Generally it is easy to agree with the sentiment that machine learning is being used to solve problems where it isn't really needed. But on the other hand, the same argument could have been used when computers initially came along: "you don't need a supercomputer to calculate this function, I can do it with pen and paper faster". So the real value in projects like this is not that you can now drive 2d car game with a neural network, but that neural networks just took another tiny step forward and demonstrate that their capability to minimize error functions is in principle transferrable to real life problems no matter how stupid, and one day those small steps will have accumulated and neural nets will (and already have) supercede many limits that humans have.