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GNU Gneural Network

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31–40 of 111 posts

Re: GNU Gneural Network

#31

Post by sseveran »

raverbashing wrote: post #17
semisight wrote: post #6

Earlier quoted context omitted.

Almost all of the open source software in the area is permissive-licensed, and relies on non-free components (CUDA). To be honest, I'm not sure how Gneural plans to compete with those packages without support from CUDA or cuDNN, all of which are distinctly not open source.

Yeah, you don't depend on CUDA/cuDNN, but of course you can use them if you want it to be fast But the CPU fallback is there

Its going to need to use CUDA or it will not be competitive with alternatives. CUDA makes training networks more than an order of magnitude faster.

Re: GNU Gneural Network

#32

Post by fche »

riscy wrote: post #28
fche wrote: post #26

The "ethical motivations" section is out of place here. Its moaning about "money driven companies" (as though money were a bad thing), or "monopoly" (which does not exist in AI), just reflects badly upon the project.

The monopoly _does_ exist in AI: machine learning is entirely data driven, and companies like Facebook and Twitter quite literally have investors throwing money at them because they have such valuable data for that purpose. Google is no different.

"Monopoly" does not mean "two companies have lots of knowhow that competitors might like".

Re: GNU Gneural Network

#33

Post by tburmeister »

latenightcoding wrote: post #12
perfectfire wrote: post #9

Earlier quoted context omitted.

There's already FANN: which is more mature and has bindings for 28 other languages: http://leenissen.dk/fann/wp/language-bindings/ I maintain the C# wrapper.

I have used FANN from Perl, amazing library. I'm still glad there is some AI software under GNU's belt and the source code for "gneural networks" is pure C and way easier to follow (for now)

It doesn't have quite the same feature set, but I wrote a simple, and I think "clean" neural net library for Python but with a pure C engine under the hood - could be pretty easily adapted to use directly from C.

https://github.com/tburmeister/pyneural

Re: GNU Gneural Network

#34

Post by arnorhs »

- It's nice that GNU is taking on such a project

- FANN seems like a pretty good alternative

- The value of the software at the big "monopolies" lies within the data, not necessarily the software

- This needs to be in some publicly accessible repo. Downloading a zip file and submitting patches? I thought we, as a society, were over that way of building OSS.

Re: GNU Gneural Network

#36

Post by [deleted] »

_delirium wrote: post #3

I agree with the general motivation that having too much AI research in the hands of software companies who keep it proprietary harms transparency and progress. But there is already a lot of neural-network free software, so why another package? For example, these widely used packages are free software, and seemingly more featureful: http://torch.ch/ , http://www.deeplearning.net/software/theano/ , http://pybrain.org/…

[deleted]

Re: GNU Gneural Network

#38

Post by cJ0th »

fche wrote: post #26

The "ethical motivations" section is out of place here. Its moaning about "money driven companies" (as though money were a bad thing), or "monopoly" (which does not exist in AI), just reflects badly upon the project.

I think they stay within reason. IMO they don't say that being money driven is bad. It is rather that big, money driven companies can pose a problem. Maybe there is no monopoly on AI but there is certainly a monopoly on, for instance, social network data.

However, I find it quite amusing (and perhaps "out of place") that the maintainer uses a gmail address.

Re: GNU Gneural Network

#39

Post by riscy »

fche wrote: post #32
riscy wrote: post #28

Earlier quoted context omitted.

The monopoly _does_ exist in AI: machine learning is entirely data driven, and companies like Facebook and Twitter quite literally have investors throwing money at them because they have such valuable data for that purpose. Google is no different.

"Monopoly" does not mean "two companies have lots of knowhow that competitors might like".

Monopoly does mean "when a specific person or enterprise is the only supplier of a particular commodity [...] which relates to a single entity's control of a market" (Wikipedia)

Data is the commodity. There is nowhere else you can get good raw data about, say, what people were publicly discussing last week, except through Twitter, in order to guess the stock market. Much of that data is closed off or incomplete even through their API. There is no other option except to create another Twitter.

Re: GNU Gneural Network

#40

Post by mindcrime »

_delirium wrote: post #3

I agree with the general motivation that having too much AI research in the hands of software companies who keep it proprietary harms transparency and progress. But there is already a lot of neural-network free software, so why another package? For example, these widely used packages are free software, and seemingly more featureful: http://torch.ch/ , http://www.deeplearning.net/software/theano/ , http://pybrain.org/…

I agree with the general motivation that having too much AI research in the hands of software companies who keep it proprietary harms transparency and progress. But there is already a lot of neural-network free software, so why another package?

Not only is there a lot out there, a lot of it was released by companies like IBM[1], Google[2], Yahoo[3], Baidu[4], Microsoft[5], etc. So while I'm generally sympathetic to the FSF's position, this case almost seems like a bit of a reversal of things: there doesn't seem to be a problem with for-profit companies taking the fruits of the labors of volunteers and building on top of it... instead, we have a surplus of riches, released as Open Source by a bunch of big companies. It just happens that most of it is under a permissive license like the ALv2.

Of course, one could suggest that that state of affairs isn't natural and/or sustainable, and that this doesn't negate the issues the FSF is dedicated to. So I support this effort, even if it seems redundant on some level at the moment.

[1]: http://systemml.incubator.apache.org

[2]: http://tensorflow.org

[3]: http://yahoohadoop.tumblr.com/post/139916563586/caffeonspark...

[4]: https://github.com/baidu-research/warp-ctc

[5]: https://github.com/Microsoft/CNTK

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