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Yeah, I've also seen several academic papers on performance or "optimization" of existing algorithms which just demonstrate a complete lack of knowledge about how those algorithms are implemented in practice.

For example, there was a paper explaining how you could optimize the GJK algorithm by reducing the number of distance checks required, and in turn the number of square-roots... Despite the fact that everyone (including the authors of the original GJK algorithm) knows that you don't actually need to do a square-root to compare distances...



> Despite the fact that everyone (including the authors of the original GJK algorithm) knows that you don't actually need to do a square-root to compare distances..

Academia's purpose is to produce research, typically measured in publications per unit time. Optimizing one paper leads to a global reduction in the size of the literature by pruning opportunities for subsequent research, harming the overall performance of the system.


how is less and more accurate (read: not done wrong) studies pruning opportunities for future research?

from my view, it becomes easier to make research.

less, more condensed literature is easier to cite and read, as it's "unified".

from there, many other researches can easily base the work off the paper for novel research.

less doesn't necessarily mean worse.




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