Sure, in looking at what it would cost to replicate this: https://arxiv.org/pdf/1704.01444.pdf https://arxiv.org/pdf/1704.01444.pdf They say they used four Ti

Sure, in looking at what it would cost to replicate this: https://arxiv.org/pdf/1704.01444.pdf https://arxiv.org/pdf/1704.01444.pdf They say they used four Titan X cards for a month. I was actually looking at google cloud machine learning since I thought being targeted to tensorflow would be the most cost effective. But it's 0.49/hour per ML training unit, or 1.47/hour per GPU. A basic gpu gives 3 training units, so I thought that something approximately similar would require 12 training units, which comes to something like $4000+ a month. Maybe I completely misunderstood the resources being offered though, because you are right that cloud engine costs seem much lower. I'll have to revisit the math here, though it worries me that it's not at all clear that a K80 will be much faster than a Titan X for a given problem. E.g. https://www.amax.com/blog/?p=907 https://www.amax.com/blog/?p=907. It would also be really nice to get some pricing and benchmarks for the new TPUs, assuming they are priced better. Maybe part of the problem is that vendors are not making it remotely easy to even understand what performance you'll actually get for a given price.