Don't do that: Rather, accelerate business transformation efforts now to put yourself in better position after the pandemic passes, say experts and CIOs. "You have to avoid the tendency to slash and burn your transformation and revert back to your traditional working model, which is human nature," Steve Bates, global leader of KPMG's CIO center of excellence, tells CIO.com. From the dot-com bust to 9-11 to the 2008 financial crisis, disruptions have stymied digital strategies. CIOs even have a cost-cutting playbook that starts with hardware haircutting and elimination of new projects, according to Forrester Research. But organizations that contained costs during past disruptions felt pressure from companies that took a pro-investment approach when the global economy rebounded.
The oil and gas industry is massive and highly-diversified in its operational characteristics between the upstream, mid-stream and downstream sectors of the industry. Even within each sector, there are distinct differences; offshore gas/oil rigs have a completely different set of requirements to onshore well pads in the fracking industry. However, every sector is susceptible to the boom and bust cycles that have traditionally characterised the oil and gas industry. All of this makes oil and gas ideal for adopting IOT technologies to address a whole range of problems and risks, and to smooth out the ups and downs of the business cycle. Where are oil and gas companies today with edge computing adoption?
Red Hat, Inc., the world's leading provider of open source solutions, today highlighted that more organizations are using Red Hat OpenShift as the foundation for building artificial intelligence (AI) and machine-learning (ML) data science workflows and AI-powered intelligent applications. OpenShift helps to provide agility, flexibility, portability and scalability across the hybrid cloud, from cloud infrastructure to edge computing deployments, a necessity for developing and deploying ML models and intelligent applications into production more quickly and without vendor lock-in. AI/ML represents a top emerging workload for Red Hat OpenShift across hybrid cloud and multicloud deployments for both our customers and for our partners supporting these global organizations. By applying DevOps to AI/ML on the industry's most comprehensive enterprise Kubernetes platform, IT organizations want to pair the agility and flexibility of industry best practices with the promise and power of intelligent workloads. As a production-proven enterprise container and Kubernetes platform, OpenShift delivers integrated DevOps capabilities for independent software vendors (ISVs) via Kubernetes Operators and NVIDIA GPU-powered infrastructure platforms.
Terjmat is a multilanguage translation service integrated with the Telegram application that you can use to make chatbot translations easier. The IBM Language Translator service can connect to other IBM services, and these services can be linked to the Telegram application using a Node-RED app. When you link the services, users can easily use the translation app by sending text or voice to your bot. In this tutorial, I walk you through the steps to create a Node-RED boilerplate that's available on IBM Cloud and link Terjmat to a Telegram app as the user interface using Node-RED flows – in under 20 minutes and using only IBM Cloud services. Note: Make sure to create instances of all of the required services for this project before moving to the next steps.
In this new year, it is crucial for the CIO to carefully examine and determine which technologies are the best fit for their organization. A recent Accenture report found that 83% of companies want systems that will allow them to pivot into new strategic directions. Soon, we anticipate that organizations will rely on key technologies to help them advance and drive innovation, including multi-cloud, data and analytics, artificial intelligence (AI) and increased security capabilities. By embracing these forces for change, it will allow organizations to be more secure, current and innovative to keep up with the competition. Embracing the cloud is imperative to a successful digital transformation across the entire enterprise.
There are plenty of tools and point solutions that address bits and pieces of the challenge of delivering artificial intelligence (AI) and Internet of things (IoT) applications. C3.ai's focus is on delivering an end-to-end platform for developing, deploying and running these applications in production at scale. Whether customers use every aspect of the C3.ai platform or not, big enterprise-scale companies seem to be attracted by that promise of quickly developing and running innovative, data-driven applications at scale. There was plenty of evidence of that fact at C3.ai's February 25-27 Transform conference in San Francisco, where customers including Bank of America, Shell, 3M and Engie detailed their deployments. C3.ai's cloud-first platform is comprehensive, addressing the needs of developers, data engineers and data scientists, and the operational teams challenged with bringing applications into production at scale.
With Novel Coronavirus (2019-nCov) causing a bigger number of deaths than the 2003 SARS episode and giving no indications of containment, one thing turns out to be clear: the sickness is out of our control at this moment and we will need to get innovative if we need to catch it. The illness began in China back in December and keeping in mind that there's been a lot of discussion around how it was taken care of, it's essential to perceive that our energy is best spent discovering solutions. Presently, like never before, the world needs to meet up. We need to deliver the best personalities in healthcare and technology and innovate in case we will outflank this sickness. The ongoing coronavirus outbreak (or COVID-19, if you need to be progressively precise) is changing the manner in which individuals live their day-to-day lives and interact with one another.
This is the second of a three-part blog post on the Jupyter Notebook ecosystem. Here, I'll discuss various tools that I use alongside Notebooks, and how I incorporate them in my day-to-day work. You'll find Part One in this link. Let's jump right into it. Recall that in Part One, we identified (1) two directions of ecosystem growth, i.e, cloud adoption and software production, and (2) three forces of change driving the evolution of our tools, especially in the Jupyter Notebook ecosystem: In Part Two, we'll expound upon these key drivers and investigate how the Jupyter Ecosystem grew to respond to these forces--perhaps via a plugin, a new tool, or a new workflow. Lastly, we'll put them together as I share how I use notebooks in my day-to-day.
By- Amith Singhee At the dawn of the Information Age in the 1970s, the role of Information Technology (IT) was limited to'computing plumbing' - to keep the networks and computers working. In the 90s and 2000s, it evolved into an enterprise shared servicesmodel that was essential for operational efficiency, cost takeout and decision support. Today, IT is witnessing another shift that increasingly requires the Chief Information Officer organization to act as a partner in defining business strategy and driving topline growth via IT-driven business transformation. To realize this, the IT delivery platform that includes infrastructure, applications, processes and roles of people -needs to be scalable and adaptable tokeep pace with the rapidly changing business and operational needs, and, hence, transform to a hybrid cloud IT architecture. The transformation will involve four phases: Advice for Cloud, Move to Cloud, Build for Cloud and Manage on Cloud.
Neville Vincent says the combination of hyperconverged infrastructure, edge computing and AI is driving value and insights to new levels. While cloud has been a key component to AI's exponential growth and its availability on nearly every technological device, the combination of hyperconverged infrastructure HCI), edge computing and AI provides the ideal environment to uncover patterns in data from multiple devices and predict future performance or issues. It is driving value and insights to new levels. The adoption of hybrid cloud -- enabled by HCI and public cloud and combined with AI and data gathered from the edge -- offers granular visibility into operations, enabling real-time, comprehensive and actionable intelligence. Through this combination businesses will become self-learning, flexible, self-determining and able to adopt next-generation infrastructure to help realign their operations, personnel, business and even business models.