AI can speed up a lot of the manual labour needed to bring even an almost dead, 10-year-old device back to life. My Xiaomi Mi Max 2 (oxygen, MSM8953) was dead. With AI help and my own knowledge, I ported/rewrote the missing drivers, and it now runs Nura (postmarketOS) with working camera, torch, SIM, phone calls and SMS. Only the loudspeaker is still broken.

Everything is up for anyone who wants to install it, or to understand the changes and manually write the patches for mainline: https://github.com/sv1sjp/mi-max2-oxygen-msm8953-nura-drivers Testing, feedback and PRs welcome.

  • emergencyfood@sh.itjust.works
    1·
    8 hours ago

    one of the models was being portrayed as finding a mathematical proof which was actually in it’s training data. The original authors will not get the credit, academic support, exposure and funding they would have gotten otherwise.

    If the original authors have published their findings somewhere (journal / conference / arXiv), they will definitely get the credit from other mathematicians.

    it’s epistemology and source are an important part of it.

    I don’t know about all AIs, but deepseek does cite sources. You can always cross-check them.

    • GeorgimusPrime@lemmy.world
      1·
      4 hours ago

      Unfortunately the proof found by the LLM combines work by different teams of mathematicians that cannot individually be published as proofs. It’s the equivalent of a scoop in investigation journalism by someone who was spying on journalists instead of doing any investigating. It’s on lemmy/wired: https://lemmy.world/post/52843754

      It’s good that some do cite sources, however one major problem with generative AI is that it can produce volumes of output much faster than they can be verified. “You can always cross-check” is not viable at scale, and by the time LLM output gets cited, it becomes a quagmire potentially unlimited levels deep.

      LLM output should never be treated as original until they can show their work transparently.