Google made headlines this week with the news it is open-sourcing TensorFlow, its AI (artificial intelligence) engine, under the Apache 2.0 license, and among the move's many implications is a potential wave of innovation for the collaboration software market. Here's the scoop from Google's official blog post on the announcement:
Today we’re proud to announce the open source release of TensorFlow -- our second-generation machine learning system, specifically designed to correct these shortcomings. TensorFlow is general, flexible, portable, easy-to-use, and completely open source. We added all this while improving upon DistBelief’s speed, scalability, and production readiness.
TensorFlow is great for research, but it’s ready for use in real products too. TensorFlow was built from the ground up to be fast, portable, and ready for production service. You can move your idea seamlessly from training on your desktop GPU to running on your mobile phone.
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.
POV: Smarter Collaboration
Google uses TensorFlow for a variety of its own needs, such as speech recognition, the Google Photo search function and Gmail's recently introduced Smart Reply feature.
Smart Reply is a sterling example of how the next generation of collaboration software can help users get more work done, says Constellation Research VP and principal analyst Alan Lepofsky. The feature scans a user's inbox messages, determines which ones need the user to take action, and offers suggestions for potential quick replies.
An open-sourced TensorFlow has huge implications for the many companies creating add-ons such as webconferencing, task management and other tools for Google's collaboration suite, Lepofsky notes. "Those are all going to have access to artificial intelligence," he says. "This is empowering the next generation of assisted collaboration."
Think of the various facets used to date for sorting messages and content, such as time, sender and size, Lepofsky says. "What if there weren't defined categories like that? What if you clicked a button and said, 'show me the things that are important.'"
It's still early days for the open-source TensorFlow, of course, and it's not clear what enablement plans Google has to get Google at Work partners up and running on it. Google also has some catching up to do with the likes of IBM, which has been aggressively courting developers for its Watson AI platform for some time.
But overall, AI technologies look to figure prominently in the next generation of collaboration suites, and customers should map out their buying plans accordingly.
