Google has always used its annual I/O conference to connect to developers in its sprawling empire. It announces new tools and initiatives, sprinkles in a little hype, and then tells those watching: choose us, and together we’ll go far. But while in previous years this message has been directed at coders working with Android and Chrome — the world’s biggest mobile OS and web browser respectively — yesterday, CEO Sundar Pichai made it clear that the next platform the company wants to dominate could be even bigger: Artificial Intelligence.
For Google, this doesn’t just mean using AI to improve its own products. (Although it’s certainly doing that). The company wants individuals and small companies around the world to also get on board. It wants to wield influence in the wider AI ecosystem, and to do so has put together an impressive stack of machine learning tools — from software to servers — that mean you can build an AI product from the ground up without ever leaving the Google playpen.
The heart of this offering is Google’s machine learning software TensorFlow. For building AI tools, it’s like the difference between a command line interface and a modern desktop OS; giving users an accessible framework for grappling with their algorithms. It started life as an in-house tool for the company’s engineers to design and train AI algorithms, but in 2015 was made available for anyone to use as open-source software. Since then, it’s been embraced by the AI community (it’s the most popular software of its type on code repository Github), and is used to create custom tools for a whole range of industries, from aerospace to bioengineering.
“There’s hardly a way around TensorFlow these days,” says Samim Winiger, head of machine learning design studio Samim.io. “I use a lot of open source learning libraries, but there’s been a major shift to TensorFlow.”
Google has made strategic moves to ensure the software is widely used. Earlier this year, for example, it added support for Keras, another popular deep learning framework. According to calculations by the creator of Keras, François Chollet (himself now a Google engineer), TensorFlow was the fastest growing deep learning framework as of September 2016, with Keras in second place. Winiger describes the integration of the two as a “classic tale of Google and how they do it.” He says: “It’s another way that making sure that the entire community converges on their tooling.”
But TensorFlow is also popular for one particularly important reason: it’s good at what it does.
