>> So is it fair to say that deep learning is fundamentally missing something that humans do?
Yes, it's missing the ability to generalise from its training examples to unseen data and to transfer acquired knowledge between tasks.
Like you say, the article describes an experiment where a robot hand learned to manipulate a cube. A human child that had learned to manipulate a cube that well would also be able to manipulate a ball, a pyramid, a disk and, really, any other physical object of any shape or dimensions (respecting the limits of its own size).
By contrast, a robot that has learned to manipulate cubes via deep learning, can only manipulate cubes and will never be able to manipulate anything but cubes, unless it's trained to manipulate something else, at which point it will forget how to manipulate cubes.
That's the fundamental ability that deep learning is missing, that humans have.
Yes, it's missing the ability to generalise from its training examples to unseen data and to transfer acquired knowledge between tasks.
Like you say, the article describes an experiment where a robot hand learned to manipulate a cube. A human child that had learned to manipulate a cube that well would also be able to manipulate a ball, a pyramid, a disk and, really, any other physical object of any shape or dimensions (respecting the limits of its own size).
By contrast, a robot that has learned to manipulate cubes via deep learning, can only manipulate cubes and will never be able to manipulate anything but cubes, unless it's trained to manipulate something else, at which point it will forget how to manipulate cubes.
That's the fundamental ability that deep learning is missing, that humans have.