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  1. 1
    Using a local LLM to clean up a full hard drive●I gave my local LLM a nearly-full SSD and told it to find everything I could safely delete✉newsTechnologyAI1 h ago

    A tech writer describes running a locally hosted large language model on a nearly full SSD, asking it to identify files that could be safely deleted. The piece highlights a practical, off-cloud use of local AI: letting the model scan the drive and suggest disk cleanup targets, reflecting growing interest in running LLMs directly on personal hardware for everyday tasks.

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    AMD driver update boosts Radeon AI performance up to 23%●🤖 AMD boosting AI/LLM performance for Radeon iGPUs as much as 18~23% with Linux 7.4 submitted by /u/Fcking_Chuck [link]MmastodonTechnologySoftware016 h ago

    AMD is delivering significant AI and large language model performance gains for its Radeon integrated graphics, with improvements of roughly 18 to 23 percent arriving via the Linux 7.4 driver. The gains matter for users running AI workloads on budget and portable systems that rely on integrated GPUs rather than discrete graphics cards. Linux users and AI enthusiasts are discussing what the update means for local LLM performance on AMD hardware.

  3. 3
    Local LLM helps hobbyist code a handy tool●Okay my local LLM helped me yesterday to vibecode something really handy. To be honest it did most of the heavy regex liMmastodonTechnologyAI22 h ago

    A developer says a locally run large language model helped him build a genuinely useful script, handling most of the tricky regex work in what he calls vibecoding. He now wants to release the tool publicly but is unsure how to do so on his Codeberg account without violating its terms, and is asking others for advice on the right way to share it.

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