Thanks for the feedback. As more and more new ML system architectures emerge over the next few years, these performance comparisons will get even more complicat

Thanks for the feedback. As more and more new ML system architectures emerge over the next few years, these performance comparisons will get even more complicated. Chip-to-chip comparisons and server-to-server comparisons are arbitrary, and it will sometimes be difficult to define these boundaries at all. Our impression is that top-line performance comparisons independent of system size (like the comparison in the blog post) and performance-per-dollar comparisons are the easiest to understand, but we're certainly open to other ideas.