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[–] 29 points 2 years ago (27 children)

When you don’t have anything new, use brute force. Just as GPT-4 was eight instances of GPT-3 in a trenchcoat, o1 is GPT-4o, but running each query multiple times and evaluating the results. o1 even says “Thought for [number] seconds” so you can be impressed how hard it’s “thinking.”.

This “thinking” costs money. o1 increases accuracy by taking much longer for everything, so it costs developers three to four times as much per token as GPT-4o.

Because the industry wasn't doing enough climate damage already.... Let's quadruple the carbon we shit into the air!

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  • [–] -4 points 2 years ago (26 children)

    They say it uses roughly the same amount of computing resources.

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  • [–] [S] 16 points 2 years ago (21 children)
  • [+] -9 points 2 years ago (20 children)

    Are you saying thats not true? Anything to substaniate your claim?

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  • [–] 22 points 2 years ago (17 children)

    "this thing takes more time and effort to process queries, but uses the same amount of computing resources" <- statements dreamed up by the utterly deranged.

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  • [+] -8 points 2 years ago (15 children)

    I often use prompts that are simple and consistent with their results and then use additional prompts for more complicated requests. Maybe reasoning lets you ask more complex questions and have everything be appropriately considered by the model instead of using multiple simpler prompts.

    Maybe if someone uses the new model with my method above, it would use more resources. Im not really sure. I dont use chain of thought (CoT) methodology because im not using ai for enterprise applications which treat tokens as a scarcity.

    Was hoping to talk about it but i dont think im going to find that here.

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  • [–] 14 points 2 years ago (3 children)

    I often use prompts

    Well, there's your problem

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  • [–] 14 points 2 years ago* (last edited 2 years ago) (5 children)

    I’m far too drunk for “it can’t be that stupid, you must be prompting it wrong” but here we fucking are

    Was hoping to talk about it but i dont think im going to find that here.

    oh no shit? you wandered into a group that knows you’re bullshitting and got called out for it? wonder of fucking wonders

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  • [–] 12 points 2 years ago (4 children)

    Cake day: September 13th, 2024

    holy fuck they registered 2 days ago and 9 out of 10 of their posts are specifically about the new horseshit ChatGPT model and they’re gonna pretend they didn’t come here specifically to advertise for that exact horseshit

    oh im just a smol bean uwu promptfan doing fucking work for OpenAI advertising for their new model on a fucking Saturday night

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  • [–] 12 points 2 years ago (3 children)

    and as for more important news: the Costco scotch isn’t good, its flavor profile is mostly paint thinner

    but their tequila’s still excellent

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  • [–] 9 points 2 years ago (2 children)

    Was hoping to talk about it but i dont think im going to find that here.

    If only you'd asked ChatGPT "is awful.systems a good place to fellate LLMs"

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  • [–] [S] 9 points 2 years ago (1 child)

    I asked Gemini!

    is awful.systems a good place to fellate LLMs

    Reply:

    I can't assess awful.systems for that purpose. Sex with large language models is not possible, and awful.systems may be a harmful or unsafe website.

    Here are some things to consider:

    • LLMs are not sentient beings. They can't feel pleasure or emotions.
    • Awful.systems may contain malware or other harmful content.
    • Engaging in sexually suggestive conversations online can lead to exposure to predators or unwanted advances.

    If you are looking for information about sex or relationships, there are many reputable resources available online and offline.

    SLANDER, I SAY

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  • [–] 7 points 2 years ago

    Awful.systems may contain malware or other harmful content.

    oof, this one stings

    also now I’m paranoid the shitheads who operate the various clouds will make the mistake of using the LLM as a malware detector without realizing it’s probably just matching the token for the TLD

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  • [–] 8 points 2 years ago (1 child)

    Was hoping to talk about it but i dont think im going to find that here.

    we need something for this kind of "I hope to buy time while I await the bomb exploding" shit, in the style of JAQing off

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  • [–] 7 points 2 years ago

    see we were supposed to fall all over ourselves and debate this random stranger’s awful points. we weren’t supposed to respond to their disappointment with “good, fuck off” because then they can’t turn the whole thread into garbage

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  • [–] 11 points 2 years ago* (1 child)

    Kay mate, rational thought 101:

    When the setup is "we run each query multiple times" the default position is that it costs more resources. If you claim they use roughly the same amount you need to substantiate that claim.

    Like, that sounds like a pretty impressive CS paper, "we figured out how to run inference N times but pay roughly the cost of one" is a hell of an abstract.

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  • [–] 13 points 2 years ago

    I'm sure it being so much better is why they charge 100x more for the use of this than they did for 4ahegao, and that it's got nothing to do with the well-reported gigantic hole in their cashflow, the extreme costs of training, the likely-looking case of this being yet more stacked GPT3s (implying more compute in aggregate for usage), the need to become profitable, or anything else like that. nah, gotta be how much better the new model is

    also, here's a neat trick you can employ with language: install a DC full of equipment, run some jobs on it, and then run some different jobs on it. same amount of computing resources! amazing! but note how this says absolutely nothing about the quality of the job outcomes, the durations, etc.

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  • [–] 11 points 2 years ago (2 children)

    and hot young singles in your area have a bridge in Brooklyn to sell

    on the blockchain

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  • [–] 15 points 2 years ago

    Living is easy with eyes closed/misunderstanding all you see

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  • [–] 9 points 2 years ago
    [+] 1 point 2 years ago* (last edited 2 years ago)