Fushuan [he/him]

Huh?

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  • 221 Comments
Joined 4 个月前
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Cake day: 2025年6月8日

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  • Fushuan [he/him]to196[Spoiler] expedition 33 ending rule
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    7 小时前

    It’s about you recognising the people in the canvas as real or as paintings. If they are paintings Maelle being there forever is toxic. If they are real burning the painting is horrible. Even if you pick Maelles ending, in that same ending you kinda see a twisted reality where everyone is forced to be happy.

    So it’s either cleansing or becoming puppets. Both endings are bad for the painted world.

    Also, it’s a story about the acceptance of Verso’s death, the painting is a metaphor of his memories. In the end both endings show that painted people are not real, that they are paintings, so letting go is kinda the healthy ending for the only actually alive people of the story. I’d wish they left the world alone but that not being an option… Yeah.








  • Fushuan [he/him]to196Ruleatoulle 2
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    21 小时前

    Ben is selectively picking aspects from the movie that fit his agenda, completely ignoring the point Joe is doing, then trying to focus on how bad using ratatouille for “something piloting your actions” is, instead of expanding on what that would look like or having an actual opinion on the concept itself.

    Wtf is this, is Ben there to explore ideas or nitpick every unsubstantial things to “be right”? Pathetic.





  • I have a bachelor’s and master’s in computer science, specialised in data manipulation and ML.

    The problem with AI is that you don’t really need to understand the math behind it to work with it, even with training. Who cares how the distribution of the net affects results and information retention? who cares how stochastic gradient descent really works? You get a network crafted by professionals that gets X input parameters, which modify the network’s capacity in a way that’s given to you, explained, and you just press play in the script that trains stuff.

    It’s the fact that you only need to care about input data quality and quantity and some input parameters that freaking anyone can work with AI.

    All the thinking on the NN is given to you, all the tools to work with training the NN are given to you.

    I even worked with darknet and Yolo and did my due diligence to learn Yolov4, how it condensed info and all that, but I really didn’t need to for the given use case. Most of the work was labelling private data and cleaning it thoroughly. Then, playing with some Params to see how the final results worked, how the model over fitted…

    That’s the issue with people building AI models, their work is more technical that that of “prompt engineers” (😫), but not much.






  • WFH has been a blessing.

    You easily eliminate almost 2h from there, no commute, and some workdays no showerp/getting ready to go out. Even when I shower I try my damnest to do it between meetings in company time.

    I also do zero overtime, you’d be surprised that there are actually decent consultancy companies in that regard.