Red Hat Ansible Automation Platform is growing in prominence within OpenShift and the industry in general
Ansible’s popularity has prompted a new round of key partnerships to expand OpenShift’s ecosystem
Red Hat Ansible has matured into a shining star, not only among OpenShift’s portfolio, but the industry in general for its ability to abstract the complexity of building and operating IT automation at scale as part of enterprises’ business transformations.
The incremental consolidation of the UK enterprise telecoms market continues in light of broader national combinations, with further deals inevitable.
Although driven by financial imperatives in a highly competitive market, these developments reflect a broader re-segmentation in the context of the current economic environment.
Following the creation of the Virgin Media O2 50:50 joint venture between Liberty Global and Telefónica via the merger of their respective Virgin Media and O2 UK businesses, there has been an increasing pressure on Vodafone, BT, and other players to improve investor returns by creating a greater scale through mergers and acquisitions.
Fujitsu is the latest infrastructure vendor to enter the market of high-performance computing as a service (HPCaaS) with the ‘Fujitsu Computing as a Service (CaaS)’ portfolio.
Competitors in this market include Hewlett Packard Enterprise (HPE), Lenovo, IBM, Dell Technologies, Atos, Amazon Web Services (AWS), Microsoft Azure, Google Cloud, Oracle Cloud, and Alibaba.
Fujitsu announced the launch of the Fujitsu CaaS portfolio in Japan last month, a services platform to enable commercial organizations to access high-end HPC capabilities to run complex artificial intelligence (AI) workloads via the public cloud. ‘Fujitsu Cloud Service HPC,’ the first services offering made available as part of the CaaS portfolio, is based on Fujitsu’s Supercomputer PRIMEHPC FX1000 servers running on ARM A64X chips, the same processors behind the world’s fastest supercomputer, Fugaku. Fujitsu has combined these supercomputing capabilities with software to deploy a wide range of AI and machine learning (ML) applications. Continue reading “Fujitsu Takes a Shot at Big Cloud with New HPC On-Demand Offering”→
The Nokia Bell Labs and Equideum Health collaboration will leverage data generated from wearables and home health devices.
Analytics will be fundamental in aiding clinicians, pharmaceutical companies, and researchers to rapidly gain insight from the data as well as shorten clinical trial timelines.
In April 2022, Nokia Bell Labs and Equideum Health announced a partnership focused on empowering individuals to own and benefit from their personal health data. The collaboration will leverage the rapidly expanding datasets generated from wearables and other edge devices, including the growing set of in-home medical devices. The central premise is that while health data is increasing exponentially, no one has figured out a way to collect it, centralize it, and use it for near real-time meaningful insights. Edge computing, AI, ML, and blockchain technologies are now available to accomplish this by collecting and analyzing diverse data types from a wide variety of devices (e.g., wearables, sensors, smartphones, and video feeds). The partners also expect to empower a flood of innovation, without companies worrying about sharing proprietary information or individuals worrying about sharing their personal information without knowing who has access to it. Beneficiaries of this vision will include consumers, healthcare providers, pharmaceutical companies, researchers, institutions, medical device manufacturers, and potentially a slew of startups excited about access to reams of high quality, verifiable health data.
Companies rely upon data lakes to store massive amounts of unstructured data. However, data lakes are not equipped with the necessary tools for deep analysis.
With Google’s BigLake, users can utilize analysis tools to query their data from a single platform, avoiding the risk and expense of moving data to a platform with more functions.
The ever-increasing amount of data collected by businesses, governments, and related organizations creates both opportunities and problems; the ability to collect and analyze data allows companies to understand their customer’s preferences quickly and accurately. At the same time, the amount of data ingested continues to grow exponentially, overwhelming efforts to manage and analyze the data effectively. Creating even more challenges in data collection has been the shift from the orderly, defined tables of structured data stored in a data warehouse to the exabytes of raw unstructured data, including text messages, audio files, videos, and all of the by-products of the digital world. Continue reading “Google Unifies Data Storage with BigLake “→
At Domopalooza 2022, Domo announced a suite of low-code data app tools designed to help customize the way data is presented to end users.
