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In his book The Most Human Human: What Artificial Intelligence Teaches Us About Being Alive, Brian Christian explained that “the first branch of computer science was what’s come to be known as computability theory, which doesn’t care how long a computation would take, only whether it’s possible or not. Take a millisecond or take a millennium, it’s all the same to computability theory.” However, as Christian also noted, “computer scientists refer to certain problems as intractable – meaning the correct answer can be computed, but not quickly enough to be of use.”

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Comments (1)
This article is an incoherent mishmash of concepts that are only superficially related to each other. Computation theory is about the mathematical nature of the problem, the "intractable" are what they are because the time to process is polynomial (time increases geometrically with each new data point). This has nothing to do with things that "Moore's law" may make more practical today than they were two years ago, and is more about subjective ideas of "timely" than anything mathematical. Put simply, the cost/time to solve "intractable" problems will double (or worse with each single additional data item to process. The linear time constrained issues, what you talk about in the second half of the article, you can increase the data points by 100% or more, before the time/cost doubles. Finally, "currency" has nothing to do with either of these, it is how frequently a set of data is refreshed, it is only very tenuously related to the question of how long that refresh took to run. The last paragraph ... I'm not even sure what to say about that.
Posted by | Thursday, March 06 2014 at 9:04AM ET
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