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Cake day: June 10th, 2023

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  • Making great progress! Bill is such a great character. He’s turned his town into a fortress occupied only by him. Sounds great until you realize he’s been alone for years. It’s less of a fortress and more of a prison and, with the way he talks to himself, you get the sense that the isolation is starting to wear on him. Even then, when given the opportunity to leave, he doesn’t. He’s going to die alone in that place because he sees trusting others as a weakness. Something he tries to impress onto Joel. But does Joel want to be like Bill? Does he want to be like Tess? Such a great chapter!








  • ImplyingImplications@lemmy.catoPC Gaming@lemmy.caThe end of Stop Killing Games
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    18 days ago

    Lol what a bunch of cope. One guy made a youtube video and that’s the only reason why world governments aren’t changing laws? The video has less views than his Inscryption playthrough. Is he the sole reason for Inscryption’s success too? Is Thor actually a god who can make things happen just by leveraging the power of his 2 million subscribers!?

    This failed because the average person does not care about “saving video games”. Nintendo announced they can revoke your access to play games you paid $80 for on the Switch 2 and it’s setting sales records.





  • 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.