... (thelemmy.club)
submitted 2 months ago by to c/slop@hexbear.net
 

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[–] 49 points 2 months ago
[–] 45 points 2 months ago

Explaining AI to Americans: Hallucinate a burger.

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  • [–] 45 points 2 months ago*

    AI trained on burgers plagiarises most prolific burger. Wow

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  • [+] 43 points 2 months ago* (last edited 1 month ago) (1 child)
  • [–] 41 points 2 months ago (1 child)

    Yeah, because the Big Mac is...so unique in its ingredients?

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  • [–] 36 points 2 months ago (1 child)

    Using round balls as a model system, a generative AI system rediscovers the classic round ball without explicit supervision and generates novel round balls optimised for shape, colour, or diameter, according to a paper in npj Science of Balls and Testicles.

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  • [–] 32 points 2 months ago
    [–] 30 points 2 months ago (1 child)

    trying to explain optimization to a generative AI: imagine a burger

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  • [–] 27 points 2 months ago (1 child)

    Yeah like wtf why is generative AI part of this. This is standard reward function optimization from the 1970s. Throw some simulated annealing at it and check in after 30 seconds

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  • [–] 20 points 2 months ago (1 child)

    LLMs have limited uses but they're the only thing the entire western tech industry has decided to work with so we have to rebrand old, simple processes as being done by them

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  • [–] 13 points 2 months ago (1 child)

    And even then, the only way we will know if these new, unheard-of burgers are actually delicious is to give them to focus groups to do taste testing, which is currently the process.

    Do we really need an ai to tell us that "75 percent of respondents said they didnt like how sweet the bun was" means we shluld"look at reducing the sugar in the bun? I'm not sure what an AI is even doing in this process

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  • [–] 7 points 2 months ago* (1 child)

    Haven't you heard? LLMs can replace focus groups and polls because they're already made up of averaged opinions.

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  • [–] 1 point 2 months ago (1 child)

    Thank god they haven't yet invented the RoboTongue

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  • [–] 26 points 2 months ago

    Wow, the plagiarism machine plagiarized the Big Mac.

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  • [–] 22 points 2 months ago*

    AI invents burger and all it took for it to do that is all the power of the Hoover Dam and the entire knowledge of human history including all the burgers.

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

    "rediscovers"

    Yeah, I rediscovered how to make a quarter pounder with cheese

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  • [–] 18 points 2 months ago

    Execs: We've finally found it, the AI of truth!

    AI: Use fresh, high quality ingredients and lots of meat.

    Execs: Nyehh!!

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  • [–] 18 points 2 months ago

    What a time to be alive! Now we can eat ai slop.

    ༼ つ ◕_◕ ༽つ

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  • [–] 16 points 2 months ago

    Yeah I ffucking love huge chunks of onion

    (I don't and I actually think if you're putting slices of anything on a burger that are bigger than an eighth of an inch you're a lazy hack building slop piles)

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  • [–] 16 points 2 months ago

    I do like when my imaginary burger's imaginary feedback has a +30% Moist factor over the imaginary Big Mac's imaginary feedback.

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  • [–] 15 points 2 months ago

    Nature Portfolio

    amerikkka-clap Nature is healing

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

    Am I stupid or is providing a data set to model output definitely, unambiguously, 100% supervision?

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  • [–] 12 points 2 months ago

    Delicious Burger #2's meat looks like charcoal

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

    "Delicious Burger 1" AKA the "Where's the Beef?" borger, going off of the AI slop graphic

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  • [–] 12 points 2 months ago (1 child)

    What you've never eaten a burger and thought to yourself, "Man i wish this was just all pickles and onion and no meat at all"? Everyone who has ever been vegetarian knows the the goto meatless burger is just a shit ton of pickle and a 1cm thick solid chunk of onion. Talk about flavor!

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

    From random samples, the model successfully rediscovers the classic Big Mac®, both in correct ingredients and weights, although the Big Mac® was never part of the initial training data (Fig. 2a). Across ten independent randomizations, rediscovering the Big Mac® requires on average 7.3 million samples which demonstrates that exact replication of recipes is a low-probability event under the learned distribution (Fig. 2e).

    my siblings in christ that's not recreating the big mac, that's keep hitting your head against the wall untill you start to bleed lmao. i don't have anything specific to say against the paper (because i can't be bothered to look deeper) but this really specific and horrible to test benchmark is way too funny to not dunk on.

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  • [–] 8 points 2 months ago

    >create training sample built on millions of burgers that are derivatives of the big mac™, but use a different name for legal reasons

    >the model produced a derivative of the big mac™

    waow, these dipshits really indebted themselves to the state for their whole adult lives to do this, by the way.

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  • [–] 4 points 2 months ago

    but does it know about cutting boards and newspaper and high industrial gastopub burger experience? :tm:

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  • [–] 3 points 2 months ago

    reinventing Big Macs from first principles

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