Concrete example: I own skis. But if I'm going on a ski vacation instead of a day trip, I rent them. That decision has nothing to do with the cost to rent skis

Concrete example: I own skis. But if I'm going on a ski vacation instead of a day trip, I rent them. That decision has nothing to do with the cost to rent skis vs. what they sell for, and everything to do with the fact that I can rent skis for about the same as what it would cost me to transport my own skis and boots to Breckenridge and back. I suspect that there is something like that (only not at all) going on with machine learning kit: If you've got exactly one person training models, and they're doing it all the time, then yeah, it's cheaper to own your own hardware. If you've got several people all trying to share the training rig, then you start having to worry about all the costs associated with scheduling time, delays if someone else got their first (especially if they're doing deep learning and will be monopolizing the server for upwards of a week), etc. Once you factor all those full-lifecycle costs in, the cloud might start to look relatively cheaper.