In 2012 the world learned of a surprising research project inside Google’s secretive X lab. A giant simulation of three million neurons learned to recognize cats and people in pictures, without human help, just by looking at images taken from YouTube.
The people behind the project founded a new research group known as Google Brain inside the company’s search division. They and researchers elsewhere soon proved to the world that artificial neural networks, a decades-old invention, could understand images and speech with unprecedented accuracy (see “Google Puts Its Virtual Brain to Work”). The success of deep learning, as the technique is also known, prompted Google and others to invest heavily in artificial intelligence and has even led some experts to claim we should prepare for software that’s smarter than humans (see “What Will It Take to Build a Virtuous AI?”).
Yet Google’s cat detector was in some ways a dead end. The recent successes of deep learning are built on software that needs human help to learn—something that limits how far artificial intelligence can go.
To read more, click here.