Friday, August 11, 2017

Deep Learning, TensorFlow and Tensor Core

I was lucky enough to get a ticket to the Google I/O 2017 on a Google Code Jam for Women (for girls that don't know, Google has some programming contest for women and the best classified win tickets to the conference).

One of the main topics of the conference was for sure its new Deep Learning library TensorFlow. TensorFlow is Google's OpenSource Machine Learning library that runs both on CPU and GPU.

Two very cool things were presented at Google I/O:

  •  TPU (Tensor Processing Unit) - a GPU optimized specifically for TensorFlow that can be used on the Google Cloud Engine
  •  TensorFlow Lite - a TensorFlow low weight version to run on Android and make developer's lives easier

Last week, at a BigData meetup in Chicago, I discovered that Nvidia also created a specific GPU hardware for processing Deep Learning, the Tensor Core.

 With all this infrastructure and APIs being made available, Deep Learning can be done considerably easier and faster. At Google I/O, Sundar Pichai mentioned that at Google they have been using Machine Learning for almost everything, and even Deep Learning to train the Deep Learning networks!

TensorFlow's API is so high level, that even someone with little technical background can develop something interesting with it. Sundar also shared a story of a high school guy that used the library to help detecting some types of cancer.

It seems that Data Science is becoming attainable.

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