What you need to know about Google's Open Source AI Platform - TensorFlow

Google started tinkering with deep learning neural networks back in 2011, resulting the first generation machine learning proprietary system, DistBelief. While, TensorFlow is the second generation iteration of that same technology, which is now a core part of its commercial products like Google Voice Search, Google Photos, and YouTube.

The company earlier in the week announced open-sourcing the platform, making the highly scalable machine learning system available for everyone from researchers, to developers - with the end to accelerate research in machine learning.

Albeit, machine learning is still in its infancy, open sourcing the library will enable researchers and developers to build systems capable of breaking down data to make more accurate decision based on the information.

What platforms does TensorFlow support?

TensorFlow is flexible and quite capable of running on older systems, making it ideal for every platform. It allows you to carry-out computation on one or more CPUs and GPUs on desktop, server, or mobile platforms.

Who can use It?

TensorFlow is an ongoing project, meaning it isn't complete, which opens room for everyone - including: students, academicians, independent researchers, developers and even hackers.

Google has made available a version for academic researchers with built-in binaries, and another version as API for developers. The company intends to build an active open source community and through their feedback and contributions ensure improvements to the source code.
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