One of the most interesting things I found in the MIREX results so far has been the good performance of George Tzanetakis in different categories. He scored highest in mood classification, and did well in the other classification tasks.
Since George is well known to have published some of the most frequently cited papers on music classification this isn't really interesting news. However, what's really interesting is that George did so well despite using Marsyas. Marsyas is open source and has been around in the MIR community for as long as I can remember. At the ISMIR 2004 and MIREX 2005 evaluations Marsyas didn't do too well (although, afaik it's always been by far the fastest implementation). Perhaps as a results, I've recently been seeing fewer papers on genre classification using Marsyas as baseline. But given the excellent performance this year, I think it's fair to say it has re-established itself as the baseline for any new music classification algorithm. In fact, it has done so well, that I doubt we will see any papers in the near future which can report significant gains compared to this solid baseline. (Btw, never forget to use an artist filter when evaluating genre classification performance!)