Deep-learning applications typically rely on a trained neural net to accomplish their goal (e.g. photo recognition, automatic translation, or playing go). That neural net uses what is essentially a large collection of weighting numbers that have been empirically determined as part of its training (which generally uses a huge set of training data) A free-software application could use those weights, but there are a number of barriers for users who might want to tweak them for various reasons. A discussion on the debian-devel mailing list recently looked at whether these deep-learning applications can ever truly be considered "free" (as in freedom) because of these pre-computed weights—and the difficulties inherent in changing them.
Over the last few months, it became clear that the battle over PEP 572 would be consequential; its scale and vehemence was largely unprecedented in the history of Python. The announcement by Guido van Rossum that he was stepping down from his role as benevolent dictator for life (BDFL), due in part to that battle, underscored the importance of it. While the Python project charts its course in the wake of his resignation, it makes sense to catch up on where things stand with this contentious PEP that has now been accepted for Python 3.8.
The recent announcement by Guido van Rossum that he was stepping away from his "benevolent dictator for life" (BDFL) role for Python was met with some surprise, but not much shock, at least in the core-developer community. Van Rossum has been telegraphing some kind of change, at some unspecified point, for several years now, though the proximate cause (the "PEP 572 mess") is unfortunate. In the meantime, though, the project needs to figure out how to govern itself moving forward—Van Rossum did not appoint a successor and has left the governance question up to the core developers.