space-invaders.JPG

Google's Deep Q conquers Space Invaders. (Google DeepMind/Square Enix Ltd./YouTube)

Bill Gates and Stephen Hawking are worried about artificial intelligence. "I don't know why some people are not concerned," Gates recently said.

Well, the ranks of the concerned have just swelled significantly -- to include the world's gamers.

Google's Deep Q Network has learned how to play Space Invaders and many other classic arcade games without being pre-programmed to do so, an important step forward for artificial intelligence. Writes London's The Telegraph: "Demis Hassabis of Google's artificial intelligence arm DeepMind said the ultimate goal was to create a computer which had the mental capabilities of a toddler."

No offense, gamers. After all, Hassabis says Deep Q is superior to IBM's Deep Blue computer that beat chess champ Garry Kasparov in 1997. That's some toddler.

The key difference between the two computer programs: Deep Blue was loaded with chess moves and chess-theory information. Deep Q was not given any "training" or even told the rules or objectives of the games it played.

In some instances, Deep Q proved to be remarkably inventive. In the game Breakout, in which the player tries to bust through a brick wall, Deep Q created a tunnel "so that the ball passed through and could hit more bricks." The Deep Q designers themselves hadn't even thought of that tactic.

The "deep neural" network was designed to learn like a human being. "Our brains make models that allow us to learn and navigate the world," Hassabis says. "That's exactly the type of system we're trying to design here."

It's called "deep reinforcement learning." By randomly manipulating the controls of the game, Deep Q figured out what to do and what worked. The results of the tests were published in the journal Nature.

"It's the first artificial agent that is capable of learning to excel over a diverse array of challenging tasks," Hassabis says.

Bill Gates can take some comfort in the results: the machines aren't yet ready to make us their slaves. Deep Q sucked at Ms. Pac-Man, for example, because that game requires "planning and foresight." And it can't take what it learned from one game and apply it to another, which is something toddlers have no problem doing.

Needless to say, this test of deep-reinforcement learning wasn't really about a computer mastering arcade games. The Google designers hope to use the technology in self-driving cars and, of course, to improve Google searches.

-- Douglas Perry