BlueData and H2O.ai Partner to Accelerate AI Deployments

H2O and H2O Driverless AI on BlueData Ensure Faster Time-to-Value with Machine Learning

BlueData^®, provider of the leading container-based software platform for AI and Big Data workloads, and H2O.ai, the open source leader in AI, announced a partnership to accelerate AI and machine learning (ML) deployments. The collaboration includes integration of H2O.ai’s full suite of products – including open source H2O, H2O Sparkling Water for machine learning with Spark, and the automated H2O Driverless AI – with the container-based BlueData EPIC™ software platform. The result is a powerful combination to help customers rapidly deploy and scale their AI / ML environments, while ensuring enterprise-grade security and performance.

BlueData and H2O.ai share many joint customers across multiple industries – including industry-leading organizations like Barclays, Citi, GM Financial, Optum, Macy’s, Seattle Children’s, and SCL Health. They use AI / ML for a variety of applications ranging from fraud detection and credit risk analysis, to genomics research and precision medicine, to improved customer experience, and more. The BlueData-H2O.ai partnership will enable these and other enterprise customers to realize the full potential of AI / ML, helping them to make mission-critical business decisions and deliver data-driven innovation.

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“Our mission is to democratize AI by putting automatic machine learning in hands of data scientists and engineers,” said Sri Ambati, CEO and founder of H2O.ai. “BlueData has built container-based innovations that provide secure on-demand access to distributed H2O environments and accelerating adoption across the enterprise. Together we can make it faster, cheaper, and easier for our customers to monetize their data.”

The combination of BlueData with H2O.ai represents a game-changing solution for large-scale AI / ML deployments in the enterprise. Now these organization can get up and running quickly with distributed H2O machine learning environments at scale, in a multi-tenant architecture with a shared pool of resources for improved efficiency and reduced costs. They can operationalize their machine learning pipelines and deliver faster time-to-value for their AI initiatives — while ensuring security and high performance.

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With the BlueData EPIC software platform, data science teams can instantly spin up multi-node clusters for H2O Flow, Sparkling Water, and Driverless AI running on containers – whether on-premises, in the public cloud, or in a hybrid model. Through its App Store, BlueData EPIC provides pre-tested and pre-integrated Docker container images for distributed H2O environments. In just a few mouse clicks, users can have on-demand access to H2O’s best-in-class machine learning capabilities – using GPUs and/or CPUs for their containerized compute clusters.

BlueData also offers a data connector to enable compute / storage separation for H2O. With BlueData, different containerized compute clusters for different workloads (including Spark, Kafka, Tensorflow, and/or H2O) can share access to a common data lake. This separation enables H2O users to easily connect their compute cluster to the data they need for large-scale distributed machine learning, while providing the ability to scale and optimize compute resources independent from data storage. The result is improved flexibility and resource utilization, along with reduced costs by eliminating data duplication and reusing existing storage investments.

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“Artificial intelligence and machine learning are at the top of the priority list for just about every CIO and CDO in every industry,” said Kumar Sreekanti, co-founder and CEO of BlueData. “Our partnership with H2O.ai will help these organizations to deliver faster time-to-value for their AI / ML initiatives across a wide range of use cases for business innovation and competitive differentiation. Working with H2O.ai, we can help simplify the deployment of advanced AI / ML technology and make it more readily accessible for teams of data scientists, engineers, and developers across the enterprise.”

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