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Joined 2 年前
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Cake day: 2023年6月10日

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  • You’re not alone! I worked 12 hours in 37°C (99°F), 47% humidity yesterday. However, we get essentially unlimited breaks in an air conditioned break room, have cooling vests filled with ice packs we can wear on the floor, and are supplied with sports drinks and feeezies. Your work can’t really make the world less hot, but they can work with you to avoid development of heat related illnesses!






  • My understanding is that “China” is special because they’re a founding member of the UN and have special powers due to that. After the civil war, neither Taiwan or China wanted to lose that power, so neither side wanted to be recognized as anything other than “China”. I’ve heard that the younger generation in Taiwan are more open to being recognized as Taiwan but China has kind of made that impossible now by threatening any country that doesn’t respect the “one China” policy.


  • I don’t think there’s any moment that truly blows your mind. It’s a very slow burn. I found every run I learned something new that made me want to revisit old rooms and search out new ones. It definitely helps to take notes which is also fun in its own way.

    Sometimes solving a puzzle just gives you some lore but that was also neat too. There’s one note I found that stuck with me regarding following traditions. It doesn’t have anything to do with the game but it was great writing!


  • why don’t they program them

    AI models aren’t programmed traditionally. They’re generated by machine learning. Essentially the model is given test prompts and then given a rating on its answer. The model’s calculations will be adjusted so that its answer to the test prompt will be closer to the expected answer. You repeat this a few billion times with a few billion prompts and you will have generated a model that scores very high on all test prompts.

    Then someone asks it how many R’s are in strawberry and it gets the wrong answer. The only way to fix this is to add that as a test prompt and redo the machine learning process which takes an enormous amount of time and computational power each time it’s done, only for people to once again quickly find some kind of prompt it doesn’t answer well.

    There are already AI models that play chess incredibly well. Using machine learning to solve a complexe problem isn’t the issue. It’s trying to get one model to be good at absolutely everything.









  • I have a friend who has worked for 3 companies over 6 years. She has never once released a game as they were all cancelled before release. She found out she lost her job at one company after reading an interview about a bunch of studios being shut down. One of them was the place she worked. Even her boss apparently didn’t know.

    The studio she works at now initially hired her for completely remote work, but they’ve since changed their minds and now she has to drive over 100km to work every day. She was going to quit but she’s sticking with it for now in the hopes of finishing at least one game.