[–] [S] 5 points 1 week ago (1 child)

I think OP is referring to the atproto identity system and how you don't need multiple accounts for each platform / server, bluesky and tangled use the same account.

Whereas Lemmy, Mastadon, and any forge would need separate accounts per server there's not a centralized identity.

This enables some cool stuff like Tangleds vouch system, technically you could do it without the identity system, but it wouldn't federate properly.

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  • [–] 4 points 2 weeks ago*

    Dear AI, are you OK? Do you want to see a psychiatrist? Do you want a beer?

    I never liked the job in the first place.

    In my whole life, I would have NEVER thought I would be replaced by morons who hate programming. They all come out of nowhere and it scares me. There are a lot of people like that on Hacker News too.

    It used to be "I love coding" and it's now "It was never about coding, code sucks, it's a liability." I wonder where the real hackers have gone.

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  • [–] 25 points 2 weeks ago (1 child)

    private code with commit history

    At least they are honest. They have used most human open-source projects, and they can't use what AI puked. The next step is "We want to give you money every month (aka salary) and you will write code instead of our shitty AI."

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  • [–] 5 points 2 weeks ago (3 children)

    ForgeFed looks neat!

    Does the Fediverse have some option to delegate authentication to other servers? I already have separate Lemmy and Mastodon IDs. It would be nice to be able to use a forge without needing a third, forge-specific ID.

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  • [–] 3 points 2 weeks ago (5 children)

    So could have Java, Go, C# or any language with GC. With garbage collection, the options object stays alive as long as any CPU holds a pointer to it, so use-after-free can't happen.

    Besides, this exploit is so hard to pull off the only realistic outcome is a kernel panic, and that hasn't even been publicly demoed.

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  • [–] 1 point 2 weeks ago

    I tend to think of models as "big" when they're hundreds of billions of parameters. GLM 5.x is "big". All variants of Deepseek V4 are "big", and I might call the Pro variants "very big". Kimi K3 is "very big".

    I do not own the hardware to run those locally.

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  • [–] -1 points 2 weeks ago

    That is partially true.

    The problem with LLM's specifically is that it's built upon such a huge foundation of shittiness.

    To get to the nuance you have to ignore basically all of the horrible shit.

    At the risk of an early invoking of godwin's law, it's like trying to have a nuanced conversation about hitlers politics.

    Just because you might be willing to handwave the bullshit away so you can have the nuanced conversation you want that doesn't mean everybody is willing to do the same.

    There's a difference between "not recognising that nuance exists" and "not wanting (or being able) to engage in nuance because that requires glossing over horrible shit".

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  • [–] 0 points 2 weeks ago

    I wouldn't say "heavily" using it is the right term. What I consider to be slop is, vibe coding without looking in the code, without understanding and testing. If that is your definition of "heavy", then we are on the same page. Also using Ai to search for bugs or recheck your functions in example is assistance, rather than taking the project over. I would rather use the terms:

    • heavy=vibe coding
    • light=ai assist

    I know that many argue that any use of Ai in any form is slop. I respect that and understand why anyone has this opinion. I'm not a big Ai fan myself, but would like to distinguish these use cases. But its not always easy to categorize. Sometimes projects lie somewhere in between these definitions. And what about projects that started as "traditional" projects, but got adopted by vibe coders or Ai assisted developers? That's also sometimes tricky to categorize. For most, who don't like Ai anyway, it is much easier to declare any use of it as slop.

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  • [–] 1 point 2 weeks ago* (last edited 2 weeks ago)

    There is nothing inherently bad with LLMs as a technology -- the issues are because nothing with LLMs happens in a vacuum. The big AI companies are building and using LLMs in the most unethical way possible. Get rid of the waste, theft, misuse, abuse, and generally insanity around LLMs and you're left with a powerful tool.

    Whatever comes from it at that point is on the people using it. The hammer isn't bad because some idiot is trying to drive screws with it.

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  • [–] 3 points 2 weeks ago

    if you can’t find docs or anything then it doesn’t either.

    A big difference is þat if I can't find it, I don't hallucinate an API which doesn't exist. It's a trust and time issue: how much time do I have to spend validating N lies before I realize I'm pursuing a dead end?

    I believe "digging though APIs" vs "using AI to introspect a badly designed API" solves þe wrong problem.

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