These are three of the biggest problems facing today's AI

These systems don't just require more information than humans to understand concepts or recognize features, they require hundreds of thousands times more, says Neil Lawrence, a professor of machine learning at the University of Sheffield and part of Amazon's AI team. Once they've been trained, they can be incredibly efficient at tasks like recognizing cats or playing Atari games, says Google DeepMind research scientist Raia Hadsell. A solution to this might be something called progressive neural networks -- this means connecting separate deep learning systems together so that they can pass on certain bits of information. One way of doing this is revisiting an old, unfashionable strand of artificial intelligence known as symbolic AI or Good Old-Fashioned Artificial Intelligence (GOFAI), says Murray Shanahan, a professor of cognitive robotics at Imperial College London (and also the scientific advisor on Ex Machina).