That was fascinating, thanks for sharing.
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 quit
On 2023-07-04, zamfofex wrote:
>> On 07/03/2023 6:39 AM -03 Simon Tournier wrote:
>>
>> Well, I do not see any difference between pre-trained weights and icons
>> or sound or good fitted-parameters (e.g., the package
>> python-scikit-learn has a lot ;-)). As I said elsewhere, I do not see
>> the
> On 07/03/2023 6:39 AM -03 Simon Tournier wrote:
>
> Well, I do not see any difference between pre-trained weights and icons
> or sound or good fitted-parameters (e.g., the package
> python-scikit-learn has a lot ;-)). As I said elsewhere, I do not see
> the difference between pre-trained neura
Hi,
On Sun, 02 Jul 2023 at 21:51, Ludovic Courtès wrote:
> Someone™ has to invest time in studying this specific case, look at what
> others like Debian are doing, and seek consensus on a way forward.
Hum, I am probably not this Someone™ but here the result of my looks. :-)
First, please note
Hi,
Simon Tournier skribis:
> Somehow, if we do not have guidelines for helping in deciding, it makes
> harder the review of #63088 [1] asking the inclusion of lc0 or it makes
> hard to know what to do about GNU Backgamon.
>
> On these specific cases, what do we do? :-)
Someone™ has to invest t
Hi Ludo,
On ven., 26 mai 2023 at 17:37, Ludovic Courtès wrote:
>> Well, I do not know if we have reached a conclusion. From my point of
>> view, both can be included *if* their licenses are compatible with Free
>> Software – included the weights (pre-trained model) as licensed data.
>
> We disc
> To me, there is no doubt that neural networks are a threat to user
> autonomy: hard to train by yourself without very expensive hardware,
> next to impossible without proprietary software, plus you need that huge
> amount of data available to begin with.
>
> As a project, we don’t have guideline
Hello,
Simon Tournier skribis:
> On sam., 13 mai 2023 at 12:13, 宋文武 wrote:
>
>> Hello, zamfofex submited a package 'lc0', Leela Chess Zero” (a chess
>> engine) with ML model, also it turn out that we already had 'stockfish'
>> a similiar one with pre-trained model packaged. Does we reached a
>
Hi,
On sam., 13 mai 2023 at 12:13, 宋文武 wrote:
> Hello, zamfofex submited a package 'lc0', Leela Chess Zero” (a chess
> engine) with ML model, also it turn out that we already had 'stockfish'
> a similiar one with pre-trained model packaged. Does we reached a
> conclusion (so lc0 can also be acc
Simon Tournier writes:
> Since it is computing, we could ask about the bootstrap of such
> generated data. I think it is a slippery slope because it is totally
> not affordable to re-train for many cases: (1) we would not have the
> hardware resources from a practical point of view,, (2) it is a
Nathan Dehnel writes:
> a) Bit-identical re-train of ML models is similar to #2; other said
> that bit-identical re-training of ML model weights does not protect
> much against biased training. The only protection against biased
> training is by human expertise.
>
> Yeah, I didn't
should be included as any other data and the lack of debootstrapping is
> not an issue for inclusion in this particular cases.
>
> The question for inclusion about this pre-trained ML model binary
> weights is the license.
>
> Last, from my point of view, the tangential question
binary weights. I do not know if they fit the
store.
Well, that’s my opinion on this “Guidelines for pre-trained ML model
weight binaries”. :-)
(*) And Ricardo is training hard! See [4] and part 2 is yet published,
IIRC.
1:
https://www.cs.cmu.edu/~rdriley/487/papers
>From my point of view, the tackle of such biased weights is not via
re-learning because how to draw the line between biased weights,
mistakes on their side, mistakes on our side, etc. and it requires a
high level of expertise to complete a full re-learning.
This strikes me as similar to being in t
Hi,
On ven., 07 avril 2023 at 00:50, Nathan Dehnel wrote:
> I am uncomfortable with including ML models without their training
> data available. It is possible to hide backdoors in them.
> https://www.quantamagazine.org/cryptographers-show-how-to-hide-invisible-backdoors-in-ai-20230302/
Thanks
I am uncomfortable with including ML models without their training
data available. It is possible to hide backdoors in them.
https://www.quantamagazine.org/cryptographers-show-how-to-hide-invisible-backdoors-in-ai-20230302/
Hi,
On Thu, 6 Apr 2023 at 15:41, Kyle wrote:
> I have only seen situations where the optimization is "too entailed with
> randomness" when models are trained on proprietary GPUs with specific
> settings. Otherwise, pseudo-random seeds are perfectly sufficient to remove
> the indeterminism.
F
>Since it is computing, we could ask about the bootstrap of such
>generated data. I think it is a slippery slope because it is totally
>not affordable to re-train for many cases: (1) we would not have the
>hardware resources from a practical point of view,, (2) it is almost
>impossible to tac
Hi,
On Mon, 03 Apr 2023 at 18:07, Ryan Prior wrote:
> Hi there FSF Licensing! (CC: Guix devel, Nicholas Graves) This morning
> I read through the FSDG to see if it gives any guidance on when
> machine learning model weights are appropriate for inclusion in a free
> system. It does not seem to of
On Mon, 3 Apr 2023, Nicolas Graves via "Development of GNU Guix and the GNU
System distribution. wrote:
Just to be precise on llama, what I proposed was to include the port of
Facebook code to CPP, (llama.cpp, see ticket 62443 on guix-patches),
which itself has a license.
The weight themselves
On 2023-04-03 18:07, Ryan Prior wrote:
> Hi there FSF Licensing! (CC: Guix devel, Nicholas Graves) This morning I read
> through the FSDG to see if it gives any guidance on when machine learning
> model weights are appropriate for inclusion in a free system. It does not
> seem to offer much.
>
Hi there FSF Licensing! (CC: Guix devel, Nicholas Graves) This morning I read
through the FSDG to see if it gives any guidance on when machine learning model
weights are appropriate for inclusion in a free system. It does not seem to
offer much.
Many ML models are advertising themselves as "o
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