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GNU is Not Unix Open Source AI Software

GNU Project Introduces Gneural Network AI Package (gnu.org) 95

jones_supa writes: The GNU free software project is introducing a new neural network computation package called Gneural Network. The GNU project has been impressed by the work of Google, IBM, AlphaGo and Watson on the field of artificial intelligence. However, the GNU project sees that the fact that only companies and labs have access to this technology can represent a threat: "First of all, we cannot know how money driven companies are going to use this novel technology. Second, this monopoly slows down Progress and Technology." This is why the author, Jean Michel Sellier, decided to create Gneural Network and release it under the GNU GPL license. In the current release (version number humbly set to 0.0.1), it is a very simple feedforward network which can learn very simple tasks such as curve fitting, but the development team plans to deliver more advanced features very soon. They are already spending efforts to implement a network of LSTM (long short term memory) neurons for recurrent networks and deep learning. Learning reinforcement techniques are also planned.
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GNU Project Introduces Gneural Network AI Package

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  • by dinfinity ( 2300094 ) on Sunday March 13, 2016 @09:15AM (#51689287)

    "However, the GNU project sees that the fact that only companies and labs have access to this technology can represent a threat"
    That is not a fact at all. There are tons of open source neural network libraries and tools and even tons of open source neural network libraries that provide recurrent network and deep learning features. Just a 30 second search gives me this list:
    http://deeplearning.net/softwa... [deeplearning.net]

    "a very simple feedforward network which can learn very simple tasks such as curve fitting"
    This is NN101 stuff and I'm sure hundreds if not thousands of college students have made something similar.

    Nothing to see here. Move along.

    • by Dutch Gun ( 899105 ) on Sunday March 13, 2016 @09:57AM (#51689393)

      Yep, nothing novel at all, even in conception. The real trick with deep learning software is figuring out how to integrate them into knowledge bases and provide useful training and feedback mechanisms. Honestly, creating the neural network software is the easy part, because there's a ton of academic research that tells you *exactly* how to do it. I actually downloaded and examined the code, and while it looks reasonably clean and functional, we're not exactly talking about a huge amount of work to replicate it - it's just a few hundred lines in total.

      Moreover, when any software package starts with a section on "The Ethical Motivations" for its existence, it strikes me as the wrong sort of motivation altogether. The real motivation should be "I want to solve some interesting problems", and THAT will drive the design. This sounds like a pretty typical academic exercise, and as such, probably is not going to amount to much, other than as a starting point for some student projects here or there. But even that is dicey, as naturally, there's no documentation at all - just a readme file telling you to look at the source code to figure out how it works. Odds are pretty good that documentation is never actually written for it, because that's a hell of a lot less fun than writing the code.

      Sorry, I really do love this sort of stuff, but it's a little hard to get excited about the project when its exactly the same sort of code I was tinkering with as an undergrad student decades ago. That anyone is actually comparing a few hundred lines of relatively simplistic C code to IBM or Google's machine learning projects is disingenuous at best, borderline insulting at worst.

  • by nickovs ( 115935 ) on Sunday March 13, 2016 @09:38AM (#51689343)

    The idea that "the fact that only companies and labs have access to this technology can represent a threat" is patently absurd. Theano [deeplearning.net], Caffe [berkeleyvision.org] and Torch [torch.ch] are all open source and even Google has open-sourced its Tensor Flow [tensorflow.org] platform which makes it easy to build new tools and run then, fast, on all the GPUs you can find. If you need to do this at scale and you're not the size of Google or IBM you can use Amazon's Machine Learning for AWS [lorienpratt.com]. There are many, many higher level toolkits out there that are available under licenses that are much less restrictive than GPLv3.

    • There are many, many higher level toolkits out there that are available under licenses that are much less restrictive than GPLv3.

      Aaaand ... you found the problem. See, wasn't that hard, was it?

      The GNU people don't recognize anything as 'free' if it's not licensed under GPL.

  • Does anyone know how this is different from the other open source neural nets that exist?There have been tons of these over the last 40 years. AFAIK most of the algorithms originate in academia and stay there where open sourcing is the norm.

  • by ooloorie ( 4394035 ) on Sunday March 13, 2016 @09:59AM (#51689403)

    But the fact that only companies and labs have access to this technology can represent a threat. First of all, we cannot know how money driven companies are going to use this novel technology. Second, this monopole slows down Progress and Technology.

    The GNU project should do a bit more background research before starting new projects. Here are some links to open source deep learning tools. These are the same tools and libraries used by those "money driven companies" in their projects, including AlphaGo:

    Caffe [berkeleyvision.org], widely used C++ deep learning framework.

    Theano [deeplearning.net], widely used Python deep learning framework.

    Torch [torch.ch], the software used by Google, AlphaGo and Facebook.

    TensorFlow [tensorflow.org], Google's large scale machine learning framework.

    CNTK [github.com], Microsoft's deep learning toolkit.

  • 1990 called and wants its version control system back. I'd go poking around in their version control to at least determine the implementation language, but... nah.
    • by w1z7ard ( 227376 )

      1990 called and wants its version control system back. I'd go poking around in their version control to at least determine the implementation language, but... nah.

      Where did you find this? I was looking for the source code repo. And I agree. CVS is dooming this project from the start.

      • by Greyfox ( 87712 )
        When I clicked on the "here" link in "You can download the software here" the first time, it took me to some page about their CVS. Now it just gets you a tarball.
    • by Anonymous Coward

      GIT isn't modern...its a tool used to torture devs, used by hipster programmers who think using the same tools as other devs isn't "cool"...now go back to making your unnecessarily complex code in a brand new framework and I'll go back to making something useful that does the same thing with 1/10 the computer's resources...

  • So soon I will be able to use this to help make my ultra-drone army even more effective at killing all the humans! Now I just need to perfect my human glucose-based power harvesting, and my biological harvested bioprinter!
  • I couldn't find the source code repository. It might just be because I am clueless on how to find them for GNU projects. Anyone devise the subversion or git or darcs or whatever it is location?
  • Machine learning is software generated by statistical algorithms fit to lots of data. Without the training data, the algorithms alone are quite useless. Pre-trained networks are essentially closed source, because the source is the training data.

    There's lots of open source code for this work already. It boils down to who has access to the data. Tesla can turn on autopilot to collect data [businessinsider.com] from its entire fleet for millions of miles traveled. Google doesn't have a fleet, so it wants to collect so much data w [mashable.com]

Stinginess with privileges is kindness in disguise. -- Guide to VAX/VMS Security, Sep. 1984

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