Machine learning, a type of artificial intelligence that employs software to interpret and make predictions from large sets of data, is in popular demand in Silicon Valley. Some of the largest of those companies such as Microsoft, Facebook, and Apple have thrown their hat into the ring. But it was Google that started the trend, and in order to remain innovative, Google needed to keep looking like the cutting-edge leader.
Hence TensorFlow, a machine-learning system that Google has used internally for a few years. Today, Google is taking it open source, releasing the software parameters to fellow engineers, academics and hacks with enough coding skills. There is no denying that learning systems have made it possible to create and improve apps when it comes to speech and image recognition technologies.
For example, Google Photos have benefitted from their own machine learning system, called DisBelief. Developed in 2011, DisBelief has helped Google build large neural networks, but it has its limitations, including difficult configurations and its inability to share code externally. As a result, the company has open-sourced TensorFlow, which was designed to fix the shortcomings of DisBelief. However, it’s important to note that it only allows for part of the AI engine to be open-sourced.
By releasing TensorFlow, Google aims to make the software it built to develop and run its own AI systems a part of the standard toolset used by researchers. It may also help Google identify potential talent for the future.