Open Source Artificial Intelligence

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Open Source Artificial Intelligence

The open-source AI trend represents the convergence of two other powerful trends:

  • The open-source movement
  • The artificial intelligence revolution

The open-source movement is the trend toward making the source code for software available to developers and users so that anyone can modify it and, theoretically, improve it. Examples of open-source software include the Linux operating system, the Mozilla Firefox browser, and the Android mobile platform.  The concept has spread to encompass open innovation, in which companies invite everyone outside the company to help in developing new products or in solving design challenges.

The artificial intelligence revolution refers to the growth in the science of using algorithms to develop computer software that is capable of reasoning, problem solving, and decision making.  Examples of AI include:

  • Loan-processing systems that evaluate the creditworthiness of mortgage applicants.
  • Image-recognition systems that can identify what is happening in a photograph and provide a text description.
  • The software that allows driverless cars to recognize obstacles in their path and navigate around them.

Now, tech giants like Google, Microsoft, and Amazon are bringing the open-source concept to artificial intelligence by opening their AI code to the outside world. 1

In November 2015, Google open-sourced its deep learning engine software called TensorFlow.  Deep learning uses neural networks to learn to do something by absorbing huge amounts of data.

TensorFlow is the software that the Google Photos app uses to “learn” to recognize photos of an object after it is fed millions of photos of that object.  So if you want to find a photo of a birthday cake in your photo library, you can search for the term “birthday cake” and the app will show you every image you’ve stored of a dessert topped with candles.

Google uses the same software to constantly increase the accuracy of its search results; to improve speech recognition apps; and to translate written words from one language into another language.

At the same time, the company was criticized because the version of TensorFlow that it released could only run on a single computer.  To achieve the scale needed to create new enterprise applications, developers must be able to use the software to analyze data quickly across a multitude of computers.

In 2015, Facebook had shared the software it uses to operate the open-source AI software called Torch on multiple computers...

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