I can neither confirm, nor deny that I am in fact D̵̡̮̻̗̖̮͔̜͈̙͖͙͍̺̀̒̍̌̑͐̓͡å̴̲͍̋̉́̀̑͊̎̐̊͡l̴̟̭̳̄̅̕͝͠͝ȩ̸͚̼̘̫̺̻̬̻̮͖̣̬̖̠̗̎̌ ̵̯͕͛́͋͌̀͝͠ͅͅG̷̛͈̩̟̟̠͓̗̘͓͍̽̒̌̔̓̈͗̐̈̿͠͠r̷̘̞̹͂̀̑̋̀͌̍͗̆͝͠͝ͅi̶̡͔͖͍̟̲̮͑̎͌̀̎b̵̡̢̹̗͔̗͍̘̣͊͊̑͒̍̑͌̽͋͌̔͝͝b̷̭̩̩̣͙̺͎̱̗͙͚̩̈́l̸̛͎̼̟̋͆͆͗̓̓̓͘͟ĺ̶̼͇͎̫̮͎̣̳͉̯̊̆̂̓̄̍̃̚e̶̢̡̛̫̣͈̺̾̅͐̾̓͒̚ͅ.̴̫̞̥̒̈̇̓́̾͗̒́̉̔͑

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Cake day: March 4th, 2024

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  • Pay thousands for a Mac computer that may not have the features you want, and never be able to upgrade or repair it, or

    M1 Air costs USD $750 where I live.

    Get a software engineering degree so you can figure out how to install, use and regularly debug Linux. Because even techy people you know that might want to help you don’t know anything about Linux.

    Hyperbole to sell an easily disprovable false narrative. For what?

    Calm down and eat your lunch, Helen.












  • Rusty Shackleford@programming.devtolinuxmemes@lemmy.worldI can't use AMD
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    4 months ago

    Earlier in my career, I compiled tensorflow with CUDA/cuDNN (NVIDIA) in one container and then in another machine and container compiled with ROCm (AMD) for cancerous tissue detection in computer vision tasks. GPU acceleration in training the model was significantly more performant with NVIDIA libraries.

    It’s not like you can’t train deep neural networks without NVIDIA, but their deep learning libraries combined with tensor cores in Turing-era GPUs and later make things much faster.