The human brain can still outperform our best algorithms for a variety of tasks. Some tasks, like object identification, aren't really surprising—our brain itself has been optimized through evolution to be pretty good at this. But there are other classes of problems that are a bit of a surprise, like some forms of optimization.
You might expect a computer to be pretty good at finding optimal solutions. But when it came to figuring out the optimal structure of a protein, people playing the game FoldIt managed to beat some of our best software. Now you can add a second task where our brains come out ahead: figuring out the best way to perform some quantum manipulations. All it took was turning quantum mechanics into a game.
Algorithms often come up short in optimization problems because of how they're structured. It's easiest to think of this idea as a landscape with peaks and valleys. The algorithm simply starts off by picking a large number of random locations within this landscape and then tries to move uphill from each of these locations. Once it finds a collection of peaks, it can compare them to find the highest peak that it has located, which can represent the optimal solution.
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