On one hand, we have racks of servers (1920 CPUs and 280 GPUs) [1] using megawatts (gigawatts?) of power, and on the other hand we have a person eating food and using about 100W of power (when physically at rest), of which about 20W is used by the brain.
[1] http://www.economist.com/news/science-and-technology/2169454...
Probably on the order of one megawatt or so.
http://inhabitat.com/infographic-how-much-energy-does-google...
1920 CPUs (a 4-core haswell from 2013 is around 170Gflops). 280 GPUs (previous gen Nvidia K series peaks at around 5200GFLOPS). That's 1,782,400Gflops or around 150,000x more processing power. If they were running latest-gen hardware, then the would be closer to 200,000x faster.
Given that Moore's law is slowing down and the size of the system, we're a long way from considering putting that in a smartphone.
AlphaGo is still a very new program (two years since inception). It will get significantly better with more training, or, equivalently, it will stay at the same strength while running on much less hardware.
Don't read too much into what one particular snapshot in its development cycle looks like. Humanity has had hundreds of millions of years to maximize the efficiency of the brain. AlphaGo has had two years. It's not a fair comparison, and more importantly, it's not instructive as to what the future potential of AI algorithms looks like.