Daily Tech Digest - August 06, 2020

It’s time to think differently about how to develop cloud computing talent

“Certifications help set a benchmark for a conversation, but we tend to verify during interviews. Personally, I’m far more interested in curiosity, a desire to solve a problem, being self-starters — this talent goes much further as you develop it,” he adds. Sean Farrington, SVP EMEA at Pluralsight, also believes that developing and maintaining cloud computing skills once talent is in place is a challenge. Businesses “need the ability to accurately map skill levels and proficiencies within teams and put in place tailored learning pathways to address knowledge gaps,” he says. Success in this requires a reassessment of how learning is undertaken. Pluralsight, for example, found that 40% of IT professionals prefer learning online, either through self-paced or instructor led courses, rather than in classroom-based setups. Commenting on this, Farrington adds: “Companies are nothing more than the sum of their parts, and so business leaders must listen to the needs of their employees and implement an appropriate learning environment. In this case, the ability to upskill on demand and in bite-sized chunks is likely to keep cloud computing talent motivated, current and project-ready.”

Working With Intelligence: How AI Will Reshape Remote Work

HR managers and associates are required to undertake many tasks that allow them to comply with legal requirements for hiring as well as the policies issued by their respective companies. Finding the right candidate can be a time-consuming process when all of these compliances are taken into account. However, businesses can create remote positions that ease the load for managers or in-house employees. One of the criticisms about WFH surrounds a business’ ability to monitor the productivity and quality of output from external workers. Fortunately, artificial intelligence and machine learning are on hand to help out. Team leaders, supervisors and managers alike can turn to machine learning programs to monitor staff performance in a non-invasive and accurate manner. More modern systems are capable of utilising information through survey-based tools in order to provide impartial performance reviews and deliver accurate reports that indicate respective employee strengths and weaknesses on a case-by-case basis. Here, technology takes the lead and creates a level of analysis that’s difficult to replicate through human management. This is especially true for companies with a large number of employees that work from remote locations.

Overcoming the Evolving DevOps Skills Gap

It’s clear that in-demand skills don’t always remain in vogue for very long. To help limit the variability in expertise needed from year to year, companies should invest in tools that don’t constantly require learning new techniques to operate and that can automate tasks whenever possible. For example, a growing number of companies work with multiple cloud providers to ensure their applications and services are always available. While a multi-cloud strategy offers benefits, it also likely means running different projects on different providers’ clouds. To limit the amount of skills needed, companies can select container tools that deploy easily to multiple cloud environments without significantly affecting application topology.  Furthermore, tools that automate repetitive processes can help your company reconcile a skills gap. Leveraging solutions that automate processes tied to risk, compliance, and governance can help people focus on their core responsibilities and objectives rather than conducting manual data analyses or attempting to learn data-privacy law.  Thoughtfully employing technology can also help close skill gaps. With everyone now working remotely, there are fewer opportunities for in-person training and mentoring.

Why developers are falling in love with functional programming

A function with clearly declared in- and outputs is one without side effects. And a function without side effects is a pure function. A very simple definition of functional programming is this: writing a program only in pure functions. Pure functions never modify variables, but only create new ones as an output. (I cheated a bit in the example above: it goes along the lines of functional programming, but still uses a global list. You can find better examples, but it was about the basic principle here.) Moreover, you can expect a certain output from a pure function with a given input. In contrast, an impure function may depend on some global variable; so the same input variables may lead to different outputs if the global variable is different. The latter can make debugging and maintaining code a lot harder. There’s an easy rule to spot side effects: as every function must have some kind of in- and output, function declarations that go without any in- or output must be impure. These are the first declarations that you might want to change if you’re adopting functional programming.

IoT Automation Trend Rides Next Wave of Machine Learning, Big Data

Automation takes on a different aspect when IoT data is introduced, according to Susan Foss, product manager for real-time visualization and analytics at Esri, the geographic information system (GIS) giant. What is different? “It’s the nature of the data being collected,” she said. “Organizations have never had this type of information before or at this granularity of time-space detail.” “Before it was more periodic. Now they have it in the form of a living, breathing, constant supply,” she added. That ushers in event processing architectures, changes the pace with which teams have to work with data, and augers more automation. Foss said Esri is working with users to connect fast-arriving IoT data to location data. The goal is to create immediate visualizations of data on a map. This requires, Foss said, “a delicate balance of compute horsepower against the incoming real-time data, as well as static data sources that might need to be used with it.” And, real-time activity mapping is going indoors in the face of the COVID-19 pandemic. To that end, Esri recently updated its ArcGIS Indoors offering with new space planning templates. The software uses beacons and Wi-Fi to collect data for display on a live map showing activity in offices and other physical plants. Clearly, such capabilities have special import in the wake of coronavirus.

