> I keep hearing about outrageous training times for GPUs on the order of weeks with something like 4-8 GPUs This is for training a competitive model from scra

> I keep hearing about outrageous training times for GPUs on the order of weeks with something like 4-8 GPUs This is for training a competitive model from scratch on a fundamental problem like image recognition. If you don't care about the last 1-2%, it's possible to train a useful model in a few hours (but still on a GPU). > is anyone actually using CPUs instead There are useful things you can do without a GPU. For example, "Transfer learning", which can be as simple as chopping off the last layer of someone else's GPU-trained model and substituting your own, can be done on a CPU in reasonable time. This is because you typically need less data and because far fewer parameters need to be fit. For example, HBO's "Hotdog/Not-hotdog" app was done this way. See their description of "V1" here: https://medium.com/@timanglade/how-hbos-silicon-valley-built-not- https://medium.com/@timanglade/how-hbos-silicon-valley-built...