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InitialsDiceBearhttps://github.com/dicebear/dicebearhttps://creativecommons.org/publicdomain/zero/1.0/„Initials” (https://github.com/dicebear/dicebear) by „DiceBear”, licensed under „CC0 1.0” (https://creativecommons.org/publicdomain/zero/1.0/)EZ
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2 yr. ago

  • Where it was a little wonky - and i didn’t expect this - was dice rolling and math.

    I'm not really surprised - these are LLMs = Large Language Models. They are made to remix natural language sources, they can walk like a duck and quack like a duck. But the things that are really hard to get right with them are math, logic & reasoning, and facts. E.g. https://www.forbes.com/sites/johnwerner/2024/10/07/ai-is-usually-bad-at-math-heres-what-will-happen-if-it-gets-better/

    AI image generators are even worse, e.g. https://gpt.gekko.de/ai-numeracy-text-image-models/