Disclosure: I work on Google Cloud. I didn’t downvote you, but presumably people disagree with “Here’s an FPGA” as comparable to being given a working piece of

Disclosure: I work on Google Cloud. I didn’t downvote you, but presumably people disagree with “Here’s an FPGA” as comparable to being given a working piece of hardware. That is, would you have said that the best comparison to a V100 is this same FPGA box? I (and others) get what you were trying to say: TPUs are ASICs that aren’t general purpose at all, so an FPGA is a better comparison than a more general purpose GPU. As an end user, that just isn’t true though. If someone hands you an f1.16xlarge, you have to build your own psuedo-chip for machine learning. While with this offering, TensorFlow handles the acceleration / offload for you.