Humans also have millions of years of evolution that have effectively pre-trained the structure and learning ability of the brain. A baby isn't born knowing a language but is born with the ability to efficiently learn them.
The upshot is that once you've found an architecture that is already biased towards solving a specific problem, then the training of the weights is faster and results in better performance.
From the abstract, "...In this work, we question to what extent neural network architectures alone, without learning any weight parameters, can encode solutions for a given task.... We demonstrate that our method can find minimal neural network architectures that can perform several reinforcement learning tasks without weight training. On a supervised learning domain, we find network architectures that achieve much higher than chance accuracy on MNIST using random weights."