The Competitive Advantage of Google Cloud Platform (GCP) Machine Learning
Among the organizations that have invested in GCP, many are looking to initiate Google cloud machine learning projects. Why? These projects (and machine learning in general) have proved to be a huge competitive factor. In 2017 MIT Technology Review had already claimed that machine learning was “the new proving ground for competitive advantage” and the number of machine learning pilots and implementations has doubled each year since then. Google cloud machine learning projects are paving the way for businesses to understand their customers at a granular level, to detect fraud at its earliest possible onset, to predict product effectiveness and maintenance requirements and much more.
Powering these Google cloud platform machine learning projects is the Google suite, or the most comprehensive AI/ML framework on the market. The Google cloud platform for machine learning provides the necessary storage (such as Google Cloud Storage and BigQuery) and processing (such as Dataflow and Dataproc) for large-scale projects. But where Google cloud machine learning suite excels more than any other cloud providers is with its AI/ML services—BigQuery ML, Cloud AutoML, Cloud TPU, Dialogflow, Cloud Natural Language, Cloud Speech-to-Text and Cloud Translation are just some of the offerings. With the Google cloud machine learning platform, users have the right technology framework to support ML/AI adoption.