This doesn't solve the data science and machine learning problems, though. You will still have the problem that optimized code paths will be hundreds to thousands to even millions of times faster (on a GPU) than any Python could be, and falling back to pure Python, accidentally or otherwise, will still incur those slowdowns, even if the resulting pure Python code is embarrassingly parallel and that is fully perfectly exploited.

Personally, I wouldn't be surprised all this work gets done on GIL-removal, and the end result is that if you run 10 threads in Python you max out at roughly a 3x performance improvement in your pure Python code (and often get less, I do mean that as a max not an average), with all the memory traffic it is doing. Honestly even if it did perfectly parallelize up to 32 cores, a completely impossible absurdity, it would still be noticeably inferior performance to what many languages will give you on one core. I can't help but think that if you're sitting here waiting with bated breath for the GIL-ectomy to improve your Python performance that that is a sign you should be rewriting your code right now in any number of languages that are simply faster. I very, very strongly suspect that this is going to result in very very disappointing speedups when it is done.