There is a disconnect between Microsoft's efforts and expectations – months of development time and testing to produce features and functionality that customers will clamor for – and the reaction by, in electioneering terms, a landslide-sized majority of those customers. In many cases, IT admins simply shrug at what Microsoft trumpets. "I understand the concept of WaaS, and the ability to upgrade the OS without a wipe/re-install is a good concept," one of those polled said. "((But)) let's concentrate more on useful features, like an upgraded File Explorer, a Start menu that always works, and context-sensitive (and useful) help, and less on, 'It's time to release a new feature update, whether it has any useful new features or not.'" Some were considerably harsher in taking feature upgrades to task. "Don't have a clue why they think some of the new features might be worth our time, or even theirs," said another of those polled. And others decried what they saw as wasted opportunities. "It's mostly bells, whistles and window-dressing," one IT admin said. "It seems like no fundamental problems are tackled. Although updates DO every now and then cause new problems in fundamental functionality. Looks like there's at least some scratching done on the fundamental surface – ((but)) without explanation."
Conceptually, IT borrowed a lot of themes from Civil Engineering, one being Architecture. Despite the 3000 years that separate both areas, Architecture & Software Architecture share similar words through the multiple definitions that they have, such as "structure", "components", and "environment". At first, that relationship was really strong because the technology was "more concrete", heavier, and, obviously, slower. Everything was super difficult to change and applications used to survive without an update for quite a long time. But, as computers advance, the world is submerged in a massive flow of information on digital platforms and customers can directly connect to businesses through these channels, existing conditions that demand companies to be able to push reliable modifications to their websites, or applications, every day, or even multiple times throughout the day. This progress didn't happen overnight, and as digital evolved, the technical landscape started to change, reflecting new requirements and problems. In 2001, an initiative to understand these obstacles to develop software, obstacles still relevant to this day, seventeen people gathered in the Wasatch mountains of Utah. From that reunion, "The Agile Manifesto" was created, a declaration based on four key values and 12 principles, establishing a mindset called "Agile".
Banks are now staring at the massive challenge of continuing their digital investments in a cost constrained environment. Getting their workforce ready to develop the technologies, while continuing to deliver value to their customers is another issue. At the same time, they are competing with new digital banks that will undoubtedly come in with newer technology built on modern architecture without the legacy debt. However, there are industry players that may have cracked the code to successful digitalisation. I know of incumbent banks as well as digital banks developing world-class digital capabilities at lower costs, while training their people to make full use of their new digital investments. Recently the finance function of a leading global universal bank adopted a “citizen-led” digital transformation, training 300+ “citizen” developers who identified 200+ new use cases resulting in an annual run rate cost reduction of $15 million. This case study highlights the importance of engaging and upskilling your workforce while contributing to bottom line benefits. Over the last two decades, technology by itself has evolved and now has the ability to transform whole businesses in the financial services sector, similar to its impact on other industries such as retail and media. Traditionally, for banks, technology was a support function enabling product and customer strategies.
Google researchers put RigL to the test in an experiment involving an image processing model. It was given the task of analyzing images containing different characters. During the model training phase, RigL determined that the AI only needs to analyze the character in the foreground of each image and can skip processing the background pixels, which don’t contain any useful information. The algorithm then removed connections used for processing background pixels and added new, more efficient ones in their places. “The algorithm identifies which neurons should be active during training, which helps the optimization process to utilize the most relevant connections and results in better sparse solutions,” Google research engineers Utku Evci and Pablo Samuel Castro explained in a blog post. “At regularly spaced intervals we remove a fraction of the connections.” There are other methods besides RigL that attempt to compress neural networks by removing redundant connections. However, those methods have the downside of significantly reducing the compressed model’s accuracy, which limits their practical application. Google says RigL achieves higher accuracy than three of the most sophisticated alternative techniques while also “consistently requiring fewer FLOPs (and memory footprint) than the other methods.”
