1) It seems to somewhat conflate "more power" and "an order of magnitude more training data". I don't think there is any particularly strong evidence that more training data is the key. We know from things like AlphaGo that AIs are using training data very inefficiently. Humans learn to play grandmaster level Go with many less games than it takes a computer; arguably orders of magnitude less data. We need better graphics cards/chips.
2) The evidence to date is that every time we add an order of magnitude more FLOPS we get transformative improvements in performance. AI can now make a decent-enough attempt at every field of endeavour humans are active in; including arguably superhuman performance at artistic work and being much better read and more reasonable conversationalists than the average person. It is quite challenging to name a field of endeavour where AI isn't becoming superhuman in practice, let alone in theory with enough computational power to call on.
At this point I think the onus is very much on the people who think AI won't improve to justify themselves. This is the most obvious trend I've seen in my lifetime.