Google Open-Sources TensorFlow: A Preemptive Strike On Competitors?

  • Google is open-sourcing its second-generation machine learning system TensorFlow.
  • TensorFlow is a powerful AI system general enough to be applicable in a wide variety of domains.
  • AI and Deep Learning are likely to dominate the computing landscape of the next decade and beyond.
  • With this move, Google is offering a free alternative to its competitors's AI, and recruiting (for free) an army of new developers to improve its own.

Alphabet Inc-A (NASDAQ:GOOGL) announced that it's open-sourcing its second-generation machine learning system TensorFlow. The Internet giant has open-sourced TensorFlow as a standalone library and associated tools, tutorials, and examples with the very permissive Apache 2.0 license, so single developers, companies and organizations will be free to use TensorFlow in their projects.

Note: You might also be interested in 'Alphabet bets on Visionary Futurist Projects, Investors should bet Too.'

TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

"[TensorFlow is] a highly scalable machine learning system - it can run on a single smartphone or across thousands of computers in datacenters," said Google CEO Sundar Pichai. "We use TensorFlow for everything from speech recognition in the Google app, to Smart Reply in Inbox, to search in Google Photos. It allows us to build and train neural nets up to five times faster than our first-generation system, so we can use it to improve our products much more quickly."

Using TensorFlow as a base platform, open-source developers everywhere will be able to improve on current methods used in Artificial Intelligence (AI) research for speech recognition, image recognition, navigation, automated data processing, smart search, and a growing body of machine learning algorithms known as Deep Learning.

"Deep Learning has had a huge impact on computer science, making it possible to explore new frontiers of research and to develop amazingly useful products that millions of people use every day," note AI specialists on Google's Research blog. "Our deep learning researchers all use TensorFlow in their experiments. Our engineers use it to infuse Google Search with signals derived from deep neural networks, and to power the magic features of tomorrow. We’ll continue to use TensorFlow to serve machine learning in products, and our research team is committed to sharing TensorFlow implementations of our published ideas."

Make no mistakes - AI and Deep Learning are likely to dominate the computing landscape of the next decade and beyond, including self-driving cars, delivery drones, robotics, intelligent homes, Internet of Things (IoT) networks, Big Data, personalized medicine, smart personal assistants, and human-like user interfaces. That's why top technology companies are betting billions on AI.

The software developers who will use TensorFlow in their projects are likely to follow the standard practices in open-source development - they will leverage their collective brain-power to develop all sorts of improvements to the algorithms initially developed by Google, invent new even more powerful techniques, and place their new developments back into the open-source TensorFlow repository for other developers to re-use and improve upon.

This positive feedback loop typical of open-source development is known for its potential to produce spectacular results in short times. The risk of open-source software projects is that the core developers could run out of money and go, but that's not likely to happen to the TensorFlow project, fully backed by Google's cash.

What's in the deal for Google? Of course, the acquisition of an army of smart, highly trained and self-motivated software developers who will work long nights for free to improve Google's products, is likely to have spectacular effects on Google's business. But Google's move can also be interpreted as a preemptive strike on its competitors in advanced computing and AI.

In particular, IBM (NYSE:IBM) and Facebook (NASDAQ:FB) are aggressively pursuing their own AI developments. IBM recently expanded Watson, its Artificial Intelligence (AI) platform, with new AI tools in the Watson Developer Cloud. Facebook is becoming one of the most advanced AI research centers in the world, and the company's AI developments have accelerated to the point that AI will surely shape the way humans interact with computers.

By open-sourcing TensorFlow, Google is offering a free alternative to the AI products of its competitors, and recruiting (for free) an army of new developers to improve its own AI products and keep them state-of-the-art. The mid to long term impact on Google stock price is likely to be positive.

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