But be careful, his interpretation of P versus NP is rather light-hearted (but OK, given that it&#x27;s not his speciality).  He says:<p><i>For example, breaking almost any cryptographic code can be phrased as an NP problem.  So if P=NP—and if, moreover, the algorithm that proved it was “practical” (meaning, not n1000 time or anything silly like that)—then all cryptographic codes that depend on the adversary having limited computing power would be broken.</i><p>But the parenthetical remark is not a negligible detail.  The class P contains those O(n^1000) algorithms, and also much, much slower ones.  Being in P does not mean at all &quot;efficient&quot;.  This is one of the reasons why many people (e.g. Knuth) say that P=NP is not crazy.  The class P is so huge, that it must certainly contain extremely clever algorithms that reduce NP to P.  Yet, there are may be no practical implications of this equality.