Google has launched its new large-scale cloud-based machine learning platform which will be able to learn from available information and make predictions “across a whole variety of scenarios”. “We look forward to seeing the innovative ways you’ll use these new products”.
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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.
On Wednesday, Google presented its newly assertive push for the enterprise, hosting its inaugural cloud developer conference in San Francisco. In fact, Google unveiled a handful of new offerings that, in essence, pour ML all over the cloud. AWS ranks first with 31 percent, followed by Microsoft Azure at 9 percent, IBM at 7 percent and Google Cloud Platform at 4 percent, reveal Synergy data. Stackdriver, a cloud monitoring tool which the company opened in beta at the start of the year, works by monitoring traffic, notifications and diagnostic functions. For big enterprises, which Google wants, moving data to the cloud (or moving from one cloud to another) is expensive. This includes sending logs to BigQuery for analysis and Google Cloud Datalabs for visualisation.
Google has approximately 60 cloud-related job postings on its site, with about a third of them related to sales and marketing, and another third related to IT positions. Reuters late Tuesday added Home Depot to the list of customers including Spotify and Apple.
Google is also looking to hire IT professionals like cloud software engineers.
Google today kicked off its GCP Next 2016 event in San Francisco, California, and with it comes the announcement of some new products that will bolster Google’s cloud offerings.
Google is to open 12 datacentre regions between 2016 and 2017, as it steps up its efforts to grab a larger slice of cloud infrastructure services market.
Despite having access to large amounts of user data, Google has been a latecomer in the machine learning field, with Microsoft having established a lead two years ago with its Azure-based Cortana Analytics Suite. Docker container use by Google’s cloud customers is doubling every quarter because they have the advantage of portability and serve as a common unit for test and for continuous deployment. A product of Google’s long term investment in artificial intelligence, it is a differentiator that will attract customers to its cloud who need machine learning.
Until now, Google has struggled to make headway with major enterprise clients.
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A limited preview of the service is now available for users to build their own machine-learning models “that work on any type of data, of any size”.
