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Cake day: November 19th, 2023

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  • Those are trained attack corgis. They may look cute, but their itty bitty widdle teefies can rip apart your throat if you so much as look at them wrong. When you’re watching their little fluffy butts when they walk, they just see you as a target. Just today’s hit. One signal, one word - and it’s over. You’ve been mauled to death by adorable attack sausages.


  • I’d describe it as sort of 3 layers. The first is practical/everyday things, which are mostly much nicer than being alone, but require attentiveness and communication (learn what your SO doesn’t like doing, and do it. Learn what things are work together projects, and what things are stay out of my way type things for each of you, probably other aspects too) - but once you know how to take care of each other, almost everything is less work, takes less time, and costs less money. Cooking, laundry, cleaning, gardening, repairing things, painting the house are all improved. Decorating and having guests over are harder, at least for me. You have to not fall into the trap of taking the things they do for granted, even when those things are routine.

    The second layer I’d describe is lust/romance, which is sort of easier, except that you must avoid letting things coast too long. You have to dedicate time and effort to discovering new things about each other, and new things you enjoy together. You should still be dating, no matter how long it’s been, and ideally you should both be planning things most of the time. In my relationship, this is usually 1-2 things per month, each.

    The final layer is the emotional/support layer. Almost any time, my wife can seek comfort and support from me in a variety of ways for all kinds of things, and I get the same from her. All the big problems in life are easier when you can share them, so here the benefits are huge. This is the only thing I got basically none of from having roommates or a best friend, or dating. For my situation, there’s basically no downside to this.








  • Real everyone-eats-ice-cream-and-dances-all-day hasn’t been tried either. Just because you describe a set of circumstances doesn’t mean those circumstances can exist, and it especially doesn’t mean they can be stable long term.

    Scarcity is a fact of nature. You cannot rationally distribute scarce things without knowing people’s preferences, so you either need to continuously solve the economic knowledge problem (which requires a huge state apparatus, which will be taken over by a dictator), or a means of exchanging goods between people to better suit their preferences (at which point you have invented capitalism).



  • There’s a lot of answers here, but I don’t think anyone said the magic words. To reseason cast iron, you need an oil high in poly-unsaturated fatty acids. Those are the kind that can chain together, and form a good polymer coating.

    The thing that trips me up most about this subject is that 140 years ago, pork fat was very good for seasoning cast iron. Today, it isn’t, because the composition of the fat has changed significantly.

    The best seasoning coats will be thin, not appear or feel oily, give the pan a dark color slightly more glossy than an eggshell, and resist mild detergents, metal spatulas, and heat high enough to sear a steak on. If you have a layer of loose stuff in the pan, that’s just a layer of gunk, and is probably adding some weird flavors to anything you cook.





  • I managed a CentOS system where someone accidentally deleted everything from /usr, so no lib64, and no bin. I didn’t have a way to get proper files at the time, so I hooked the drive up to my Arch system, made sure glibc matched, and copied yum and other tools from Arch.

    Booted the system, reinstalled a whole lot of yum packages, and… the thing still worked.

    That’s almost equivalent to a reinstall, though. As a broke college student, I had a laptop with a loose drive, that would fall out very easily. I set it up to load a few crucial things into a ramdisk at boot, so that I could browse the web and take notes even if the drive was disconnected, and it would still load images and things. I could pull the cover off and push the drive back in place to save files, but doing that every time I had class got really tiring, so I wanted it to run a little like a live system.



  • What we have done is invented massive, automatic, no holds barred pattern recognition machines. LLMs use detected patterns in text to respond to questions. Image recognition is pattern recognition, with some of those patterns named things (like “cat”, or “book”). Image generation is a little different, but basically just flips the image recognition on its head, and edits images to look more like the patterns that it was taught to recognize.

    This can all do some cool stuff. There are some very helpful outcomes. It’s also (automatically, ruthlessly, and unknowingly) internalizing biases, preferences, attitudes and behaviors from the billion plus humans on the internet, and perpetuating them in all sorts of ways, some of which we don’t even know to look for.

    This makes its potential applications in medicine rather terrifying. Do thousands of doctors all think women are lying about their symptoms? Well, now your AI does too. Do thousands of doctors suggest more expensive treatments for some groups, and less expensive for others? AI can find that pattern.

    This is also true in law (I know there’s supposed to be no systemic bias in our court systems, but AI can find those patterns, too), engineering (any guesses how human engineers change their safety practices based on the area a bridge or dam will be installed in? AI will find out for us), etc, etc.

    The thing that makes AI bad for some use cases is that it never knows which patterns it is supposed to find, and which ones it isn’t supposed to find. Until we have better tools to tell it not to notice some of these things, and to scrub away a lot of the randomness that’s left behind inside popular models, there’s severe constraints on what it should be doing.


  • That estimate is based on assuming that the ratio of matter to light output is the same between galaxies 10 billion years apart in age. The high light output of these young galaxies could also be supermassive stars that burn out very quickly, larger stars typically forming faster than smaller stars, or many other things.

    Blindly assuming a linear relationship between two things, then extrapolating is how you get the Windows loading bar circa 2000.

    Separately, but just as big a potential issue, the data itself may be incorrect. Previous galaxies measured at extreme redshift values were remeasured, and found to have less extreme values. This can be as simple as there aren’t that many photons from these galaxies reaching us, so a short measurement period might not be enough to get an accurate picture.