Google Cloud Machine Learning hits public beta, with additions

Google unveiled today machine learning-related additions to its cloud platform, both to enrich its own cloud-based offerings and to offer expanded toolsets for businesses to develop their own machine learning-powered products.

The most prominent offering was the public beta of Google Cloud Machine Learning, a platform for building and training machine learning models with the TensorFlow  learning framework and data stored in the BigQuery and Cloud Storage back ends.

Google says its system simplifies the whole process of creating and deploying machine learning back ends for apps. Some of this is simply by making models faster to train. Google claims Cloud Machine Learning’s distributed training “can train models on terabytes of data within hours, instead of waiting for days.”

Much of it, however, is about Cloud Machine Learning’s APIs reducing the amount of programming required to build useful things. In a live demo, Google built and demonstrated a five-layer neural net for stock market analysis with just a few lines of code.

Another announced feature, HyperTune, removes another source of drudgery often associated with building machine learning models. Models often need to have parameters tweaked to yield the best results. Google claims HyperTune “automatically improves predictive accuracy” by automating that step.

Google Cloud Machine Learning was previously only available as an alpha-level tech preview, but InfoWorld’s Martin Heller was impressed with its pre-trained APIs for artificial vision, speech, natural language, and language translation.

Many of the machine learning tools Google now offers for end users, such as TensorFlow, arose from Google’s internal work to bolster its projects. The revamped version of Google’s office applications, G Suite, is one of the latest to be dressed up with machine-learning powered features. Most of these additions are for automating common busywork, such as finding a free time slot on a calendar to hold a meeting.

Google’s machine learning offerings pit it against several other big-league cloud vendors offering their own variations on the same themes, from IBM’s BlueMix and Watson services to Microsoft’s Azure Machine Learning. All of them, along with Amazon, Facebook, and others, recently announced the Partnership on AI effort to “study and formulate best practices on AI technologies” — although it seems more like a general clearinghouse for public awareness about machine learning than a way for those nominal rivals to collaborate on shared projects.

Source: InfoWorld Big Data