I agree, but at the same time you're kind of missing the point. Adding more and more examples to the pattern recognizer is like adding more and more epicycles (for dealing with special cases) into the theory of celestial object movement, where a more general and simpler theory will do a better job.

But it's true we don't precisely know how to "find and represent the better theory", if it's at all possible (most likely not) and what the exact trade-off is.

Also note that my argument doesn't necessarily rely on computational difficulty of SAT - even if we limit to some "simple" subset of SAT instances, we might see that the pattern recognizer is unable to learn these problems correctly.