On the other hand, such distributed planning is incredibly inefficient - how much resources are wasted by Uber competing with Lyft competing with Taxis, by FedEx competing with UPS competing with post office, etc.? The point is, it's a tradeoff - efficiency with single points of failure vs. resilience at a cost of huge waste.

What resources are wasted? Perhaps some innovative ideas are being duplicated at worst?

Goods are produced that no one needs. The market gets randomly stuck at local minimas that lead, for instance, to throwing away tons of food because it's more profitable to do that than to donate to those in need. You get tons and tons of duplication by companies competing with each other over a limited set of customers, which also feeds the advertising industry that wastes resources on zero sum games. In current model, the economy is regulated implicitly, by feedback loops fighting against each other creating a dynamic equilibrium. It's inherently less efficient than regulating explicitly. My point is that while humans are not capable of regulating on such scale and thus have to rely on implicit methods, optimization algorithms run on real-time data feeds may in fact be able to regulate explicitly.

Getting stuck in local minima happens in centrally planned systems too.

You are correct that things like advertising are (sometimes) zero sum - specifically, advertising based on irrational criteria. (Advertising which transmits useful information, e.g. "taxis suck and Uber exists", is not zero sum.)

But you also gloss over one of the big benefits of a non-centralized system - correctly finding the utility function. In a centrally planned system, your utility function needs to properly identify what tradeoffs people would make if they had the choice. This is not easy, and modern computing doesn't help very much here.

In contrast, consumer choice via price systems handles this nicely.