Google releases TensorFlow, its second generation machine learning system to open source.
Get an insight into the workings of google's machine learning system by employing the open source code in your own environments. Of course, you need lots of data to make it work.
"TensorFlow has extensive built-in support for deep learning, but is far more general than that -- any computation that you can express as a computational flow graph, you can compute with TensorFlow. Any gradient-based machine learning algorithm will benefit from TensorFlow’s auto-differentiation and suite of first-rate optimizers. And it’s easy to express your new ideas in TensorFlow via the flexible Python interface."
"TensorFlow is great for research, but it’s ready for use in real products too. TensorFlow was built from the ground up to be fast, portable, and ready for production service. You can move your idea seamlessly from training on your desktop GPU to running on your mobile phone. "
Because it is cheaper to have thousands of developers work on something you can then use and implement within your model. Your question is no different than the question many asked in the 80's when UNIX was made open source. Who knows in 10 or 15 years, this AI tool can become the next best thing since slice bread and have the Google/Alphabet stamp on it.