The headline feels like clickbait. Does MLPerf also benchmark power consumption/cost per submission? It's not particularly illuminating that if you use a 10k GPU cluster, you can train things quickly and a "per chip" comparison is vague.
For most people the bottom line is cost and availability anyway - does it matter if a TPU is twice as slow if it costs half as much? I think I read somewhere that Apple Silicon is actually one of the most efficient platforms to use for development (e.g. a tricked out Mini makes quite a good inference server); I've been able to train recent object detection models on my M2 without much trouble (and it's much cheaper than paying for cloud time).
For most people the bottom line is cost and availability anyway - does it matter if a TPU is twice as slow if it costs half as much? I think I read somewhere that Apple Silicon is actually one of the most efficient platforms to use for development (e.g. a tricked out Mini makes quite a good inference server); I've been able to train recent object detection models on my M2 without much trouble (and it's much cheaper than paying for cloud time).