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H2O.ai launches H2O AI Hybrid Cloud

H2O.ai announces the launch of the H2O AI Hybrid Cloud, a comprehensive AI platform that enables organizations to quickly build, share and distribute AI models and applications use.

The innovative new H2O AI Hybrid Cloud platform enables everyone to innovate and use AI to make better predictions, optimize operations, reduce risks and personalize customer experiences. It has capabilities and automation throughout the data science cycle; This includes connecting with data and preparing it, building and explaining models, using and operating models, and creating and sharing AI applications.

“AI is central to AT & T’s mission to deliver video to our customers, be it wireless, broadband or software-based. We have used hundreds of AI models to support these products and services, for example to protect our customers by classifying transactions for the likelihood of fraud in real time. By working with H2O and their open source tools, including H2O Wave and H2O AI Hybrid Cloud, we will be able to extend these capabilities to all areas of AT&T. ”- Mark Austin, Vice President of Data Science, AT&T

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The H2O AI Hybrid Cloud is used on Kubernetes and enables customers to operate in any cloud, such as Microsoft Azure or on the basis of a local infrastructure on site.

The platform has more than 200 data connections, automatic data visualization, automatic feature engineering, AutoML for table, time sequence, text, image and video data, and machine learning operating technology to help organizations continuously control and improve their models be. The H2O AI Hybrid Cloud is integrated with Snowflake, enabling data engineers to create AI models and classify records using their preferred language – SQL.

“Seasoned data scientists typically took months or more to develop a single model, but today data engineers can quickly deploy their models and grade records using the extensibility capabilities of Snowflake and H2O’s AutoML technology – all within Snowflake and using SQL. “- Snowflake Director of Product Management, Torsten Grabs

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The H2O AI Hybrid Cloud integrates with the recently launched H2O Wave and is designed for organizations that want to give users in their company AI. A lightweight, open source Python development program, this platform makes it easy for developers, data scientists, and machine learning engineers to create sophisticated applications that make effective use of AI models.

“The future belongs to contactless, seamless, smooth automation, supported by in-depth knowledge. Enabled by the H2O AI Hybrid Cloud, AMS.ai brings to life Arogya, a healthcare-optimized automated supply chain platform built on deep insights. ”- Vijay Sarashetti, Co-Founder and CTO of Arogya

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The H2O AI Hybrid Cloud also offers an AppStore that enables organizations to publish and share the AI ​​applications they have created with H2O Wave. The AppStore comes with a number of ready-made applications such as Automatic Insights, Recommendations and LIBOR, which organizations can use to incorporate AI into production even more quickly.

“AI is reshaping the world. Organizations are increasingly adopting AI and need holistic, open, and automated platforms to rapidly build world-class AI models and applications. The H2O AI Hybrid Cloud enables organizations to create AI for virtually any use case, optimize machine learning initiatives, and democratize AI across the organization. ”- Sri Ambati, CEO, H2O.ai

Red Hat OpenShift will certify the platform at the beginning of this year in order to be able to meet the requirements for hybrid and multi-clouds necessary for corporations.

“Red Hat OpenShift, the industry-leading, fully supported, enterprise-grade Kubernetes platform, is optimized for H2O Driverless AI and H2O Open Source, making it easier for customers to deploy H2O.ai products across the hybrid cloud and manage. We are working closely with H2O.ai as the company seeks to certify H2O AI Hybrid Cloud on OpenShift to continue building on that dynamic. ”- Joe Fernandes, Vice President and General Manager, Cloud Platforms, Red Hat

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