This a great overview - nicely done! It would have been nice to also mention how other implementations of Python like Jython that _don't_ have the GIL, and how they managed to do it.
As for why it hasn't been solved yet...the api for threads and processes is pretty much identical. Since you're just as well off using a process in the majority of cases, that's we we go with.
Actually, the reason it hasn't been "solved" yet has much more to do with the cPython implementation rather than the fact that we can just use multiprocessing. There is a ton of globally shared data in the cPython implementation. Retrofitting a locking scheme granular enough to obviate the need for the GIL while at the same time not negatively impacting single-threaded performance is decidedly non-trivial.
The PyPy guys are making decent progress by attacking the problem from another angle: using software transactional memory to automatically resolve data conflicts that arise from multiple threads mutating data simultaneously.
As for why it hasn't been solved yet...the api for threads and processes is pretty much identical. Since you're just as well off using a process in the majority of cases, that's we we go with.