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Categories: AI Amazon DEEP LEARNING DELL EMC google IBM Machine learning Microsoft

Here at The Next Platform, we’ve touched on the convergence of machine learning, HPC, and enterprise requirements looking at ways that vendors are trying to reduce the barriers to enable enterprises to leverage AI and machine learning to better address the rapid changes brought about by such emerging trends as the cloud, edge computing and mobility. At the SC17 show in November 2017, Dell EMC unveiled efforts underway to bring AI, machine learning and deep learning into the mainstream, similar to how the company and other vendors in recent years have been working to make it easier for enterprises to adopt HPC techniques for their environments. For Dell EMC, that means in part doing so through bundled, engineered systems. IBM has strategies underway, including through the integration of its PowerAI deep learning enterprise software with its Data Science Experience. Both offerings are aimed at making it easier for enterprises to embrace advance AI technologies and for developers and data scientists to develop and train machine learning models. Software vendors like SAP and Microsoft similarly are easing the way for enterprise adoption of AI and machine learning techniques. @Google has been a vocal proponent of the idea of democratizing #AI by making it easier for mainstream businesses to use. As we outlined last year, Google sees its capabilities in AI, machine learning and deep learning as a competitive advantage against larger hyperscale players like @Amazon Web Services and @Microsoft #Azure in the highly competitive #cloudcomputing arena and a key way of enticing enterprises to the #GoogleCloudPlatform to help them manage, analyze and leverage the rapidly mounting data to more quickly and effectively build products and services that their customers can use. Google in 2016 created a machine learning unit within its Cloud Platform business and rolled out a series of APIs for such jobs as natural language, language translation and vision recognition. The hyperscaler also brought  in Fei-Fei Li, at the time the director of Stanford University’s Artificial Intelligence Lab and the Stanford Vision Lab, to head up the new machine learning group

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