Everything you need to know about Google brains- Tensorflow.

Google took o’Reillay’s idea further than even he expected. It’s open sourcing that engine, freely sharing the underlying code with the world at large scale. This software is called Tensorflow and in literally giving the technology away.Google believes it can accelerate the evolution of AI.

Tensorflow researchers cloud
Tensorflow is an open-source software library for machine learning across the range of tasks. It is used for research and production at Google. It was developed by the Google brain team. It was released under the Apache 2.0 open source license on November 9, 2015.
It was developed for numerical composition using data flow graphs.

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The flexible architecture allows you to deploy computation to one or more CPUs in a desktop, server or mobile devices with a single API.Python was the first client language supported by Tensorflow and currently supports the most features. More of that functionality is being moved into the core of tensor flow(implemented in C++)and exposed via a C API.

Google brain team members set their own research agendas, it has a special thrust in the field of deep learning.
Deep learning is a new area of machine learning research, it is a deep neural network that leverages the massive amount of data to solve tasks that are beyond the reach of machine learning in the early 2000s.

Many Google services use a machine learning technology called tensor flow. Here learning refers to that the technology will get smarter by time to the point currently we can’t imagine.

In November 2015 Google made this technology open-source and allowed it to all types of researchers. So many independent developers contributed to tensor flow. We don’t need to know where the machine learning technology will take us but there are some applications of Tensorflow that may give us peek at future.

  • More on image analysis
  • Speech recognition
  • Dynamic translation
  • Alpha Go
  • Magenta project


The technology of image analysis is not only used in Google photos but also in Google Maps’ Street View feature. Tensorflow helps in connecting the image with the map coordination.
Tensorflow is also used for voice assistant speech recognition software by Google. over 80 languages and variants are recognized by current speech recognition technology.

Googles translation feature is another example of machine learning technology. The users of Google translation can add new vocabularies and fix the mistakes in it. it helps machine improve the further performance by learning from those mistakes.

Alpha go is one of the most fun examples of Tensorflow usage. It was programmed to play Go.Go was originated in China, it is a board game for two players. It’s still played today. In the match against Lee, Sedol-the-18-time go world champion, Alpha go won 4 out of 5 games and was given the honorary highest go Grandmaster rank.

The magenta project is an another ambitious application of Tensorflow to create machine-generated art.Google hopes to generate more advance machine-generated art through the magenta project and build a community of artists around it.An Art exhibition was also held in February 2016 by Google in San Francisco showing off 29 computer generated arts.
The best applications of Google Tensorflow are the best applications for deep learning in general. deep learning is great at pattern recognition/machine perception, and it’s being applied to images, videos, sounds, voice, text and time series data. Tensorflow also goes beyond deep learning to support other forms of machine learning like reinforcement learning.

Some of the companies currently using Tensorflow are Google, Airbnb, eBay, Intel, Dropbox, Deepmind, Airbus, CEVA, Snapchat, SAP, Uber, Twitter, and IBM.

Logo of Tensorflow:

In Tensorflow logo, the left arm of the T looks like 2 units long, while the right arm is 1 unit long. the shadow should look different (asymmetrical).

“What we are hoping is that the community adopts this as a good way of expressing machine learning algorithms of lots of different types, and also contributes to building and improving [tensorflow] in lots of different and interesting way,”says Jeff Dean,one of googles most important engineer and a key Player in rise of its deep learning technology.


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