Just like Lee Se-dol is a Go grandmaster, beats Gary Kasparov at chess and can also get a perfect score in Pac-Man, right? I mean, if you can't do all of those things then are you even a human-level intelligence?

This just illustrates that surpassing "human level" performance is a silly and arbitrary benchmark, because there is no such thing as general human level performance. But I bet Kasparov would be pretty good at Go, and Sedol would be pretty good at chess.

Universality is the real hard problem of AI. In the long run, a mediocre AI that does a lot of different things is far more useful that most targeted "superhuman" AIs. Most domains simply don't require better-than-human performance, but could still reap tremendous benefits from automation.

Agreed. It's great that we have ___domain-specific approaches that can beat humans in their ___domain (and that we're learning how to make these approaches more generic so that, with re-training, they can adapt to new domains), but the real "oh snap" moment will be when we build something that's barely-adequate but widely adaptable. Something with the adaptability of a corvid or an octopus, say. If we get to that level, it'll mean we've discovered the "universal glue" that joins specialist networks together into a conscious entity.

You forget to add "running on 20 watts of power". It's not reasonable to require it to run on a single machine, when brain performance is estimated to be more than 10 petaflops.

I don't know if you're being sarcastic or not. If not, I suggest you look at the cartoon at http://www.kurzweilai.net/robot-learns-self-awareness

Add Pacman and Pitfall to the list. Humans have played perfect games of both. My understanding is DeepMind performed poorly on those games.