From the post:
When people realize that I study pure math, they often ask about how to visualize four or more dimensions. I guess it’s a natural question to ask, since mathematicians often have to deal with very high (and sometimes infinite) dimensional objects. Yet people in pure math never really have this problem.
Pure mathematicians might like you to think that they’re just that much smarter. But frankly, I’ve never had to visualize anything high-dimensional in my pure math classes. Working things out algebraically is much nicer, and using a lower-dimensional object as an example or source of intuition usually works out — at least at the undergrad level.
But that’s not a really satisfying answer, for two reasons. One is that it is possible to visualize high-dimensional objects, and people have developed many ways of doing so. Dimension Math has on its website a neat series of videos for visualizing high-dimensional geometric objects using stereographic projection. The other reason is that while pure mathematicians do not have a need for visualizing high-dimensions, statisticians do. Methods of visualizing high dimensional data can give useful insights when analyzing data.
This is an important area for study, but not only because identifications can consist of values in multiple dimensions.
It is important because the recognition of an identifier can also consist of values spread across multiple dimensions.
More on that second statement before year’s end (so you don’t have to wait very long, just until holiday company leaves).
I first saw this in Christophe Lalanne’s A bag of tweets / Dec 2011.