Domo launched pre-designed data apps, or solution accelerators, to target common business challenges in the retail, consumer packaged goods, and financial services industries.
Ideally, successful advanced analytics deployments should lead to more intelligent actions by line-of-business users. The market has talked for years about concepts such as data democratization and generating data-driven insights, but enterprises still struggle with getting a large portion of their teams to take actions that are informed by data analytics. Numerous suggestions such as role-based training, model explainability, intuitive dashboards, user-friendly tools, and executive-led initiatives have been made, but with varying degrees of effectiveness. Continue reading “Domo Tackles Challenge of Getting to More Intelligent Actions with Launch of Data Apps”→
• Radian Arc, a Perth-based edge infrastructure provider is helping telco monetize 5G with cloud gaming, but is turning its sights on enterprise applications.
• Radian Arc’s built for purpose edge infrastructure and partner marketplace could offer a template for a CAPEX free way for telcos to monetize 5G.
Radian Arc, founded only in 2020, is making a name for itself in the emerging cloud gaming industry. Cloud gaming works largely the same way as video streaming services, with content and processing stored and run on remote servers with the visual outputs of the game being streamed to an end user device. Radian Arc, however, is not a gaming company, instead positioning as an Infrastructure as a Service (IaaS) provider, specifically focusing on providing graphical processing unit (GPU) and storage solutions. However, unlike IaaS providers in the public cloud space like AWS or Azure, or traditional private cloud IaaS, Radian Arc is focused exclusively on delivering their infrastructure at the edge of telecom operator networks.
• IBM leveraged Deep Blue, a supercomputer, to victory over chess champion Gary Kasparov and Watson’s subsequent victory over Jeopardy champion Ken Jennings to highlight the promise of AI.
• IBM hoped to expand Watson beyond game playing to solving problems that had proven intractable to business managers. Seeking a challenge, IBM adapted Watson to diagnose and treat cancer.
IBM’s experience developing the platform for Jeopardy gave the company hope that it could broaden Watson’s capabilities. Key to the success of Watson’s victory at Jeopardy was the development of DeepQA, a specialized software architecture that, according to IBM, “generates a wide range of possibilities and for each [query] develops a level of confidence by gathering, analyzing, and assessing evidence.”
Databricks Lakehouse for Retail is an integrated platform to help retailers tackle specific industry challenges, such as demand forecasting and supply chain inventory provision.
The product helps users gain insights from data, either through traditional analytics or by leveraging Databricks’ AI tools.
Advanced analytics firm Databricks, known for its AutoML capabilities, has launched its first industry-specific product, Databricks Lakehouse for Retail. It is a savvy move to target the retail sector, which has been shaken to the core during the global pandemic, with supply chain disturbances and a massive shift towards e-commerce accelerating trends that would have taken many years in normal circumstances. Against this backdrop, retailers are looking to optimize their data to better manage inventory issues and supply chains and to improve their ability to forecast demand and personalize marketing campaigns for customers. Continue reading “Landscape for AI-Based Vertical Solutions Heats Up as Databricks Unveils Offering for Retail Companies”→
DataRobot Core incorporates tools for data scientists that the company gained from its acquisition of Zepl in May 2021.
The product offers specialized capabilities that enable users to toggle between the development of customized machine learning models and the use of AutoML for experimentation.
DataRobot’s mission is to help enterprises implement ‘Augmented AI’ by offering products that enable users to combine human intelligence with machine automation. The DataRobot AI Cloud platform facilitates customers’ ability to toggle between automation and human intervention, so that they can adjust their AI strategy as needed throughout the duration of a project’s lifecycle. To support this strategy, the company launched DataRobot Core in December 2021. The platform enables data scientists to use the tools and languages they prefer, to speed up experimentation and accelerate AI deployments. Continue reading “DataRobot Launches Solutions Aimed at Combining Human Intelligence with Machine Automation “→