Machine learning is like having a billion extra interns, not one Einstein, to make effective ads

When we harness machine learning’s ability, we’ll make better, more relevant, and more effective ads.

Think of it like this: Using machine learning is like having a billion interns working for you, not a single Einstein coming up with the perfect solution. You have to figure out how to use them which requires assigning them tasks and translating their output into something useful. Without you, the interns would be lost.

The path to better advertising is teaching the interns how to win

Imagine your interns are playing a game of Breakout, that foundational computer game in which the player controls a paddle to keep a bouncing ball in play, aiming to destroy that pesky layer of bricks at the top of the screen.

For machine learning to work, it needs to:

The first thing the interns need to learn is what it means to “win.” In Breakout, this means highlighting the score and telling the interns that higher is better.

The next thing they need to learn is how to win. As they keep playing, they’ll discover that repeatedly attacking one column until the ball “breaks out” into the space above the bricks is the most efficient strategy. This gives them a stable set of rules to play within.

Finally they need a big enough data set to emerge victorious. If you give them 10 minutes, they’ll probably lose, badly.