Large period PRNGs such as Mersenne Twister require good seeding otherwise the initial output in the sequence may not seem to be high-quality, at least for the first few words (and in the way that is useful in production). For example, Marsaglia talked about seeding methods in his May 2003 Communications of the ACM article . It feels like a chicken/egg situation. You need a source of high-quality random bits in order to seed your generator, so you can create a source of high-quality random bits.
I was wondering:
Is von Neumann unbiasing a legitimate way to defend against poor seeding of large-period PRNGs? In other words, if I apply von Neumann unbiasing to the bitstream output of Mersenne Twister, does the quality of the stream still depend on how I seeded it?
 George Marsaglia, "Seeds for random number generators." Communications of the ACM, 46(5):90–93, 2003 (ACM page.)