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Cake day: June 11th, 2023

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  • The argument I’m replying to is a classic “not perfect, thus not worth it”. Its disingenuous and it calls for disingenuous reply. We are also pursuing renewables in despite of their political and technical flaws. The point is that all the flaws that OP exposes about nuclear power also applied to renewables (at one point in history solar power was 10x more expensive than nuclear) and also to oil. They are status quo defending arguments designed to halt thought, paralyze action and scoff change. Just because it isn’t perfect doesn’t mean it isn’t better.




  • It means nothing, it’s just a paycheck you sign and then you get to say “I certify my OS is Unix”. The little bit more technical part is POSIX compliance but modern OSs are such massive and complex beasts today that those compliances are tiny parts and very slowly but very surely becoming irrelevant over time.

    Apple made OSX Unix certified because it was cheap and it got them off the hook from a lawsuit. That’s it.




  • Luddites weren’t against new technology, they were against the aristocrats using new technology as a tool or excuse to oppress and kill the labor class. The problem is not the new technology, the problem is that people were dying of hunger and being laid off in droves. Destroying the machinery, which almost always they were the operators of when working on said aristocrat’s factories, was an act of protest, just like a riot, or a strike. It was a form of collective bargaining.



  • Well, you see, that’s the really hard part of LLMs. Getting good results is a direct function of the size of the model. The bigger the model, the more effective it can be at its task. However, there’s something called compute efficient frontier (technical but neatly explained video about it). Basically you can’t make a model more effective at their computations beyond said linear boundary for any given size. The only way to make a model better, is to make it larger (what most mega corps have been doing) or radically change the algorithms and method underlying the model. But the latter has been proving to be extraordinarily hard. Mostly because to understand what is going on inside the model you need to think in rather abstract and esoteric mathematical principles that bend your mind backwards. You can compress an already trained model to run on smaller hardware. But to train them, you still need the humongously large datasets and power hungry processing. This is compounded by the fact that larger and larger models are ever more expensive while providing rapidly diminishing returns. Oh, and we are quickly running out of quality usable data, so shoveling more data after a certain point starts to actually provide worse results unless you dedicate thousands of hours of human labor producing, collecting and cleaning the new data. That’s all even before you have to address data poisoning, where previously LLM generated data is fed back to train a model but it is very hard to prevent it from devolving into incoherence after a couple of generations.





  • Most distributions and DEs already package wine in a set it and forget it configuration. Wine by default has a system wide prefix such that clicking on any exe in the file system automatically runs it on the default prefix. This way of doing things predates wsl by a long time. It is just safer and better practice to setup a new prefix for every software, specially if they are games.








  • dustyData@lemmy.worldtoGames@lemmy.worldWhy are most mobile games trash?
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    7 days ago

    Have you ever sat in front of a casino’s slot machine. They are also trash, awful and disgusting. But they’re also engineered with the worst dark pattern psychology to manipulate any human being that sits on it to keep playing and be so addictive that people will burn their money just to keep playing. The qualities of fun, and additive are independent of each other. A game can be very addictive and really bad at the same time. Unlike slot machines, they have the advantage of constantly sitting in your pocket and going with you everywhere you go.