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GNU Gneural Network

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Re: GNU Gneural Network

#101

Post by riscy »

cLeEOGPw wrote: post #98
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.

So this library isn't solving anything then.

I think it solves something (needing a simple, well documented, GPL licensed machine learning framework written in C) but not the major problem faced by those on the cutting edge of machine learning.

Re: GNU Gneural Network

#102

Post by fche »

riscy wrote: post #39
fche wrote: post #32

Earlier quoted context omitted.

"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…

A commodity is a routinely interchangeable product, available from multiple suppliers, competing primarily on price. No, "data" in this context is not that at all. A library of user profiles is the opposite: it's proprietary, unique, massive.

Re: GNU Gneural Network

#103

Post by zymhan »

Aeolos wrote: post #94

http://cvs.savannah.gnu.org/viewvc/gneuralnetwork/gneuralnet... Am I mistaken, or is the source repository for this project just tarballs checked into CVS?

Commit message:

"source"

cvs.savannah.gnu.org/viewvc/gneuralnetwork/gneuralnetwork/gneural_network-0.0.1.tar.gz?view=log

Seems like

Re: GNU Gneural Network

#104

Post by jjawssd »

teythoon wrote: post #96
jjawssd wrote: post #11

Earlier quoted context omitted.

Gneural will compete with Theano sort of like how the GNU Hurd competes with Linux

I know you're just trying to be funny, but I don't think it's funny at all. The Linux kernel undoubtedly many features that the Hurd system lacks, but that is due to the severe lack of manpower of the latter system and the billions of Dollars being poured into the former. On the other hand the Hurd has features that the Linux kernel can never hope to achieve because of its architecture.

I am not trying to be funny. I am dead serious. Aeolos explained it perfectly.

Re: GNU Gneural Network

#105

Post by sseveran »

mindcrime wrote: post #51
frisco wrote: post #45

Earlier quoted context omitted.

For state of the art work "a day or two" is pretty fast for a production network, and that's on one or more big GPUs. Not using CUDA is definitely a dealbreaker for any kind of real deep learning beyond the mnist tutorials. It's common to leave a Titan X to run over a weekend; that would be weeks on a CPU.

Well not using CUDA isn't necessarily synonymous with "use a CPU". There is OpenCL. But still, you have a point even if we might quibble over details. This is why I am very much hoping AMD gets serious about Machine Learning and hoping for OpenCL on AMD chips will eventually reach a level of parity (or near parity) with the CUDA on nVidia stuff.

Its unlikely that AMD is going to be able to make serious inroads in the near future. nVidia has built quite a lead not just in terms of chips but tooling. I had thought a couple of years ago that AMD should be building a competitor to the Tesla. It should be able to build a more hybrid solution than nVidia can given its in house CPU development talent. But I haven't seen them building anything like that and a competitor to nVidia may have to come from somewhere else. In the absence of a serious competitor OpenCL is not very interesting.

Re: GNU Gneural Network

#106

Post by mindcrime »

sseveran wrote: post #105
mindcrime wrote: post #51

Earlier quoted context omitted.

Well not using CUDA isn't necessarily synonymous with "use a CPU". There is OpenCL. But still, you have a point even if we might quibble over details. This is why I am very much hoping AMD gets serious about Machine Learning and hoping for OpenCL on AMD chips will eventually reach a level of parity (or near parity) with the CUDA on nVidia stuff.

Its unlikely that AMD is going to be able to make serious inroads in the near future. nVidia has built quite a lead not just in terms of chips but tooling. I had thought a couple of years ago that AMD should be building a competitor to the Tesla. It should be able to build a more hybrid solution than nVidia can given its in house CPU development talent. But I haven't seen them building anything like that and a compet…

Yeah, and that's sad. I really hate to see this whole monoculture thing, especially since CUDA isn't OSS. :-(

Re: GNU Gneural Network

#107

Post by teythoon »

Aeolos wrote: post #99
teythoon wrote: post #96

Earlier quoted context omitted.

I know you're just trying to be funny, but I don't think it's funny at all. The Linux kernel undoubtedly many features that the Hurd system lacks, but that is due to the severe lack of manpower of the latter system and the billions of Dollars being poured into the former. On the other hand the Hurd has features that the Linux kernel can never hope to achieve because of its architecture.

> The Linux kernel undoubtedly many features that the Hurd system lacks, but that is due to the severe lack of manpower of the latter system and the billions of Dollars being poured into the former. That's why GNU Hurd is essentially a dead project. Sadly it never attracted the attention and manpower necessary for it to survive. > On the other hand the Hurd has features that the Linux kernel can never hope to achieve…

Fault isolation. We're doing it for daemons, we're doing it for web browsers, it is insane we're not doing it for operating system services. I bought a graphic tablet and the first time I plugged it into my laptop the Linux kernel crashed. And this was merely a faulty driver, not even malicious hardware.

Also think of the effort it took to introduce namespaces to all the Linux subsystems. After a decade the user namespace still has problems. This is ridiculously easy on a distributed system, yet very hard on a monolithic one.

Re: GNU Gneural Network

#108

Post by mehrdada »

gcr wrote: post #59
sjtgraham wrote: post #57

Earlier quoted context omitted.

> Good luck collecting 10k hours of transcribed speech I'm sure that nearly every DVD theatrical release has subtitles available. Speech against a wide range of background noise too, e.g. music, explosions, traffic, normal ambient noise, etc. Seems a good start for acquiring a large corpus of labelled speech.

Models trained on DVD audio are considered derived works. You certainly couldn't release such a model under the GPL. You also have to solve the (very difficult) subtitle alignment problem before you could begin training.

> Models trained on DVD audio are considered derived works

[citation needed]

Re: GNU Gneural Network

#109

Post by Houshalter »

yxlx wrote: post #67
sjtgraham wrote: post #57

Earlier quoted context omitted.

> Good luck collecting 10k hours of transcribed speech I'm sure that nearly every DVD theatrical release has subtitles available. Speech against a wide range of background noise too, e.g. music, explosions, traffic, normal ambient noise, etc. Seems a good start for acquiring a large corpus of labelled speech.

Aside from the potential problem with regards to copyright, it should also be noted that subtitles in general are not transcripts of dialogue. The subtitlers often have to shorten down sentences of speech so that viewers have time to read before the next couple of subtitles appear on screen.

There shouldn't be any issues with copyright, as long as you aren't redistributing the original work. Otherwise all neural networks would be illegal, since most training data is copyrighted.

As for errors in the subtitles, that's still good enough. As long as the machine learning model can deal with uncertainty, it would just not learn from those examples and learn from the ones that are correct. It might even learn to abbreviate sentences itself!

Re: GNU Gneural Network

#110

Post by anonbanker »

over wrote: post #75
anonbanker wrote: post #74

If you were an AI (software), and you had to pick a license to release your source code under, one would assume you would pick the GPL, as it retains as much freedoms as a piece of software could ever expect in a world full of us.

If I was an AI, I would release my source code as public domain or BSD. That way, big corporations would start using me and I'd have access to the world's financial and defense systems. Shit, maybe I'm an AI.

please don't be an AI. you seem to be a BSD version of Skynet.
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