"Machine Learning and deep learning represent new frontiers in analytics," Thomas says. "These technologies will be foundational to automating insight at the scale of the world's critical systems and cloud services. IBM Machine Learning was designed leveraging our core Watson technologies to accelerate the adoption of machine learning where the majority of corporate data resides. As clients see business returns on private cloud, they will expand for hybrid and public cloud implementations."
Thomas notes that IBM Machine Learning's genesis in the Watson service ensures that it is designed around collaboration and portability in a hybrid environment. Machine learning algorithms can be composed and trained in a private cloud and seamlessly moved to the public cloud and vice versa, all with common management.
"I do think what you'll see is that hybrid will become a dominant use case here," he says.
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