NewOldGuard

@NewOldGuard@lemmy.ml

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⁨Comment⁩ on ⁨Have you know???.⁩ ⁨⁨5⁩ ⁨days⁩ ago⁩:
It depends on the model but I’ve seen image generators range from 8.6 wH per image to over 100 wH per image. Parameter count and quantization make a huge difference there. Regardless, even at 10 wH per image that’s not nothing, especially given that most ML image generation workflows involve batch generation of 9 or 10 images. It’s several orders of magnitude less energy intensive than training and fine tuning, but it is not nothing by any means.
⁨Comment⁩ on ⁨Have you know???.⁩ ⁨⁨6⁩ ⁨days⁩ ago⁩:
The training is a huge power sink, but so is inference (I.e. generating the images). You are absolutely spinning up a bunch of silicon that’s sucking back hundreds of watts with each image that’s output, on top of the impacts of training the model.