done after taking the Limitless pill in the movie Limitless. Limitless is a movie about a man who discovers the Limitless pill to help him accomplish almost limitless amount of things. But he learns that there is a limit that the Limitless pill can do if he takes it for too long. Because the Limitless pill isn’t really limitless.

  • wabafee@lemmy.world
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    3 hours ago

    I think we’re at a point were the hardware right now does not fit with the algorithm being used. Since they take so much power due to our computers being digital. Having a transistor only capable of holding 1 state (0V or 5V usually) is inefficient. The heat add up as you multiply especially with LLMs. There seems to be a potential for analog where a transistor acts more on a range 0 - 5v. Which in theory could store more information or directly represent what LLM runs on (floating point). For more context 1 float tends to be 32bits. 1 bit is 1 transistor so 1 float = 32 transistor. While an analog transistor could be 1 float = 1 analog transistor.

  • 0nt0p0fth3w0rld@feddit.org
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    16 hours ago

    and some of the most intelligent people are cast out from society because they don’t fit the culture of arrogance.

  • LifeInMultipleChoice@lemmy.world
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    14 hours ago

    Wasn’t there an article posted yesterday about a group trying to create a biological computer that was living cells do to their efficiency of use on less power? (They are far from close, they basically took skin cells, ionized them, and had no idea how they were going to get them to stay alive long term yet.

    • fonix232@fedia.io
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      13 hours ago

      Even that won’t be anywhere close to the efficiency of neurons.

      And actual neurons are not comparable to transistors at all. For starters the behaviour is completely different, closer to more complex logic gates built from transistors, and they’re multi-pathway, AND don’t behave as binary as transistors do.

      Which is why AI technology needs so much power. We’re basically virtualising a badly understood version of our own brains. Think of it like, say, PlayStation 4 emulation - it’s kinda working but most details are unknown and therefore don’t work well, or at best have a “close enough” approximaion of behaviour, at the cost of more resource usage. And virtualisation will always be costly.

      Or, I guess, a better example would be one of the many currently trending translation layers (e.g. SteamOS’s Proton or macOS’ Rosetta or whatever Microsoft was cooking for Windows for the same purpose, but also kinda FEX and Box86/Box64), versus virtual machines. The latter being an approximation of how AI relates to our brains (and by AI here I mean neural network based AI applications, not just LLMs).

      • applebusch@lemmy.blahaj.zone
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        2 hours ago

        There’s already been some work on direct neural network creation to bypass the whole virtualization issue. Some people are working on basically an analog FPGA style silicon based neural network component you can just put in a SOM and integrate into existing PCB electronics. Rather than being traditional logic gates they directly implement the neural network functions in analog, making them much faster and more efficient. I forget what the technology is called but things like that seem like the future to me.

        • fonix232@fedia.io
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          44 minutes ago

          I’m very much aware of FPGA-style attempts, however I do feel the need to point out that FPGAs (and FPGA style computing) is even more hardware-strained than emulation.

          For example, current mainstream emulation FPGA DE10 Nano has up to 110k LE/LUT, and that gets you just barely passable PS1 emulation (primarily, it’s great for GBA emu, and mid to late 80s, early 90s game console hardware emulation). In fact it’s not even as performant as GBA emulation on ARM - it uses more power, costs more, and the only benefit is true to OG hardware execution (which isn’t always true for emulation).

          Simply said, while FPGAs provide versatility, they’re also much less performant than similarly priced SoCs with emulation of the specific architecture.

  • linuxgator@lemmynsfw.com
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    11 hours ago

    Back when I was in college, grad students in physics seemed to live on frozen burritos (thawed and cooked in the microwave), and cherry coke.