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Cake day: September 26th, 2026

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  • Yeah I used to think the whole “At home data center” guys were insane but personally I’m digging up my old GPU’s to get a small rig going. Nothing insane but enough to run some light weight models.

    1. The AI techies were right, this is a revolutionary technology and 2. The companies that own it are evil in a no-joke-actually-evil-like-comic-book-evil kind of way. they-will-destroy-the-climate-and-world-just-to-be-the-one-that-did-it kind of way. Humans-are-too-expensive-kill-them type of way.

    Time to build your rigs and pull down some open source models before the criminals (openai, et al) stick telemetry in them to track your usage. Get your own wiki reader while you’re at it…





  • NotAnOtter@lemmus.orgtoMemes@sopuli.xyz•What AI art reveals
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    6 days ago

    I’ve recently heard some AI Music that is objectively just good.

    Like it sounds real, feels real, the lyrics have deep meaning, and so on. I hate it, and wish it didn’t exist. But fact is “I hate AI art because it’s bad art” just doesn’t really make sense anymore. You can hate it for many other reasons but the quality of the product is very good.




  • NotAnOtter@lemmus.orgtomemes@lemmy.world•Almost at 200k!
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    8 days ago

    Nah.

    If you view corporate social media like fb/twitter/reddit as a morally wrong + negative influence on society, then this is a moral win thus worth celebrating.

    Especially when you add in that the main barrier to any social media product gaining traction is first hitting that critical mass of enough posts to make it worth returning to -> habit forming + habit replacing.










  • This is the thing I’m trying to advocate people to understand. It’s not that they were wrong about AI a year ago - AI has changed in radical ways people couldn’t confidently predict within just a year.

    The AI coding agents a year ago DID create slop that would dillute your code base. The AI coding agents today generally don’t.

    It’s becoming increasingly less valuable to combat your LLM and scrutinize it’s output. You can provide more market value by assuming it’s 95% correct, doing some manual verification, and architecting it in a way that leads to low integration complexity. The OOP principles are still relevant - abstract, encapsulate, etc.

    I swear I’m not an AI bro despite the above comment being somewhat pro-AI. I’m just trying to be pragmatic about the state of our field.