I'm interested to see if neural network parameters become the new "binary blob". While in theory you could always retrain the network yourself, actually doing so takes a lot of work fiddling with the network's hyperparameters and requires significant computing resources.
[1] http://www.robots.ox.ac.uk/~vgg/research/very_deep/
[2] "On a system equipped with four NVIDIA Titan Black GPUs, training a single net took 2–3 weeks depending on the architecture." - arXiv:1409.1556
It's still interesting and cool to see! Just not what I thought it was when I clicked on the link.
Open source does not just mean you can see the source. From Wikipedia[0]:
"Open-source software is computer software with its source code made available with a license in which the copyright holder provides the rights to study, change, and distribute the software to anyone and for any purpose."
In fact, looking closely at that definition, isn't practically nothing open source?
"Open-source software is computer software with its source code made available with a license in which the copyright holder provides the rights to study, change, and distribute the software to anyone and for any purpose."
I.e. public domain? Any other license lives precisely to limit those rights of distribution, no?
Anyway, just pedantry. I see your point. Learn something new every day.
Re: Open source vs Free software, this is a matter for debate (the tendency being too associate Free software with the more copyleft/viral/gnu-ish side of things), but I would definitely say that both involve explicit licencing, as opposed to potentially implicit " all rights reserved " style regional copyright.
The L part clarified the type of freedom, as the FL clarifies that it's not just OSS.