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polymathwannabe comments on Open thread, Nov. 09 - Nov. 15, 2015 - Less Wrong Discussion
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In the news:
Google just open-sourced TensorFlow, its AI engine.
*linear algebra computational graph engine with automatic gradient calculation
I really wonder how this will fit into the established deep learning software ecosystem - it has clear advantages over any single one of the large players (Theano, Torch, Caffee), but lacks the established community of any of them. As a researcher in the field, it's really frustrating that there is no standardisation and you essentially have to know a ton of software frameworks to effectively keep up with research, and I highly doubt Google entering the fray will change this.
https://xkcd.com/927/
Add Julia to the mix as well (which I currently use and I find personally better than those other ones).
I think TensorFlow's niche would be in the area of prototyping new ML algorithms as it seems pretty general, flexible, and fast. If you just want a simple deep neural net, it might be better to use Caffe or Theano. Those do not provide a flexible and general optimization framework, though. TensorFlow also seems more powerful in the area of language processing, as you'd expect.
I'm trying to figure out the business strategy behind open sourcing this.
Android I got... open sourcing was a good play (maybe the only play) to compete with iPhone.
Opensourcing TensorFlow could be a recruitment strategy - but somehow I think Google already gets top machine learning talent.
Anyone have any ideas?