Before revision:  This is the find and claim of [S{\o}rensen et al., Nature 532] and it features prominent in the abstract of the paper. It leads the authors to conclude that 'playerssucceed where purely numerical optimization fails, and analysis of their solutions provide insights into the problem of optimization of a more profound and general nature. ' While it seems clear from the presented data that human players have indeed outperformed a particular implementation of the Krotov algorithm (and, according to [S{\o}rensen et al., Nature 532] , as a consequence also algorithms like CRAB and evolutionary approaches which perform worse than Krotov), there is no reason to believe that this finding is of any particular significance.
After revision:  This is the find and claim of [S{\o}rensen et al., Nature 532] . We also verify the theoretical analysis presented by D. Sels, that gives a theoretically derived protocol that outperforms all players. We add a comparison with gradient ascent or GRAPE. Starting from uniform random values, GRAPE outperforms all players by a large margin. GRAPE works at least as well as the methods from [S{\o}rensen et al., Nature 532] , as a consequence also algorithms like CRAB and evolutionary approaches which perform worse than Krotov), there is no reason to believe that this finding is of any particular significance.