Purely from a hardware advantage standpoint Alphago runs on TPUs, and Google asserts these ASIC units offer "an order of magnitude better-optimized performance per watt for machine learning."[0] Facebook doesn't seem to have an equivalent afaik.
That doesn't make TPUs better at achieving performance, just cheaper. My bet is on the size of the team. FB only put in 2 people, or so it seems, while Google invested 10x more man-time.
It most certainly does mean they are better at achieving performance. The real headline of the optimization bit is that they are capable of more ops per second, not that they just use less energy and are therefor cheaper. To use a more open/mainstream analog with freely available metrics, look at the performance difference in bitcoin mining between GPUs and ASIC units.
