The “Forgetting How Your Own Code Works” is real. I’ve looked at code, thought to myself “what fcking idiot wrote this garbage”, only to see my own name next to it. It’s a very humbling experience

I was just about to post the same thing. I’ve been using Linux for almost 10 years. I never really understood the folder layout anyway into this detail. My reasoning always was that /lib was more system-wide and /usr/lib was for stuff installed for me only. That never made sense though, since there is only one /usr and not one for every user. But I never really thought further, I just let it be.

Sometimes I look at the memes around here and wonder wtf y’all are doing. Like, neither my code nor the code at the place I work at are perfect. But I don’t think I’ve ever seen a merge do this. Maybe some of the most diverged merges temporarily had a lot of errors because of some refactoring, but then it was just a few find + replaces away from being fixed again. But those were merges where multiple teams had been working on both the original and the fork for years and even then it was usually pretty okay.

Oh I never knew, but it seems true. On his Wikipedia page both researches are mentioned. It’s so impressive how these researchers are behind so many different but interesting papers.

Machine learning and compression have always been closely tied together. It’s trying to learn the “rules” that describe the data rather than memorizing all the data.

I remember implementing a paper older than me in our “Information Theory” course at university that treated the creation of a decision tree as compression. Their algorithm considered sending the decisions tree and all the exceptions to the decision tree and the tree itself. If a node in the tree increased the overall message size, it would simply be pruned. This way they ensured that you wouldn’t make conclusions while having very little data and would only add the big patterns in the data.

Fundamentally it is just compression, it’s just a way better method of compression than all the models that we had before.

EDIT: The paper I’m talking about is “Inferring decision trees using the minimum description length principle” - L. Ross Quinlan & Ronald L. Rivest

I’m on Arch (actually a converted Antergos) and I have an NVIDIA card as well. My first attempt a few months ago was horrible, bricking my system and requiring a bootable USB an a whole evening to get Linux working again.

My second attempt was recently, and went a lot better. X11 no longer seems to work, so I’m kinda stuck with it, but it feels snappy as long as my second monitor is disconnected. I’ve yet to try some gaming. My main monitor is a VRR 144Hz panel with garbage-tier HDR. The HDR worked out of the box on KDE Plasma, with the same shitty quality as on Windows, so I immediately turned it off again. When my second monitor is connected I get terrible hitching. Every second or so the screen just freezes for hundreds of milliseconds. Something about it (1280x1024, 75Hz, DVI) must not make Wayland happy. No settings seem to change anything, only physically disconnecting the monitor seems to work.

Not sure about satisfactory, considering the map is always the same. So the only sources of randomness are starting at another location in the same map or playing differently yourself

I bought a ThinkPad new in 2014 for my study for like 1200 euro’s. She’s still happily purring today. Around 2019 I made the mistake of emptying a cup of tea into the ThinkPad accidentally and then holding it upside down to get the water out. I think I should’ve just let it leak out of the bottom since the laptop has holes for that, but I panicked. This broke the keyboard, but not the rest of the laptop. I got an official new keyboard for like 100 euro’s which came with a tool and the simple instructions, and since then everything has been working flawlessly.

So I recommend ThinkPads, although I can’t really say anything about compatibility of new models

My first experience with the Sims was jumping behind a random computer at some kind of event that was running the Sims 1. Most of the family had just died because the previous person behind the PC had let the house burn down. Needless to say, I was a bit confused. I’ve played the Sims quite a bit after that, and I honestly like messing around with it.

I don’t think I’ve ever played a game without cheating a lot of money. I don’t like that the Sims that I made have to go off to work or school, so usually I just build a big fence around the property to keep them all there. From there on it used to devolve into chaos when I was younger. Building huge mazes to access basic necessities, launching fireworks indoors, etc. Nowadays im a bit more behaved though.

Imo the Sims 4 is the best nowadays. The older ones are showing their age. That being said, the Sims 4 is definitely in need of some competition. It’s inexcusably buggy sometimes, and I personally think there’s a lot more that can be done with a game like this. Hopefully the upcoming competitors can spark some fire into this genre.

I got randomly recommend “Kena: Bridge of Spirits” recently by Steam and decided to go for it. I just finished the story and it was definitely a good recommendation. Hard enough to make me work for it, which I always like. It is kinda short though, finished it in like 12 hours. It’s a bit janky at times with the camera and jumping, but overall a great experience.

What’s wrong? I find this a reasonable result. Most people looking for megabyte to bytes are actually looking for mebibytes, since the mega- prefix is literally just times a million but a lot of programs actually list mebibytes as “megabytes”.

Hmmm yeah, now that you mention it I do remember a few occasions of launching soy milk throughout the kitchen. Still I prefer it over the second one though. After it’s been opened once, it’s much less in the way.

Many of the new bottle caps I encounter will actively push back into the closed position, meaning I have to keep them out of the way when pouring if I don’t want to pour over the cap. Since I tend to encounter them on drink cartons rather than bottles, because I don’t drink soda etc, it becomes even more annoying. Bottles you can turn whichever way, but drink cartons need to be kept at a certain angle for optimal pouring. Quite often the cap is in the way and there isn’t really a nice place to put it.

This is even more frustrating because I never lost these caps anyway, I always threw them away with the packaging. I understand that it probably helps in the bigger picture, but for me personally it solves nothing and is incredibly annoying.

Edit: two examples

This one is fine, it snaps into a position that’s handy and out of the way:

This one is very annoying. It’ll stay in this position and requires constant force to keep out of this position. When opening or closing the packaging the attachment point also rotes, meaning it’s always in the wrong place:

True. Guess I misread. I’ve already switched to 36 hours and I totally aim to go lower once I earn more. Work to live, not live to work

Disagree. I used to spend time on more energy-intensive hobbies like programming and music production. But I’ve had mono and COVID in 2020 and I’ve never felt the same thereafter. Also working 40 hours a week drains a lot of energy

Yeah sports were my first attempt to solve it. I’m running twice a week usually and have done a few half marathons now. It’s helped a bit, but my energy is still not amazing. It’s probably related to having issues with mono and COVID in 2020, I’ve never been the same since then. Working 40 hours per week didn’t help either.

I’m supposed to have energy as an adult?! I have way more time than energy. Most of that time is spent doing useless shit like watching YouTube because I’m too exhausted to do anything useful

I recently tried to get Wayland working. Followed a simple guide to enable some NVIDIA boot parameter. Somehow it fucked my complete grub and I couldn’t boot until I messed around a fair bit with live usbs. Cost me a whole evening.

So I guess what Wayland is missing is normal support from the GPU manufacturers.

I’m not a hundred percent sure, but afaik it has to do with how random the output of the GPT model will be. At 0 it will always pick the most probable next continuation of a piece of text according to its own prediction. The higher the temperature, the more chance there is for less probable outputs to get picked. So it’s most likely to pick 42, but as the temperature increases you see the chance of (according to the model) less likely numbers increase.

This is how temperature works in the softmax function, which is often used in deep learning.

How is Spotify a scam? I can probably at most buy one CD per month for the same price as Spotify. Yet Spotify gives unlimited access to good quality versions of almost every song out there. Even with raised prices it’s still a way better deal for most consumers than buying music directly.

Personally I tend to also buy a few albums a year, because I like owning them and I like supporting the artists. But the convenience of having every track at your fingertips is hard to beat