Re: Concern for: A humble draft policy on "deep learning v.s. freedom"
Hello everybody,
this is a complex - and interesting! - discussion, and a difficult
problem to tackle, but an important one. Addressing it adequately
would be a great acheivement for Debian.
Le Sat, Jun 08, 2019 at 10:07:13PM -0700, Mo Zhou a écrit :
>
> 1. Free datasets used to train FreeModel are not required to upload
> to our main section, for example those Osamu mentioned and wikipedia
> dump. We are not scientific data archiving organization and these
> data will blow up our infra if we upload too much.
how about storing only the data used to train the version that is
released in Stable, and keeping this data in a dedicated archive, to
avoid bloating mirrors ? There was a thread on debian-project on how to
use Debian money, and I think that it could be a useful case.
For the versions in Unstable and Testing, the role of the package
maintainer would be to ensure that the data is still available for
download.
> 2. It's not required to re-train a FreeModel with our infra, because
> the outcome/cost ratio is impractical. The outcome is nearly zero
> compared to directly using a pre-trained FreeModel, while the cost
> is increased carbon dioxide in our atmosphere and wasted developer
> time. (Deep learning is producing much more carbon dioxide than we
> thought).
Optionally, we could even consider re-training the release candidate at
the approach of the Freeze, for the sake of demonstrating that the
training process functions well.
Stable point update might not need to be retrained depending on what the
patches address.
Have a nice day,
Charles
--
Charles Plessy
Debian Med packaging team,
http://www.debian.org/devel/debian-med
Akano, Uruma, Okinawa, Japan
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