IBM Power Systems with H2O Driverless AI Accelerate Time Series Workloads by up to 5X
From the H2O World 2018, IBM and H2O.ai announced a strategic global partnership focused on combining IBM POWER Systems and H2O Driverless AI. The new partnership would address the AI demands of the enterprise. This joint solution is ideal for financial services, retail, manufacturing, IoT, and healthcare industries.
H2O.ai has selected IBM POWER Systems as a strategic partner for Driverless AI because of their leading-edge capabilities designed specifically for AI workloads. By partnering with H2O.ai, IBM further expands its ecosystem for enabling businesses to harness AI for competitive gain.
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Through the multi-year agreement, IBM and H2O.ai customers can now:
- Use Driverless AI on IBM POWER Systems to accelerate machine learning insights by up to 5X on IBM POWER9 processor-based Power Systems
- Deploy the joint solution to leverage GPU-accelerated machine learning on IBM POWER Systems to gain insights and transform their business
- Take advantage of IBM’s easy on-ramp deep learning toolkit, PowerAI, with H2O Driverless AI’s automated machine learning capabilities
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“H2O.ai is a leader in the 2018 Gartner Machine Learning and Data Science Platforms and has built a strong ecosystem and reputation amongst enterprise customers for our innovations in AI and commitment to the open source AI community,” said Sri Ambati, CEO and founder of H2O.ai.
Sri added, “H2O’s Driverless AI on IBM POWER9 GPU-accelerated Systems brings the best of breed innovation in AI to customers.”
“IBM is the leader in AI for business and we are building an ecosystem of partnerships, like this one with H2O.ai, to constantly advance our position in the market,” said Sumit Gupta, VP of AI, Machine Learning and HPC at IBM Cognitive Systems.
Sumit added, “As part of this ecosystem strategy, the powerful combination of IBM POWER Systems and H2O.ai’s Driverless AI give enterprises increased ability to apply machine learning to generate extensive value and competitive advantage from their troves of proprietary data.”
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