The leading container software platform for distributed AI / ML and Data Analytics – deployed on-prem, in the cloud, or hybrid.

Just five months after completing the acquisition of BlueData, Hewlett Packard Enterprise Tuesday unleased a new version of its artificial intelligence BlueData big data-as-a-service offering that runs on its high performance Apollo systems backed up by HPE Pointnext deployment services. With the new offering, HPE said BlueData software subscriptions can be ordered with HPE Apollo server and storage infrastructure in a variety of configurations. The new offering is available in the United States, United Kingdom/Ireland, Germany, France and Singapore. "The message is if you have a AI/data science expertise and you are in the five countries we are doing business in, we absolutely want you to be participating in the HPE channel with this technology stack," said Patrick Osborne, vice president and general manager of big data and secondary storage for Hewlett Packard Enterprise. In fact, the new integrated offering signals the start of a partner recruitment offensive aimed at driving high margin, recurring revenue big data opportunities for the channel.

Our customers are living in a data-driven world and the volume of information they generate is growing exponentially. As a result, companies are increasingly investing in the hardware, software, and services needed to gain actionable insights from their data. By 2022, the total addressable market for artificial intelligence/machine learning (AI/ML) and big data is expected to grow to approximately $160 billion.[1] However, according to Gartner, by 2020 half of organizations will lack sufficient AI and data literacy skills needed to extract business value from their data, and they are already demanding easier-to-implement, faster-to-deploy, and more cost-effective solutions for AI/ML and big data analytics.[2] Today, HPE announced that we are acquiring BlueData, a leading provider of AI/ML and big data analytics infrastructure software, which will significantly expand our footprint in the rapidly growing artificial intelligence and big data analytics space.

Robin Systems is simplifying the management and deployment of big data workloads by adding a Kubernetes layer to its platform to deal with stateful container applications running on premises or in a public cloud. This will allow management using standard Kubernetes, which was originally focused on dealing with stateless container management. The Kubernetes infusion is part of Robin Systems' Hyperconverged Kubernetes Platform. The platform supports Kubernetes-based management for big data, stateful databases, artificial intelligence (AI), and machine learning applications. Robin Systems CTO Partha Seetala said that the update allows users to tap into existing workflows and use the same tools for an application management layer overseeing compute and storage.

BlueData, provider of the leading Big-Data-as-a-Service (BDaaS) software platform, today announced the new summer release for BlueData EPIC . This release builds upon BlueData's innovations in running large-scale distributed analytics and machine learning (ML) workloads on Docker containers, with new functionality to deliver even greater agility and cost savings for enterprise Big Data and AI initiatives. Last spring, BlueData introduced support for hybrid cloud environments – leveraging the inherent infrastructure portability and flexibility of Docker containers. This past fall, BlueData delivered a major new release that added deep learning (DL), GPU acceleration, and multi-cloud support to the container-based BlueData EPIC platform. And last month, BlueData announced a new turnkey solution to accelerate AI and ML / DL deployments in the enterprise.

Today we announced the latest release of the BlueData EPIC software platform, with several exciting new innovations for the containerization of Big Data and machine learning workloads. This new'summer release' for BlueData EPIC represents dozens of new features developed by our software engineering team over the past few months. In large part, this new functionality was based on input and collaboration with our rapidly growing roster of enterprise customers. These innovations will deliver even more agility and infrastructure cost savings for our customers' Big Data deployments, along with new capabilities to accelerate their AI and machine learning initiatives – whether on-premises, in the public cloud, or in a hybrid approach. Enterprises in all industries and across all geographies are embarking on digital transformation.

Kids love to play in physical sandboxes. Developers love to "play" in virtual sandboxes. BlueData, which offers a new-gen big-data-as-a-service (BDaaS) software platform, has made available a new environment for AI and machine-learning developers to try out new ideas and have fun testing them. This is a new turnkey package that enables accelerated deployment of artificial intelligence, machine learning and deep learning applications in the enterprise. Turns out you can't build these applications too quickly.

We all know that Artificial Intelligence (AI) is here to stay. We experience AI everywhere and enjoy its benefits without even realizing it. From streaming video services like Netflix, which learn our viewing behaviors and patterns so we spend our valuable time watching the shows we like best; to digital assistants like Amazon's Echo which can recognize speech patterns to follow our commands and answer our questions; to using AI-powered apps like Lyft or Google Maps to hail the closest ride or navigate around traffic and get from point A to point B, AI is now embedded in our daily lives. Each of these everyday consumer applications uses machine learning (ML) for their AI use cases. But it's not just the consumer technology giants and startups that are using ML technology to power AI-enabled applications; enterprises in virtually every industry are now exploring ML for a wide range of different AI use cases, ranging from fraud detection to medical diagnosis, stock market prediction, and autonomous driving to name just a few.