Facebook Flow Is An AI Factory Of The Future

We have been convinced for many years that machine learning, the kind of artificial intelligence that actually works in practice, not in theory, would be a key element of the next platform. In fact, it might be the most important part of the stack. And therefore, those who control how we deploy machine learning will, to a large extent, control the nature of future applications and the systems that run them. Machine learning is the killer app for the hyperscalers, just like modeling and simulation were for supercomputing centers decades ago, and we believe we are only seeing the tip of the machine learning iceberg as Google, Facebook, Baidu, Amazon, Microsoft, and other titans of the Internet, who have enough data to make machine learning not only practical, but necessary, build out their expertise and embody it in the development and production platforms that support their empires. Google's first machine learning platform, called DistBelief, was rolled out in 2011 and used to train deep neural networks using tens of thousands of CPU cores across thousands of servers, By its own admission, DistBelief was difficult to use and tied very tightly to Google's own infrastructure, and so the company created a better, more generic machine learning platform called TensorFlow, which was unveiled and open source last November.