Although advertising revenue is constantly dominating Alphabets revenues, Google’s cloud business is continuing to grow steadily. Technology Business Research has estimated that Google’s cloud revenue which is comprised of Google Apps for Work, for Education and for Government, as well as Google Cloud Platform Revenue grew by nearly 62% to reach $989 million in the second quarter of this year and that it will continue to expand over the $1 billion mark in the third quarter of 2016.
Apparently more than 100 teams at Google are using machine learning and it looks likely that machine learning technology will drive the company’s future. In addition to energy efficiency improvements gained from implying DeepMind algorithms to Google data center operations, Google Cloud Platform has also grown its machine learning capabilities for users’ development. Google’s multilingual speech API and Cloud Natural Language API are at the forefront of these innovations and which in addition to its Vision API and Translate API, empower developers with predefined models that parse voice, text, and image inputs to extract deeper information about the subject.
Even though these models are powerful in their preconfiguration and expansiveness of supporting data, they cannot be based on data specific to enterprise applications. Google has addressed this gap by unveiling Cloud Machine Learning, allowing users to build intelligent applications and predictive models using their own training data, which can in turn return tailored, enterprise-specific results. Cloud Machine Learning also integrates with other GCP products and can be supplemented with pretrained models and other data from the TensorFlow machine learning library which automatically ingests data and continues to learn from new inputs.
In May of this year Google introduced TensorFlow Processing Units which are proprietary chips built specifically for accelerated machine learning processing and tailored for TensorFlow. Although these have just been unveiled to users, these processing units have been in use at Google for more than a year and will increase the performance of GCP machine learning services as they begin to gain greater traction in the market.
Google is continuing to build out functionality to increase competitiveness and differentiation of Google Apps for Work as it seeks to further penetrate the large enterprise market. Recently those features include Google Springboard and a new User Hub. With Google Springboard, users are able to search through all applications simultaneously and it also recommends relevant tasks and business information to users throughout their workday. The AI backed content recommendation and search capabilities will increase the speed of navigation of files, adding value as a type of workday assistant catering to business’s needs. The new User Hub provides a landing page for users showing all of the Google Apps that are turned on for that user or which may have been of interest and are available for download.