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Why Machine Learning Strategies Fail

Most companies are struggling to develop working strategies, according to a new survey by cloud services provider Rackspace Technology.

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SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningThe survey, which includes 1,870 organizations in a variety of industries, including manufacturing, finance, retail, government, and healthcare, shows that only 20 percent of companies have mature / initiatives. The rest are still trying to figure out how to make it work.

There’s no questioning the promises of in nearly every sector. Lower costs, improved precision, better customer experience, and new features are some of the benefits of applying models to real-world applications. But is not a magic wand. And as many organizations and companies are learning, before you can apply the power of to your business and operations, you must overcome several barriers.

Three key challenges companies face when integrating technologies into their operations are in the areas of skills, data, and strategy, and Rackspace’s survey paints a clear picture of why most strategies fail.

Machine learning is about data

Machine learning models live on compute resources and data. Thanks to a variety of platforms, access to the hardware needed to train and run models has become much more accessible and affordable. […]

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