Every accomplishment will seem obvious in retrospect. Who here honestly thought neural networks were going to be a dominant force in board game AI? Sure we cannot extrapolate, but that doesn't mean that we aren't building up effective tools for AI.
The potential for neural networks to learn to play games, by playing each other, has been apparent at least since NeuroGammon (https://en.wikipedia.org/wiki/Neurogammon), in 1989. The "playing each other" mechanism is key, because it allows large-scale training.
The question is, what games happen to be well structured to allow so-called "credit assignment" so that you can know what states lead to wins across a reasonable spectrum of (unknown/unknowable) opponent plays.
According to the OP, it is known that you can do credit assignment in Go. ("For Go itself, it has been well-known for a decade that Monte Carlo tree search (i.e., valuation by assuming randomized playout) is unusually effective in Go.") I did not know that, but if so, it would simplify the Go problem, although the search space remains huge, etc.
The key advancement in AlphaGo seems to be generating a subset good moves, as opposed to randomly selecting them, and determining whether a given configuration has a probability of winning. Monte Carlo Tree Search by itself only gets you to amateur ranks from what I read, but won't beat a pro player. Being able to combine the policy and value networks, and figuring out how to bootstrap and train them was where all the work is.
In hindsight, everything looks like an obvious combination of separate already-known-to-be-good pieces. I don't think this achievement should be hand waved away.
More importantly, the DeepMind folks are being pretty humble about it and not making the big claims everything seems to think they're making.
https://en.wikipedia.org/wiki/Universal_approximation_theore...
Neural networks are an algorithmically simple way to approximate any mathematical function. So, really, why _wouldn't_ you think this?
Ultimately, almost all boardgames can be reduced to mathematical functions.