31337

joined 1 year ago
[–] 31337@sh.itjust.works 7 points 5 days ago

I remember liking Opposing Force and Blue Shift too.

[–] 31337@sh.itjust.works 20 points 6 days ago

Happens when you're not proud of what you're contributing to. Probably most workers, tbh.

[–] 31337@sh.itjust.works 10 points 1 week ago (1 children)

Idk. Maybe it's because I learned OOP first that it makes more sense to me; but OOP is a good way to break down complex problems and encapsulate them into easily understable modules. Languages like Java almost force everyone on the project to use similar paradigms and styles, so it's easier for everyone to understand the code base. Whenever I've worked on large non-OOP projects, it was a hard-to-maintain mess. I've never worked on projects such as the Linux kernel, and I'm hoping it's not an unmaintainable mess, so I'm pretty sure it's possible to not use OOP on large projects and still be maintainable. I am curious if they still use OOP concepts, even though they are not using strictly OOP.

I also like procedural python for quick small scripts. And although Rust isn't strictly OOP, it obviously borrows heavily from it. Haskell is neat, but I haven't used it enough to be proficient or develop good sense of application architecture.

I've done production work in C, but still used largely OOP concepts; and the code looks much different than code I've seen that was written before C++ was popular.

[–] 31337@sh.itjust.works 12 points 1 week ago

I haven't checked it out in years. From my understanding, IPFS aims to be a distributed filesystem that kinda works like Bittorent. If you access a file, you then seed it. Last time I checked it out, the project was jumping on the crypto bandwagon... Just checked out their website now, and don't know WTF it is.

[–] 31337@sh.itjust.works 1 points 2 weeks ago

Yeah, I agree. I do use Flatpaks, Snaps, and Appimages sometimes if I can't find a suitable deb repo/package. Flatpak is the best out of the three because they do try to avoid too much duplication through runtimes. I also use Docker quite a bit, which has similar issues (and benefits).

[–] 31337@sh.itjust.works 2 points 2 weeks ago (2 children)

I assume the "kill it" comment was a little tongue-in-cheek. On small SBCs, like a Pi, or old hardware, it could be a problem. I've seen people with flatpaks taking up 30GB of space, which is significant. I'm not sure how much RAM it wastes. I assume running 6 different applications that have loaded 6 different versions of Qt libraries would also use significantly more RAM than just loading the system's shared Qt libraries once.

[–] 31337@sh.itjust.works 0 points 2 weeks ago (5 children)

Wastes RAM and disk space (compared to package-manager installed applications) by storing more libraries on disk and loading them into RAM rather than just using the libraries already installed on the distro. It's probably better than Snap and Appimage though.

[–] 31337@sh.itjust.works 1 points 2 weeks ago* (last edited 2 weeks ago)

Meh, startups and businesses are capitalist organizations, and I think the idea of patents is questionable outside capitalism, so these wouldn't really be a good metrics. I'd guess the richest countries "innovate" the most because they can support more risky endeavors. The U.S. is the capitalist imperial core, so it probably innovates the most. Other capitalist nations like Haiti, probably not so much.

The best measure of innovation would probably be something like scientific publications. China wins by raw numbers, Vatican City wins per-capita (???).

[–] 31337@sh.itjust.works 2 points 3 weeks ago

It’s neither okay nor sustainable

Source?

You realize mass deportations would decimate the economy? Some cities are 10% undocumented immigrants; Florida is 5% undocumented immigrants. Undocumented immigrants are a significant part of the U.S. economy and culture.

It would also be a horrific endeavor. Police going door-to-door demanding documentation. Probably social surveillance similar to Nazi Germany (along with all the false accusations). 4 million child U.S. citizens would have their parents hauled away. There will need to be concentration camps to hold all those people before travel (if they would actually get around to doing that).

"Law breakers," isn't a very good argument. Everybody breaks the law (speeding, jay-walking, etc). The system is currently working as intended, and encouraging people to break the law to acquire an easily exploitable workforce. Incidentally, undocumented immigrants commit far less crime than citizens.

[–] 31337@sh.itjust.works 7 points 1 month ago

Thought this was a Republican ad for a second. Similar language and appeal to fear and ignorance.

[–] 31337@sh.itjust.works 2 points 1 month ago

Yann LeCun would probably be a better source. He does actual research (unlike Altman), and I've never seen him over-hype or fear monger (unlike Altman).

[–] 31337@sh.itjust.works 3 points 2 months ago

This is more complicated than some corporate infrastructures I've worked on, lol.

 

AI firms propose 'personhood credentials' to combat online deception, offering a cryptographically authenticated way to verify real people without sacrificing privacy—though critics warn it may empower governments to control who speaks online.

 

I've recently noticed this opinion seems unpopular, at least on Lemmy.

There is nothing wrong with downloading public data and doing statistical analysis on it, which is pretty much what these ML models do. They are not redistributing other peoples' works (well, sometimes they do, unintentionally, and safeguards to prevent this are usually built-in). The training data is generally much, much larger than the model sizes, so it is generally not possible for the models to reconstruct random specific works. They are not creating derivative works, in the legal sense, because they do not copy and modify the original works; they generate "new" content based on probabilities.

My opinion on the subject is pretty much in agreement with this document from the EFF: https://www.eff.org/document/eff-two-pager-ai

I understand the hate for companies using data you would reasonably expect would be private. I understand hate for purposely over-fitting the model on data to reproduce people's "likeness." I understand the hate for AI generated shit (because it is shit). I really don't understand where all this hate for using public data for building a "statistical" model to "learn" general patterns is coming from.

I can also understand the anxiety people may feel, if they believe all the AI hype, that it will eliminate jobs. I don't think AI is going to be able to directly replace people any time soon. It will probably improve productivity (with stuff like background-removers, better autocomplete, etc), which might eliminate some jobs, but that's really just a problem with capitalism, and productivity increases are generally considered good.

 

Summary: Meta, led by CEO Mark Zuckerberg, is investing billions in Nvidia's H100 graphics cards to build a massive compute infrastructure for AI research and projects. By end of 2024, Meta aims to have 350,000 of these GPUs, with total expenditures potentially reaching $9 billion. This move is part of Meta's focus on developing artificial general intelligence (AGI), competing with firms like OpenAI and Google's DeepMind. The company's AI and computing investments are a key part of its 2024 budget, emphasizing AI as their largest investment area.

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