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* An algorithm, even if impractical, may show new techniques that may eventually be used to create practical algorithms.
* Available computational power may catch up to the crossover point, so that a previously impractical algorithm becomes practical.
* An impractical algorithm can still demonstrate that conjectured bounds can be achieved, or that proposed bounds are wrong, and hence advance the theory of algorithms. As Lipton states:<ref name="seminal"/>{{quote |This alone could be important and often is a great reason for finding such algorithms. For example, if tomorrow there were a discovery that showed there is a factoring algorithm with a huge but provably polynomial time bound, that would change our beliefs about factoring. The algorithm might never be used, but would certainly shape the future research into factoring.}}
== Examples ==
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