I've been collecting examples of the abuse and misunderstanding of the no-free-lunch theorems, and this is a pretty flagrant one:
> "Any simple major enhancement to human intelligence is a net evolutionary disadvantage." The lesson is that Mother Nature know best. Or alternately, TANSTAAFL: there ain’t no such thing as a free lunch.
The NFL theorem (for search and optimisation) states that all algorithms for searching a fixed problem space perform the same, in expectation, when you don't know anything about the fitness (cost) structure over that space. There is a tradeoff in a sense: an algorithm can only do better than random search on some instances of the problem if it does worse on others. There's no sense of a tradeoff between multiple objectives on a single instance of a search problem, which is what gwern is talking about.
I believe it's actually a reference to the general expression "There ain't no such thing as a free lunch" and has little to do with the computer science theorem of a similar name.
> "Any simple major enhancement to human intelligence is a net evolutionary disadvantage." The lesson is that Mother Nature know best. Or alternately, TANSTAAFL: there ain’t no such thing as a free lunch.