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GNU Gneural Network

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Re: GNU Gneural Network

#41

Post by mindcrime »

semisight wrote: post #6
_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/…

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.

and relies on non-free components (CUDA).

Yeah, this is one reason I'm really hoping some of the stuff AMD is pushing, in regards to openness around GPUs, gains traction. And why I am hoping OpenCL continues to improve so that it can be a viable option. Being dependent on nVidia for all time would blow.

Re: GNU Gneural Network

#42

Post by mindcrime »

typon wrote: post #18
jjawssd wrote: post #11

Earlier quoted context omitted.

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

In other words, not at all

That's not necessarily relevant though. I'm sure the FSF would love to see Free Software replace all proprietary software, but in the end, the real point is that Free Software options are available to the people who want them. This isn't like a battle between commercial entities where market share is king and a project will be dropped if it isn't profitable. Gneural will be a success if a community forms around it and people work on it and use it, however small that community might be.

Re: GNU Gneural Network

#43

Post by mindcrime »

sseveran wrote: post #31
raverbashing wrote: post #17

Earlier quoted context omitted.

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.

But that may or may not matter, depending on what you're doing. And how often you do it. If I have a network that I only retrain once a month, I can deal with it taking a day or two to train. Heck, it could take a week as far as that goes.

OTOH, it obviously matters a lot if you're constantly iterating and training multiple times a day or whatever.

Re: GNU Gneural Network

#44

Post by ycmbntrthrwaway »

rand1012 wrote: post #37

Anyone else notice how GNU's website is stuck in 1993?

No, it was updated since then. Its header/footer format is certainly was not common in 1993, it has search box and things like that. Anyway, it is usable, does not require JavaScript, and loads really fast.

Re: GNU Gneural Network

#45

Post by frisco »

mindcrime wrote: post #43
sseveran wrote: post #31

Earlier quoted context omitted.

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.

But that may or may not matter, depending on what you're doing. And how often you do it. If I have a network that I only retrain once a month, I can deal with it taking a day or two to train. Heck, it could take a week as far as that goes. OTOH, it obviously matters a lot if you're constantly iterating and training multiple times a day or whatever.

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.

Re: GNU Gneural Network

#46

Post by mankash666 »

This team should focus on a SPIR-V back-end and remove vendor lock in from NVIDIA for CUDA IN tensor AI software. A GPL licensed AI library without GPU acceleration isn't attractive outside academia.

Re: GNU Gneural Network

#47

Post by q3k »

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.

> "money driven companies" (as though money were a bad thing)

It is a valid viewpoint to find money-driven companies as a “bad thing” (or more exactly, companies whose main goal is to maximize shareholder value).

Re: GNU Gneural Network

#49

Post by gcr »

semisight wrote: post #6
_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/…

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.

It's possible to run any of the "major" neural network toolkits (Caffe, Torch, Theano) on CPU-only systems. All of them are permissively licensed (to my knowledge).

It will be prohibitively difficult to train the model without some kind of hardware assistance (CUDA). This means that if we're building an ImageNet object detector, even if the code implements the model correctly the first time, training it to have close-to-state-of-the-art accuracy will take several consecutive months of CPU time. Torch has rudimentary support for OpenCL, but it isn't there yet. There are very good pre-trained models that are licensed under academic-only licenses that also help fill the gap. (This is about as permissively as it could be licensed because the ImageNet training data itself is under an academic-only license anyway.)

I'm not sure what niche this project fills. If you want an open-source neural network, you have several high-quality choices. If you need good models, you can either use any of the state-of-the-art academic only ones, or you would have to collect some dataset completely by yourself.

Re: GNU Gneural Network

#50

Post by IshKebab »

mindcrime wrote: post #40
_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 t…

Yeah they've really missed the fact that it isn't the algorithms or code that we're missing out on. Companies are usually pretty open about these because they know it isn't bit that is hard to compete on.

The hard bit is the training data. Good luck collecting 10k hours of transcribed speech, or 10k recordings of "Okay Google".

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