I agree with you as well as with the response to your comment, in that both nVidia and Google are engaging in misleading claims about their TPUs. But I'd like to add two points:

- I don't think they can get away with it when it comes to Top-500 rankings. Those rankings are based on LINPACK scores and this supercomputer would end up not scoring high enough and will be placed in the right spot in the list. So it's not a big concern to me.

- "ML isn't scientific computing" goes both ways. Sure tensor-tera-ops are not teraflops, they're specific to operations involving artificial neural networks (ANNs). But when you take the claims from the past about how much computing power it'll take for rivaling that of a human brain, and folks came up with 100 petaflops, or 1 exaflop. Well those should not be called "f"lops either. Because when it comes to brain inspired computing, ANN tensor-tera-ops are a more reliable number than FP32 or FP64. And if it's 100 peta-ops of ANN compute, well we're already past that, and can easily create a supercomputer with 1 tensor-exa-ops. And that means we have reached the hardware capacity required to emulate human-level intelligence in a machine (i.e., the only thing missing is the right set of algorithms).

Conclusion: Tensor-tera-ops are not FP ops and should not be used for placement in the Top-500 list. But tensor-tera-ops have enough significance that it warrants creating a new list Top-500-Tensor and ranking Tensor-supercomputers on that list.