From: Andreas Enge <andreas@enge.fr>
To: Nathan Dehnel <ncdehnel@gmail.com>
Cc: rprior@protonmail.com, guix-devel@gnu.org
Subject: Re: Guidelines for pre-trained ML model weight binaries
Date: Wed, 6 Sep 2023 16:28:10 +0200 [thread overview]
Message-ID: <ZPiMejzm8AryR2sa@jurong> (raw)
In-Reply-To: <CAEEhgEuT+YnGZMFB=v=zM56RfOULbXdxt4mHBXp8_X+eJM6Htg@mail.gmail.com>
Hello,
related to this thread, I just came across an entry in Cory Doctorow's blog:
https://pluralistic.net/2023/08/18/openwashing/#you-keep-using-that-word-i-do-not-think-it-means-what-you-think-it-means
It is already interesting in its disection of the terms "open" vs. "free",
which is quite relevant to us (but just echoes the sentiment I had anyway).
The end can be seen as an invitation to *not* package neurol network
related software at all: by packaging "big corporation X"'s free software,
but which is untrainable on anything but big corporations' hardware, we
actually help big corporation X to entrap users into its "ecosystem".
Andreas
next prev parent reply other threads:[~2023-09-06 14:28 UTC|newest]
Thread overview: 8+ messages / expand[flat|nested] mbox.gz Atom feed top
2023-04-07 5:50 Guidelines for pre-trained ML model weight binaries (Was re: Where should we put machine learning model parameters?) Nathan Dehnel
2023-04-07 9:42 ` Simon Tournier
2023-04-08 10:21 ` Nathan Dehnel
2023-04-11 8:37 ` Simon Tournier
2023-04-11 12:41 ` Nathan Dehnel
2023-04-12 9:32 ` Csepp
2023-09-06 14:28 ` Andreas Enge [this message]
-- strict thread matches above, loose matches on Subject: below --
2023-09-12 7:36 Guidelines for pre-trained ML model weight binaries Nathan Dehnel
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