That's not the point (as I understand it). The point is that many instances of NP-Hard problems are, in truth, easily solved.
To give an accessible example, consider the problem of finding a factor of an integer. I know this isn't NP-Hard, but it's something most people can easily think about.
If you choose a random large integer, odds are it has a small factor. 50% of the time it's divisible by 2, and most numbers (in a very real sense) or divisible by 2, 3, 5, or 7.
So most of the time a randomly chosen number is easy to find a factor of. In a similar way, most real-world instances of NP-Hard problems are actually easy to find a solution for. The proportion of difficult instances shrinks as the instance size increases[0]. Specifically, if you have an instance of SAT generated from a real-world situation, the likelihood is that it's not actually that hard, so even if it's large, an off-the-shelf SAT solver might be able to dash off a solution.
So when confronted by an NP-Hard problem don't just instantly give up. Choose an algorithm that has a go, and there's a good chance you'll get a solution.
[0] There are formal, unproven conjectures about this.
To give an accessible example, consider the problem of finding a factor of an integer. I know this isn't NP-Hard, but it's something most people can easily think about.
If you choose a random large integer, odds are it has a small factor. 50% of the time it's divisible by 2, and most numbers (in a very real sense) or divisible by 2, 3, 5, or 7.
So most of the time a randomly chosen number is easy to find a factor of. In a similar way, most real-world instances of NP-Hard problems are actually easy to find a solution for. The proportion of difficult instances shrinks as the instance size increases[0]. Specifically, if you have an instance of SAT generated from a real-world situation, the likelihood is that it's not actually that hard, so even if it's large, an off-the-shelf SAT solver might be able to dash off a solution.
So when confronted by an NP-Hard problem don't just instantly give up. Choose an algorithm that has a go, and there's a good chance you'll get a solution.
[0] There are formal, unproven conjectures about this.