But the null-hypothesis remains that it is junk. The hypothesis is that it is not junk, borrowing evidence from neural networks in which (1) things that look like noise are actually distributed representations and (2) in which noise improves robustness and facilitates exploration. This evidence is possibly transferable because both processes, neural network training and evolution can be formalized as a high-dimensional optimization problem (one being informed by gradient information while the other just randomly mutates and exploits ensemble effects of recombination).