jeffhykin @ jeffhykin @lemm.ee

Posts

13

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343

Joined

2 yr. ago

I think once you get down to the size of vehicles like this: https://www.youtube.com/watch?v=R2oD1ZHNMFE then they become naturally modular/replaceable. At least in the same way that bikes are. I don't think people really create "modular" bikes they are just naturally swappable. Of course standards are helpful, and I think there is a total lack of standards for golfcart sized enclosed vehicles.

The "front page" of most instances are not interesting to average people or to professionals (e.g. local gov that wants to go open source, like those switching to Mastodon).

Part is lemmy's hot-sort is basically broken as a ranking, another part is bad language filters, another part is that major communities here (fediverse, Linux memes, star trek memes, science memes, etc) are off-putting to out-of-group people because of so many in-group jokes. Its a hard fix.

You should watch the rest, especially the ending, there are some great quotes in there. "There's so much freedom in [suburb]. There's no shops, cafes, theaters, places to eat, schools, or even people. But uhh, that's all part of the freedom; you have the freedom to go somewhere better! like [15min city name]"

This is pretty cool. I've got a couple repos that Microsoft uses for VS Code. I switched one of them to GPLv3, but maybe I'll switch the other to this license.

I think we can agree "Good reseach" is in the how-its-done. I wish journals would chose/require/verify the how-its-done (time frame, resources, hypothesis, method etc) but after that be contractually required publish whatever conclusion is discovered by the team/project they picked and verified.

I know a good bit of micro biology, psychology, and medical trial fields can. But thats about the limit of my "other fields" knowledge.

I guess I should've clarified; in reforcement learning "I was wrong in numerous ways" almost always translates to "unpublishable, try to not be wrong next time". Nobody cares if a reinforcement learning hypothesis didn't work, its only worth publishing if it worked well.

This is why my field (reinforcement learning) is unfortunately not science.

(Can't really publish "hey I tried this algorithm and it didn't work")

Same haha.

I've already started it twice for lemmy, but didn't put in heavy effort yet. I've got a wrapper for nix that helps with common issues, but its on the messy side.

There are so many small GUI apps I want to make but I refuse until I can get Tauri to build an appimage and macos app within nix. It was more than a year ago since I put a lot of effort on that though. If you've got any tips/pointers or examples for tauri I'd be happy to hear them.

Yeah, university is almost certainly going to expect you to be able to install Unreal or Unity, which just isn't possible AFAIK on NixOS. NixOS is very all or nothing. You can't just remove the restrictions for one project and hack something together to hit an assignment deadline. Theres still lots of pain points with LD_PATH and 3rd party binaries.

That said, you can use nixpkgs on non-nixos and still get reliability for Godot and other open source tools. For your case, I highly recommend dual booting, and then using nixpkgs without going full blown nixOS.

This is a bit like asking "how do you cook meat for a lot of people?" Not only does number-of-people and kind-of-meat matter a great deal, but even with that info, there's a million different valid answers and an entire sub-field-ish of science on how to do it.

Based on what little info there is, I'm going to guess that A B testing with groups of experimental features enabled would be best for your case.

Sadly it still causes system instability even if you NEVER need the feature.

You might not need numpy at all, but Pandas needs numpy and Opencv needs numpy. Sometimes pandas needs one version and Opencv needs a different version. Well... python only allows one global verison of numpy, so pandas and opencv fight over which one they want installed, and the looser is forced to use a numpy they were not designed/tested for. Upgrading pandas might also upgrade numpy and break opencv. That causes system instability.

Stable systems like cargo coupld upgrade pandas, have pandas use numpy 1.29 without touching/breaking opencv (opencv would still importing/using using numpy 1.19 or whatever). That stability is only possible if the system is capable of having two versions of the same dependency at the same time.

I feel like they missed the most important point in their abstract and top of their conclusion; why is urban agricultural producing more carbon. The TLDR conclusion is "urban garden = bad". But if done correctly, theres no way a rainwater compost local vegetable using handmade wooden tools burns more carbon than air-freight across the Atlantic.

Its not till much later that they say "If our UA sites sourced all their materials from urban waste, all three forms of UA would be carbon-competitive with conventional agriculture"

And FYI to OP, if you can't install two versions of the same library at the same time (ex: numpy 1.25 and numpy 1.19) then the answer to "has its dependencies under control?" is generally "no".

• Deno (successor to NodeJS) is "yes" by default, and has very very few exceptions
• Rust can by default, and has few but notable/relevant exceptions
• Python (without venv) cannot (even with venv, each project can be different, but 1 project still can't reliably have two versions of numpy)
• NodeJS can, but it was kind of an afterthought, and it has tons modules that are notable exceptions

The more reliable/reproducible the container is the more pain/effort it is to setup. If you don't need reliability, then you don't need containers.

• If you want unbeatable reliability, use nix.
• If you want better-than-nothing use venv/anaconda envs (one or the other, not both)
• If you want the most reliability-per-effort and don't care about performance, use distrobox

Not only in order but also

1. very human-obvious (international 1-1-2020 is not obvious if day-mo-year or mo-day-year)
2. Allows for arbitrary additional levels of precision to be appended. (E.g. year-mo-day-hour-min-sec-etc)

Fair, I did miss that requirement

It is a sad story. Keeping it in legendary meme status is the best way to remember it IMO.