I don't have a link or full context, but it turned out that the dev of tessaract (open source program for fediverse sites, involving at least spam and blocking tools) had a functionality in the program that fetched their own block list from their site. But this blocksite was blocking a huge amount of users, fediverse domains, and anything with any keywords which would be anything political, some porn/sexual terms like Yuri, and lots more. This block was completely invisible the ones running the program and would also give fediverse instances that were blocked a generic failed to connect error instead of saying blocked, preventing the fediverse instances from talking.

Seeing the above, it seems like the dev didn't handle this discovery in any good way either and retaliated but doing this ddos thing.

I support knowing SIMD, but I think it's worth mentioning that with good design depending on language and compiler you can get SIMD for free by auto vectorization.

At least Rust does this, and let's you get away not touching explicit SIMD at all. It's of course more fragile since you don't always know if it's done or not, and they can be skipped for minor changes in code and a, but with good loop hygiene you'll get a lot of it for free.

For truly fast implementations though, handmade SIMDis usually better and faster if done correctly. And can do much more than auto vectorization can.

Honestly there's so many weird flowers out there it can be hard to tell truth from fiction. Yeah these are AI generated, but look at all the other flowers that are real:

• Lambs ear
• Sea holly
• Teddy Bear sunflowers are real even
• Protea "Little Prince"
• Hoya Multiflora

Lots of very interesting flowers out there.

I'm still quite new to Linux, using CachyOS (arch). What's the best alternative to AUR, I saw someone mention Flatpak because it is at least somewhat sandboxed. Anyone have some best practices given AUR doesn't seem to good of a choice?

The bigger paid models or potentially the local ones if given access to search the web can probably get you the right answers. The big ones have pretty much memorized half the internet, but can still be wrong so pushing them to verify their answers.

But the harder part is trusting what they say regardless. I can't just take an answer for truth, and unless I can verify the statement (fact checking myself, looking up the source, running/testing the code, etc) then it gets harder to do anything with AI. This is the thing I hate about AI in general, people just take whatever they say at face value. Lawyers with fake citations, random people asking chatgpt about random facts and such. Its a tool that people put too much faith in to do thinking for them.

Are you using real agents or the free chats on the web, because the latter ones are really dumb. Even when you ask them to search the web for basis you don't get much success.

But they do work, maybe not as a full replacement but my god the amount of boilerplate I can avoid in creating unit tests from scratch. Extracting and finding information in the code base is also useful, not everything is an easy text search of tracing a few code paths. It's an incredible tool for these kinds of work.

If it becomes harder to tell the difference then it also means it's closer to matching reality. And todays AI can do very impressive "reasoning", managing to debug complex issues I have had.

The most important part is that you as developer is fully responsible and can stand behind what they do and deliver using AI agents.

Sorta first time Linux user, picked CachyOS because it came with friendly installer and startup install guide/automation. Unlike last time i tried Linux to run some python project on the GPU I never managed to install CUDA.

CachyOS promised out of box support, wine/proton directly, and the selection of default tools got me far along the Windows migration. So far no issues even compiling programs that need CUDA drivers and more. Haven't really gamed a lot, but this OS is supposed to be good for that.

My worst one, have working code, make a change, it broke. Revert it, still broken...

The issue was that all icons and stuff randomly got a wrong size in the GUI. Just had to restart the machine to fix it, but I was really pulling my hair out when I somehow broke things backwards in time.

In principle I agree>!!<, but in practice it's not clear cut.

The main one is some historic accuracy, I say some because the color of the skin doesn't really matter for most things set in some time period or era where a race wasn't particularly present.

The second one is just how it looks, we'll see how well casting Snape for the new Harry Potter goes as it seems to be Harry's father is bullying the weird black kid. Another one is the Artemis Fowl movie which cases a woman as leader for the Fairy unit, which undermines the actual accomplishment of Holly being the first to get here place as a woman. It's not the end of the world, but it changes the tone and plot.

Probably not the end of the world, but these problems fall on the same line as other poor adaption/remake choices that actively hurt the story is try to tell. Not everyone can fit into a role in a story, and I don't think that's systematic discrimination. And I reiterate, it largely depends on the setting of the story. For most things, gener and race is not a big factor.

Lumine(boot manager) on my PC remembers the last boot choice, so when I choose windows it keep going to that until I choose Linux again. Have about 5 seconds to press a button before it auto starts. Seems like the most sane alternative here.

Adversarial reviews are also great ways to prune bad ideas and assumptions from plans. Have helped me out greatly and made the better LLMs often go "plan said do X, but doing that is a unknown huge risk that may take longer then the rest of the plan".

The superpowers plugin does the brainstorm, qa, design plan, implementation plan, implement, review quite well. It should aid the process of actually doing feature type work. I also add adversarial reviews into the process, saves a lot of time debugging what went wrong after implementation.