Three raccoons in a trench coat. I talk politics and furries.

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  • 43 Posts
  • 86 Comments
Joined 1 year ago
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Cake day: June 20th, 2023

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  • Not sure how deeply positive it was necessarily, but as far as I can tell I changed at least one person’s life significantly.

    When I was in middle school I learned how to solve the Rubik’s cube through online tutorials, and afterwards I was basically addicted to it for a while and I was messing with a cube all the time. One of my classmates was interested in learning how to solve one, so I drew a bunch of guides and taught him the terminology, and soon enough he was also hooked on the Rubik’s cube.

    I eventually grew tired of it, but he kept going and learned how to solve all sorts of smaller and bigger cubes and pyramids. I bumped into him at uni a few years later and he had a cube in his hand lol. Last I heard of him he was even participating in some local competitions, but idk what he’s up to now.

    Even if he ultimately gave up on his speedcubing dreams I can at least say that I introduced him to a cool new hobby that kept him entertained for several years.




  • Winter because I live in Brazil, which is a tropical and very humid country so the heat can get unbearable even here in the south where it’s colder compared to the north.

    There are a few cities that get cold enough to reach negative Cº, but where I live it’s mostly between 10º-20º during winter so I just need some extra coats and more blankets and I’m happy. During summer I can only take off so many layers before it becomes illegal.

























  • Please tell me how an AI model can distinguish between “inspiration” and plagiarism then.

    […] they just spit out something that it “thinks” is the best match for the prompt based on its training data and thus could not make this distinction in order to actively avoid plagiarism.

    I’m not entirely sure what the argument is here. Artists don’t scour the internet for any image that looks like their own drawings to avoid plagiarism, and often use photos or the artwork of others as reference, but that doesn’t mean they’re plagiarizing.

    Plagiarism is about passing off someone else’s work as your own, and image-generation models are trained with the intent to generalize - that is, being able to generate things it’s never seen before, not just copy, which is why we’re able to create an image of an astronaut riding a horse even though that’s something the model obviously would’ve never seen, and why we’re able to teach the models new concepts with methods like textual inversion or Dreambooth.