The ability to support a rapid evaluation model for hardware, run the business on cloud computing, and use machine learning to quickly compute data will become the basis for all successful companies within five years, he told attendees at the GCP Next 2016 conference in San Francisco Wednesday. The Machine Learning models are built using the open-source TensorFlow machine learning library.
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Despite having a reputation for possessing advanced cloud technology that one would think enterprises would glom onto, Google is also eyeing the notion of delivering enterprise cloud basics, according to comments Greene made in a Bloomberg report.
This should help Google do a better job of competing with AWS and other clouds. Each of these regions will have multiple availability zones, Google says. 451 Group Lead Analyst Carl Brooks believes the company is still not at the same level as its competitors, needing to add more enterprise compatibility, compliance, and security features.
While modern cloud systems are based on “decades-old” technology, Google said, the company’s forthcoming products and services are designed for the next wave of cloud computing.
In this market the mighty Google finds itself somewhat dwarfed by its competition.
It has been a busy period for Google’s cloudy operations, with recent announcements of a client win in the form of Home Depot, as well as the news that Apple would move a portion of its data to the search giant from Amazon Web Services (AWS). As part of Cloud Machine Learning, you’ll have access to Google’s Machine Learning models like Google Translate API and Cloud Vision API, but Google announced today that those are being joined by Google Cloud Speech API.
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Varun Sakalkar, Google product manager, says the Tokyo and OR regions, which will both be operational later this year, will enable Cloud Platform customers to deploy services and applications nearer to their own customers, providing lower latency and greater responsiveness.
