*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.
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.
If it's worth saying, but not worth its own post (even in Discussion), then it goes here.
Notes for future OT posters:
1. Please add the 'open_thread' tag.
2. Check if there is an active Open Thread before posting a new one. (Immediately before; refresh the list-of-threads page before posting.)
3. Open Threads should be posted in Discussion, and not Main.
4. Open Threads should start on Monday, and end on Sunday.