[–] 5 points 8 months ago

Hey it's almost as if you give decision making power to something that doesn't have a concept of mortality or morality it won't take those things into account. Who could have guessed.

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  • [–] 13 points 8 months ago (2 children)

    I love how the movie made in the 80s had a computer that was smart enough to realize nuclear weapons are bad but real life in 2025/26 has real computers that aren't smart enough to figure it out. I think as a species we have all been far to optimistic.

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  • [–] 1 point 9 months ago*

    Judging by what I know about Torvalds, he's a pragmatist. Bases his decisions on technical requirements. Not sure if it's a surprise someone like him tries vibe coding? It'd align with my more fact-driven perspective on the world. I'd also try things and make up my mind. See myself if a tool / programming language / project can be of use for my particular wants and needs... I mean being sceptical about something doesn't necessarily exclude nor include anything.

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  • [–] 2 points 10 months ago

    It's using data over a year old.

    Some of the examples seem like nothingburgers, the Lucy Letby example actually looks like the AI failing "safe" by refusing to make a conclusion.

    (It's also questionable of the BBC to insist that de jure and de facto innocence is the same thing, it probably is in the Letby case, but you wouldn't want it to necessarily make that assumption in, for instance, the OJ Simpson case)

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  • [–] 5 points 10 months ago

    In December 2024, the BBC carried out research into the accuracy of four prominent AI assistants that can search the internet – OpenAI’s ChatGPT; Microsoft’s Copilot; Google’s Gemini; and Perplexity. We did this by reviewing responses from the AI assistants to 100 questions about the news, asking AI assistants to use BBC News sources where possible.

    The answers produced by the AI assistants contained significant inaccuracies and distorted content from the BBC. In particular: …

    51 % significant issues, 19 % factual errors, 13 % altered or invalid quote citations

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  • [–] 1 point 10 months ago

    The article isn't very concrete on what the substance of this Anyway System is.

    The FAQ answered my question though, and it seems mostly about dynamic management of PCs as execution nodes.

    I assume that means I could run the model on one of those PCs as well, despite the article claiming you can use as few as four PCs? Or does this system somehow distribute a single model prompt process into multiple execution pipelines?

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  • [–] 2 points 10 months ago

    A 120b parameter model is small compared to the models running in datacenters. However, this does seem like the current "Moore's Law" for AI. Finding more and more efficient ways to run larger parameter models.

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  • [–] 2 points 10 months ago

    Without understanding how it’s built, how do I know if there’s duplication, dead code, or poor patterns? I used to obsess over this. Now I’m less worried that a human needs to read the code, because I’m genuinely not sure that they do.

    What you do need: simple entry points, explicit code with fewer abstractions, minimal coupling, and linear control flow.

    Seems to be the common simple standard software works well fallacy.

    By “can replace developers”, what do they mean? They don't clarify, only talk about their three success projects.

    We've seen studies of the issues and risks, and discrepancy between user perception and more factual gains. And this post certainly seems like they're not experienced in or thinking of development and maintenance that goes beyond simple standard integration software. Which doesn't make it too surprising they're not concerned about security for those simpler projects either.

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