For humans to be the most productive in their collaboration with machines, they need advanced technology skills that probably exceed their current capabilities. The skills gap must be closed for workers at various levels of competencies and who possess a variety of experiences. Filling such widely disparate skills gaps, bridging the college-to-work gap, and retooling millions of workers into completely new jobs are daunting tasks. Traditional approaches to education have come under pressure due to the costs (student debt in the U.S. is estimated at $1.3 trillion) and questionable efficacy (a late-2016 study showed that nearly half of new college graduates are underemployed). Given the magnitude of the problem, a new approach is necessary. Though not yet widely adopted, adaptive learning is a low-cost, proven, and highly efficient way to equip people from factory workers to physicians with skills — not just in technology, but in other realms as well.
StorageOS also optimises storage, tracking where containers are running and ensuring storage remains as local as possible to keep latency down. It aims to tackle the key weakness of storage for container environments – that container storage is not persistent. That means that when containers cease running, whether for planned or unplanned reasons, storage is lost and not resumed when containers are restarted. Containers are gaining popularity because of their ability to be deployed and scaled rapidly. Organisations can deploy a given number of containers to support a campaign launch, for example, then, if demand spikes, more containers can be added, effectively increasing the parallelised operation of the application. These can also be in different locations, so some containers could be run in-house while additional capacity is run from a public cloud.
The industry should aim to achieve a level of interactive integration and cooperation between analysts and their tools, so that they seamlessly play off of each other’s strengths to be better than their sum. The current place where analyst and automation meet are at the SIEM and the threat intelligence platform. The SIEM is the centre of events. The threat intelligence platform (TIP) is where intelligence is managed by the analyst. Your SIEM and TIP should work well enough together that any events that already correlate to threat intelligence can be viewed in the SIEM while the TIP can still be used to research any probable future threats. The experienced analyst is central to the process for the steps that require their intuition, given all of the possible information, to make a decision. Once they make or review decisions they can quickly deploy any changes to the appropriate systems or channels.
To be sure, a few others could build a similar service, namely Amazon and Microsoft. But they haven’t yet. With help from TrueTime, Spanner has provided Google with a competitive advantage in so many different markets. It underpins not only AdWords and Gmail but more than 2,000 other Google services, including Google Photos and the Google Play store. Google gained the ability to juggle online transactions at an unprecedented scale, and thanks to Spanner’s extreme form of data replication, it was able to keep its services up and running with unprecedented consistency. Now Google wants a different kind of competitive advantage in the cloud computing market. It hopes to convince customers that Spanner provides an easier way of running a global business, a easier way of replicating their data across multiple regions and, thus, guard against outages.
In developing mobile policies, hospitals must address the security of patient information and the need to comply with the privacy and security regulations of the Health Insurance Portability and Accountability Act (HIPAA), notes the Spok report. Some organizations that responded to the survey, in fact, “viewed mobile strategies as primarily a security project concerning HIPAA compliance,” the report points out. However, hospitals’ mobility strategies must extend beyond security to help them reach their organizational goals, Edds says. Kuhnen, similarly, says that hospitals must go beyond mobile security if they don’t want to fall behind. “They need to look at the productive uses of mobile technology—how the technology can make their workflows more efficient and improve user satisfaction.”
To decrease customer churn, you can use predictive modeling to identify the variables that are predictive of customer churn. While you can find drivers of churn manually when the data set is small, you will need to rely on the power of machine learning when you integrate all your data sources. Because integrated data sets can contain many variables, data analysts/scientists are simply unable to quickly sift through the sheer volume of data manually. Instead, to create predictive models of customer churn, businesses can now rely on the power of machine learning. Machine learning is a set of techniques that allow computers to make dynamic, data-driven decisions without explicit human input. In the context of CSM, machine learning helps computers “learn” the differences between users who stay and those who leave.
Wearables may soon not rely on a smartphone, as more than one network-connected smartwatch hit the market. One such smartwatch launching next month was developed by a major network to function as an independent device. Verizon’s new Wear24 smartwatch can connect to Verizon’s 4G LTE network without requiring a smartphone. The smartwatch automatically operates using the user’s existing phone number when sending texts and making calls, according to Verizon. The smartwatch is equipped with an eSIM (Embedded Subscriber Identity Module), which enables the network connectivity. This functions similarly to the SIM card in a smartphone, but is not removable. Integrating eSIMs into IoT devices enables networks to remotely configure device connectivity settings and allow or deny access based on the status of a device owner’s subscription.
The talent shortage is real, and it might get worse before it gets better. As the amount of accessible data grows, data crime is becoming more pervasive. Ransomware, sophisticated extended-duration attacks, phishing and whaling attacks are all targeting large enterprises, government organizations, mom and pop shops and everyone in between. It doesn't help that the rapid growth of data crimes is a relatively new trend, making it hard to find people who are deeply experienced in fighting data crime and who can be thrown into the fire immediately. This gap can have the biggest effect on small business leaders, who often can’t compete with larger companies when it comes to offering the salary and benefits that attract today’s top IT talent. At this point, qualified newly hired professionals command average salaries of roughly $150,000, and that number most likely has room to grow.
"This is the real scare, to not just a particular industry of a particular size, but to everybody. It is a matter of existence," said Aurora. That's where Darktrace's artificial intelligence system comes in, with the latest technology offering called Antigena. Once a threat is identified, Antigena automatically responds by taking proportionate actions to neutralize it and buy security teams enough time to catch up. In essence, it acts like a digital antibody that can slow down or stop compromised connections or devices within a network without disrupting normal business operations. "Human beings are still going to be fundamental, but right now, the kind of attacks — you find it very difficult to figure out and they're so quick that if you look at traditional means, by the time human beings get to respond, it's too late," Aurora explained.
A common request from network operations: “I don’t want to wait for users to phone us about problems, nor do I have time to sift through mounds of data. Tell us who’s having a problem and how to fix it.” True analytics needs to automatically surface insights and recommend useful actions that IT can take to proactively improve user experience. What’s more, the tools should be able to suggest what actions to take to deliver the biggest bang for the buck relative to improving the users’ network experience. ... But what comes out of the machine learning algorithm must be translated back into a plain English recommendation, such as: “By removing the rogue access points interfering with the 5GHz radio of a certain access point you can effectively mitigate 400 client hours of poor client Wi-Fi performance.”
Quote for the day:
"Any powerful idea is absolutely fascinating and absolutely useless until we choose to use it." -- Richard Bach