applebusch (she/her)

  • 0 Posts
  • 27 Comments
Joined 2 years ago
cake
Cake day: November 11th, 2024

help-circle





  • guessing the point was they wanted palworld to stop existing and not only do they not get that but its one of the most popular games on steam. they failed utterly. this was totally self inflicted because yeah pokemon is like the biggest ip ever and nothing palworld could have done would have changed that in the least. just like none of the fan games or rom hacks that have been killed over the years could have. but nintendo just has to sue everybody anyway because copyright law go brrr. its just nice to see them lose for once.


  • i like the mental image of a huge body of water where most places are only a few inches below the surface but youll randomly find little lava tubes that go unexpectedly deep (evidence of temporary hyperfocus), several deep valleys (more enduring fixations), and a couple mariana trenches (special interests). reminds me of the train on the water in spirited away.

    also this was me…







  • i can see that youve had some coolaid. i hope you can stop drinking and start recovering. a lot of what you said is gibberish, but throwing more data at machine learning models has been shown to result in diminishing returns, and doesnt change that the technology is inherently fallible. it might get very close to 100% reliable, but the hallucination problem will never fully go away. thats not the end of the world, but it requires machine learning algorithms to be paired with more deterministic tools to be sure of results. it happens with our own brains too, which is part of why we invented math and computers in the first place.





  • the greatest power of machine learning algorithms is the source of its greatest drawback. they are essentially heuristic models of something, constructed in a way that they are much cheaper to execute than a traditional algorithmic approach. this cheapness results in error, which for a lot of applications is fine because you can refine/check the result with more accurate tools, but it also means you can never just trust it like you can with more traditional tools. this problem is baked into the technology so theres no amount of scale that will make it go away, as we’ve seen time and again with LLMs. failing to understand this is the mistake most people make when it comes to “AI”, and results in all kinds of bad decision making. but in the hands of people who understand the limitations, machine learning can truly be a game changing technology. not chatbots though those are fucking stupid and i hope they go away when the bubble bursts.




  • to be fair the overviewer effect has been romanticized and played up by people who literally spent their entire life training and competing for the chance at a few hours or days cumulative time in space while pretending for the deciders and teams of doctors that they arent just normal flawed people like the rest of us. astronauts basically have to buy in to the overviewer effect as one of the things that makes all their sacrifices “worth it”, and part of trying to convince themselves is convincing others that its a real thing most people will experience. its more of a placebo effect in reality, though im sure there are people who genuinely felt it. bezos just didnt have to work for it at all so he has no incentive to buy into the hype, total lack of empathy and compassion aside.