semi [he/him]

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Joined 5 years ago
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Cake day: September 3rd, 2021

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  • dpi (dots per inch) is a measurement of camera resolution, not of the speed of the sensor processing. So the full processing goes like this:

    60 times per second (60 Hz), the optical sensor in the mouse takes an image at 4000dpi resolution. That information is then processed and modulated onto a radio wave that swings up and down 2. 4 billion times per second (2.4 GHz) - but the information is still only sent 60 times per second, so less often than would be of a modern gaming screen updating 144 times per second.




  • In computational biology / biotechnology, LLMs are being trained on biological sequences and can then be used to generate new genes or genetic variants. These genes can be placed into bacteria who are then fed with e.g. sugar to make them produce various valuable molecules from renewable resources instead of from crude oil using conventional chemistry. There is also work on enabling plastic biodegradation this way.










  • For inference (running previously-trained models that need lots of RAM), the desktop could be useful, but I would be surprised if training anything bigger than toy examples on this hardware would make sense because I expect compute performance to be limited.

    Does anyone here have practical recent experience with ROCm and how it compares with the far-more-dominant CUDA? I would imagine that compatibility is much better now that most models are using PyTorch and that is supported, but what is the performance compared to a dedicated Nvidia GPU?