While older adversarial attack patterns were algorithmic and easier to detect, new attacks add AI features such as natural language processing and a more natural human computer interaction to make malware more evasive, pervasive and scalable. The malware will use AI to keep changing form in order to be more evasive and fool common detection techniques and rules. Automated techniques can make the malware more scalable and combined with AI can move laterally through an enterprise and attack targets without human intervention. The use of AI in cybersecurity attacks will likely become more pervasive. Better spam can be crafted that avoids detection or personalized to a specific target as a form of spear phishing attack by using natural language processing to craft more human like messages. In addition, malware can be smart enough to understand when it is in a honeypot or sandbox and will avoid malicious execution to look more benign and not tip off security defenses. Adversarial AI attacks the human element with the use of AI augmented chatbots to disguise the attack with human-like emulation. This can escalate to the point where AI powered voice synthesis can fool people into believing that they’re dealing with a real human within their organization.
With a substantial proportion of chips and components coming from the Wuhan region in China, supply chains were already facing delays. After negotiation with suppliers, Harvey's team managed to procure the right equipment on time, air-freighting components to the island from the UK mainland instead of using ferry services as usual. As the state of Guernsey started restricting travel, a local Agilisys team was then designated to pick up the data centers' build. The team's head of IT services Shona Leavey remembers juggling the requirements for the build, while also setting up civil servants with laptops to make sure the state could continue to deliver public services, even remotely. "We were rolling out Teams to civil servants, and at the same time had some of the team working on the actual data center build," Leavey tells ZDNet. "Any concept of a typical nine-to-five went out the window." Given the timeline for the build, it became evident that some engineers would have to go into the data centers to set up the equipment during the early months of summer. That meant the Agilisys team started a long, thorough, health and safety assessment.
The problem is well known among researchers. Take Microsoft's Sept. 1 announcement of a tool designed to help detect deepfake videos. The Microsoft Video Authenticator detects possible deepfakes by finding the boundary between inserted images and the original video, providing a score for the video as it plays. While the technology is being released as a way to detect issues during the election cycle, Microsoft warned that disinformation groups will quickly adapt. "The fact that [the images are] generated by AI that can continue to learn makes it inevitable that they will beat conventional detection technology," said Tom Burt, corporate vice president of customer security and trust, and Eric Horvitz, chief scientific officer, in a blog post describing the technology. "However, in the short run, such as the upcoming US election, advanced detection technologies can be a useful tool to help discerning users identify deepfakes." Microsoft is not alone in considering current deepfake detection technology as a temporary fix. In its Deep Fake Detection Challenge (DFC) in early summer, Facebook found the winning algorithm only accurately detected fake videos about two-thirds of the time.
Instead of testers simply picking work out of this column and working on it till it’s done, they should work with the team to help them understand how they approach testing, the types of things they are looking for and also finding during testing. Doing this with a handful of tasks is likely to help them identify some key themes within their work. For example, are there similar root causes such as usability or accessibility issues, or some hardware/software combination that always results in a bug? Is there something the devs could look out for while making the changes? These themes can be used to create a backlog of tasks that the team can begin to tackle to see if they can be addressed earlier on in the development life cycle. By focusing on the process and not the people, it makes it easier to talk about what testers are doing, how developers and testers could mitigate this work earlier on in the life cycle, and begins to be the seeds of the continuous improvement programme. Leadership in this process is very important. Leaders need to help testers feel comfortable that they are not being targeted as the "problem" within the team, but are actually the solution in educating the team in what risks they are looking for when testing.
At home, most folks use a router provided by their Internet service provider. The home router has a firewall and NAT functionality so your family can safely connect out to your favorite websites, and those websites can send the data you asked for back to you. However, with most employees now working at home, enterprise-grade firewalls at the edge of corporate networks are no longer protecting them or providing the needed visibility for IT to help keep the corporate users safe. That's where having an endpoint security solution that can provide visibility, segment and limit access between different internal networks and laptop devices can come in handy. With CISOs, government employees, and business executives sharing home networks with their 15-year-old gamers and TikTok addicts, it's imperative to extend the principles of least privilege to the systems with important data inside the home network. Meaning that even if a bad actor gains access to your kid's network, your laptop and organization's internal assets stay in the clear. When it comes to proactively protecting against cyber threats, segmentation is one of the best ways to ensure that bad actors stay contained when they breach the perimeter. Because, let's be honest, it's bound to happen.
Quote for the day:
"Challenges are what make life interesting and overcoming them is what makes life meaningful." --Joshua Marine