The Right Way of Tracing AWS Lambda Functions

This increased distribution and interdependency is precisely why distributed tracing has grown to be so important and valuable. Distributed tracing is a monitoring practice that involves your services to collectively and collaboratively recording spans that describe the actions they take in servicing one request. The spans related to the same request are grouped in a trace. In order to keep track of which trace is being recorded, each service must include the trace context in its own requests towards other upstream services. In a nutshell, you can think of distributed tracing as a relay race, the discipline of track and field sports in which the athletes take turns running and passing one another the baton. In the analogy of distributed tracing as a relay race, each service is an athlete and the trace context is the baton: if one of the services drops it, or the handoff between services is not successful because, for example, they implement different distributed tracing protocols, the trace is broken.Another similarity between distributed tracing and relay is that, while each of the single segments of the race matters and can make you lose the race, you need to be fast in each segment to excel.

Evil AI: These are the 20 most dangerous crimes that artificial intelligence will create

At the bottom of the threat hierarchy, the researchers listed some "low-concern" applications – the petty crime of AI, if you may. On top of fake reviews or fake art, the report also mentions burglar bots, small devices that could sneak into homes through letterboxes or cat flaps to relay information to a third party. Burglar bots might sound creepy, but they could be easily defeated – in fact, they could pretty much be stopped by a letterbox cage – and they couldn't scale. As such, the researchers don't expect that they will cause huge trouble anytime soon. The real danger, according to the report, lies in criminal applications of AI that could be easily shared and repeated once they are developed. UCL's Matthew Caldwell, first author of the report, said: "Unlike many traditional crimes, crimes in the digital realm can be easily shared, repeated, and even sold, allowing criminal techniques to be marketed and for crime to be provided as a service. This means criminals may be able to outsource the more challenging aspects of their AI-based crime." The marketisation of AI-enabled crime, therefore, might be just around the corner. 

Organic data-transfer technology holds promise for IoT

Significantly, point-to-point links using devices made of organic matter could solve some sustainability issues, according to the U.K.'s Newcastle University. The tech industry has long wrestled with questions about how to encourage and make economical the recycling of hard-to-breakdown traditional electronics. LEDs are full of heavy metals, for example. Increasingly rapid lifecycle upgrades have exacerbated the challenges, and as IoT deployments expand, those questions could become even more pressing. OLEDs could be a solution, but data rates haven't been that great—they're not as powerful. At Newcastle University, researchers believe a new type of OLED could enable the faster data speeds required in a VLC-driven IoT communications network. Significantly, the OLED would be sustainable, since OLEDs are natural, organic and free of eco-unfriendly heavy metals. OLEDs have achieved around 10 Mbps speeds with add-on equalization algorithms and wavelength division multiplexing, whereas eco-unfriendly LEDs churn a healthy 35 Gbps. Equalization is a process where a specific band's energy is increased or decreased to level things out and improve data rates and bandwidth.

What Is Fintech And How Does It Affect How I Bank?

Fintech helps expedite processes that once took days, weeks or even months, like requesting a credit score report or sending an international money transfer. Platforms like Upstart and TransferWise accomplish these tasks in a fraction of the time as was the norm even five years ago. There’s been speculation about how fintech might help expedite traditionally red-tape-bound processes like distributing economic stimulus funds. Fintech also holds the potential to improve financial inclusion: In some parts of the world, fintech fills needs for the unbanked, where governmental or institutional support is lacking. Part of the reason fintech has the ability to streamline traditionally clunky processes is because it’s based in ones and zeros versus human skills and opinions. While many fintech platforms include elements of both traditional brokers/advisors and algorithms, others help users navigate financially complex tasks without interacting with a real, live human at all. For instance, today’s consumers can bypass traditional bank branches for things like applying for a loan (Lending Club) or even a mortgage (Better.com). Casual investors no longer need to meet face-to-face with financial experts to painstakingly go over the ins and outs of their portfolios—they can peruse their options online, or even enlist the help of chatbots to make decisions.

People: The one constant in an ever-evolving time of change

Despite the emphasis on speed, however, it is important that people remain a constant, central focus of the process. As such, a new, broadly applicable approach to change management is necessary to ensure clients, customers, and employees reach and maintain success. The creation of innovative solutions, made possible by tapping into lucrative fintech partnerships and digital initiatives, should be focused on building a strong, organizational culture that will effectively support people through these changes. As we put people first in the change model, some of our partners, and one regional northeast bank in particular, recently reinforced how thinking outside the box can pay it forward for change. The CEO utilized an innovative approach to leverage the role of bankers in the process. Rather than give the core responsibility to the digital and IT teams, he provided bankers and sales professionals a seat at the transformation table. By integrating front-end bankers into the core change management team, high performing bankers were able to think about front-end, client-facing concerns that other members of the team may not have experienced.

Quote for the day:

"Either write something worth reading or do something worth writing." -- Benjamin Franklin

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