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Cloud Computing


Google Parent's Stock Soars on Gangbuster Earnings

WSJ.com: WSJD - Technology

Google blasted through the coronavirus pandemic with gangbuster earnings, just a week after U.S. prosecutors sued the company for operating a purported illegal monopoly in its flagship search business. Alphabet Inc. reported a third-quarter profit of $11.2 billion, well outstripping analyst estimates. As importantly, digital advertising revenue of $37.1 billion was up compared with last year, marking a turnaround from a quarter earlier, when the company recorded the first drop in the category in company history. Cogs across the Alphabet empire were clicking. Helped by stay-at-home trends, YouTube pulled in more than $5 billion in advertising for the first time, gaining 32% over the same period a year earlier.


How IBM Research Is Differentiating Its Hybrid Cloud Platform with AI

#artificialintelligence

AI has already begun to automate many non-mission critical business processes, including aspects of customer service and human resources. As the technology advances, new opportunities continue to emerge, in particular AI's ability to automate the movement to, and management of mission-critical workloads on hybrid cloud environments. Many businesses--especially those in highly regulated industries such as telecom, financial services and healthcare--are hesitant to move mission-critical workloads to the cloud. In fact, data from multiple sources reveals that only 20 percent of all workloads have moved to the cloud. Businesses further along in their journey understand the benefits of cloud use and often have already turned to the cloud for non-mission critical workloads. The accelerated proliferation of mission-critical applications--combined with the fact that more than 70 percent of organizations using public cloud are working with multiple vendors--means companies must approach the migration of these applications to a hybrid cloud environment using a four-phased approach: advise, move, build and manage.


5 edge computing predictions for 2021

#artificialintelligence

Forrester has released a bundle of tech predictions for 2021, and part of it is a firm claim about edge computing: 2021 is the year it will finally become a real value. "Until now, edge computing was promising but still developing. In 2021, new business models will emerge that facilitate the deployment of edge in production," Forrester said in a summary of its predictions. The new business models that will push edge computing "from science project to real value" in 2021 are largely based around two factors, Forrester said: Cloud platforms having to compete with artificial intelligence and the widespread proliferation of 5G will make edge use cases more practical. With those two drivers in mind, Forrester made five predictions about how the tech world will evolve in 2021 that will directly impact edge computing.


#cloudcomputing_2020-10-26_04-51-01.xlsx

#artificialintelligence

The graph represents a network of 2,067 Twitter users whose tweets in the requested range contained "#cloudcomputing", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 26 October 2020 at 12:02 UTC. The requested start date was Monday, 26 October 2020 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 7,500. The tweets in the network were tweeted over the 3-day, 9-hour, 0-minute period from Thursday, 22 October 2020 at 14:58 UTC to Sunday, 25 October 2020 at 23:58 UTC.


5 Common Obstacles of Digital Transformations

#artificialintelligence

Digital transformations have become a global trend in recent years. To be clear, in mainstream understanding, the term means to increase the use of data, which can then help us to build "smarter" machines, predict the future, dig out insights, eliminate human errors and maximize efficiency. However, according to the stats released by Boston Consulting Group (BCG) and McKinsey & Company, only about 30% of digital transformation projects ended up successfully. The result keeps us wondering: What are the key issues to account for such high failure rate? And more importantly, how can we resolve these issues?


What Is Edge Computing And How It Will Change Future?

#artificialintelligence

What Is Edge Computing And How It Will Change Future? Is It All sunshine And Rainbows Though? What Do The Experts Have To Say? What Can You Do With Edge Computing? What Is Edge Computing And How It Will Change Future?


Facebook launches cloud gaming service with only free-to-play games

Washington Post - Technology News

"To install games right now, they have to go to an app store or client, have to decide they want to download, it takes three to five minutes to download, organize their home screen and have the memory on their phone," Rubin said. "It sounds like these are small problems, but the actual funnel from that ad to the install is quite a large drop off. Not a lot of games get installed based on knowledge. If we can get rid of that funnel drop or at least greatly minimize it, developers will be able to reach more consumers, and consumers will be trying more games."


How AIOps can Improve Efficiency in Federal Government

#artificialintelligence

Given the pace at which new applications are changing the IT scene consistently, it is critical to deploy monitoring systems that ceaselessly track the business impact. It is here that AIOps can have any kind of effect, distinguishing the connections and moving to a predictive mentality that will drive the evolution of enterprise IT and the link between IT and business. Obviously, enterprise leaders know that! A few factors have met up to make way for AIOps. The progress to the cloud has made enterprise IT a convoluted recommendation exacerbated by a distributed and complex multi-cloud environment.


Openness a Big Advantage as Edge Grows, IBM Says

#artificialintelligence

A large computational build-up is predicted to occur on the edge in the coming years, as organizations look to capture and act upon data as soon after it's generated as possible, when it has the highest value. Today, there are few standards and protocols defined for how all this is going to work. But in the meantime, hardware and software providers, including IBM, are espousing the benefits of an open ecosystem approach. The edge, which includes server rooms, cell towers, and smaller data centers deployed in the field, is set to proliferate over the next five years, according to the IDC. By 2025, 50% of new on-premise infrastructure will be deployed in edge locations, up from 10% today, the company says.


Splunk takes aim at multicloud, machine learning and observability - SiliconANGLE

#artificialintelligence

Splunk's Data-to-Everything Platform is an all-encompassing suite of analytics tools that help enterprises to search, correlate, analyze, monitor and report on data in real time, available through its Splunk Cloud and Splunk Enterprise products. Today's slew of updates at the virtual event are all about expanding customer's multicloud capabilities, giving them new ways to set the right data strategy and improve access to the information their businesses generate, Splunk said. For example, the Splunk Data Stream Processor, an event streaming platform, is being updated with new capabilities that enable it to access, process and route real-time data from multiple cloud services, including Google LLC's Cloud Platform and Microsoft Corp.'s Azure Event Hub. In addition, event data now gets enriched with lookups and machine learning functionality that helps to minimize compute loads and provide more accuracy when searching through this data. Moreover, the Data-to-Everything Platform is getting a new Splunk Machine Learning Environment that will make it easy for companies to build and operationalize machine learning models by bringing data from multiple sources into a single platform.