AI vs ML illustrated in NPR story

nice NPR story illustrating a conceptual and methodological 
difference between AI and ML, using some of the more 
press-grabbing, (human) game-beating systems:

http://www.npr.org/blogs/alltechconsidered/2015/01/08/375736513/look-out-this-poker-playing-computer-is-unbeatable

this story's pretty interesting in general but one particular 
part grabs my attention:

Oren Etzioni, the head of Seattle's Allen Institute for 
Artificial Intelligence, says:

Each game-winning computer involves "very, very different 
computer software," he says. In other words, they're highly 
specialized tricks for winning at particular games.

There's a quantum leap between special-purpose AI systems like 
Watson or Deep Blue and the truly awesome success of deepmind, 
which uses deep reinforcement learning to beat all of these 
Atari games ( https://www.youtube.com/watch?v=EfGD2qveGdQ ) 
using raw pixel values as input.  Machine learning focuses on 
learning general methods that can solve MANY problems, rather 
than the (usually rules-heavy) AI approaches found to beat 
particular challenges.