DoH isn't turned on by default for everyone. Google is currently running a limited experiment with a small number of users to see how DoH fares in a real-world test. Details here. Unlike Firefox, which forces all DoH traffic to Cloudflare by default, Chrome's DoH support is different. After DoH is enabled in Chrome, the browser will send DNS queries to the same DNS servers as before. If the target DNS server has a DoH-capable interface, then Chrome will encrypt DNS traffic and send it to the same DNS server's DoH interface. This prevents Chrome from hijacking an operating system's DNS settings, a sensible approach in enterprise environments. ... Next year, Microsoft plans to roll out a new version of its Edge browser, rebuilt on the Chromium codebase. A Microsoft spokesperson told ZDNet the company is supportive of DoH, but they couldn't share their exact plans. However, the Chromium-based version of Edge already supports DoH. ... Mozilla was the organization that pioneered DoH's creation together with Cloudflare. Support for DoH is available in stable versions of Firefox already. You can enable it via the browser's Settings section, in the Networking section. See instructions here.
Evolutionary algorithms have been around for a long time. Traditionally, they’ve been used to solve specific problems. In each generation, the solutions that perform best on some metric — the ability to control a two-legged robot, say — are selected and produce offspring. While these algorithms have seen some successes, they can be more computationally intensive than other approaches such as “deep learning,” which has exploded in popularity in recent years. The steppingstone principle goes beyond traditional evolutionary approaches. Instead of optimizing for a specific goal, it embraces creative exploration of all possible solutions. By doing so, it has paid off with groundbreaking results. Earlier this year, one system based on the steppingstone principle mastered two video games that had stumped popular machine learning methods. And in a paper published last week in Nature, DeepMind — the artificial intelligence company that pioneered the use of deep learning for problems such as the game of Go — reported success in combining deep learning with the evolution of a diverse population of solutions.
First, AI systems must be subjected to vigorous human review. For example, one study cited by a White House report during the Obama administration found that while machines had a 7.5% error rate in reading radiology images, and humans had a 3.5% error rate, when humans combined their work with machines the error rate dropped to 0.5%. Second, much like banks are required by law to “know their customer,” engineers that build systems need to know their algorithms. For example, Eric Haller, head of Datalabs at Experian told us that unlike decades ago, when the models they used were fairly simple, in the AI era, his data scientists need to be much more careful. “In the past, we just needed to keep accurate records so that, if a mistake was made, we could go back, find the problem and fix it,” he told us. ... Third, AI systems, and the data sources used to train them, need to be transparent and available for audit. Legislative frameworks like GDPR in Europe have made some promising first steps, but clearly more work needs to be done.
Dealing with workplace pressures and functioning well under stress demands an ability to manage our emotions. People with higher levels of emotional intelligence are more aware of their internal thermometer and therefore better able to manage their stress levels. They tend to have better-developed coping mechanisms and healthy support systems that keep working effectively even in tough situations. The increasing rate of change in the workplace is likely to increase work-related stress and boost the value of those who can manage it. ... Everyone wants to be heard and understood. The ability to listen well and respond to others is crucial for developing strong working relationships. Many of us, though, aren’t as good as we could be at really listening to what others are saying. Because of their ability to understand others, highly emotionally intelligent people are in a better position to put their own emotions and desires aside and take others into account. Their ability to pick up on people’s emotions, through tone of voice and body language, come in handy in team settings.
As a general rule, the biggest disadvantages a startup has when competing against giants is that it simply doesn’t have access to the same opportunities. Whether you’re talking about hiring the smartest people or investing in services that cost a fortune, big companies may not be doing something radically better, but they sure do have more resources to work with. That is especially the case in the cyber security space. According to Crisler, “Less than 1 percent of the companies in the United States have the resources to implement cyber security in the way that it has been designed toda. Most small- and mid-sized companies do not have budgets nor cyber security experts at their disposal, yet all of the products and services that exist in the market require money, expertise, or both.” And for those reasons, Dark Cubed doubled down on the value proposition of catering to those smaller companies. Whether your company is in the cyber security space or not, leveling the playing field for smaller businesses to compete with giants will both open the market to a lot more potential clients as well as create a value proposition most prospects can’t ignore.
What we’re currently seeing is fewer and fewer skills and jobs for life. Therefore, we need to constantly adapt and learn new things. In fact, the half-life of skills is reducing at a drastic rate. What we’ve learned today will be out of date in two or three years' time. Everyone will need to build their flexibility and adaptability skills, so they are prepared to update their skills every few years and accept new ways of doing things. ... Data is the fuel of the 4th industrial revolution that we’re experiencing today. Companies are bombarded by data. The data explosion is worthless to companies unless their people have the data skills to extract insights and make better decisions based on the data. There is a big data skills gap in the market at the moment. While not everyone needs to be a data scientist, all professionals should be data literate. ... The final important job skill for the future is tech-savviness. The 4th industrial revolution is bringing together a lot of major technology trends. On their own, these individual technologies would transform businesses, but together they are completing reshaping our world.
When a module is built, it gets stamped with a version; typically, that version will be either a development or CI version. The version also contains a version number, supporting the Semantic Versioning 2.0.0 specification, and the version stamp can be updated, so a CI build that does not regress any tests can be stamped as a QC or pre-release build. When the build is ready for roll-out, the pre-release marker can be removed. This is all designed for automation, and designed to be flexible enough to match an organization’s existing processes. The module design is unique in another way: A single module can contain many different versions of the same module. When two different versions of a module are combined, the module only increases by the size of the differences between the versions. This allows a single module file to contain every single one of its supported versions, plus pre-releases of future versions, plus optional patches to older versions, and so on.
The problem with using multiple content management platforms is that there’s no single source of truth. If an end-user needs to find a file, where is the most recent version of the document stored? Perhaps it was shared with a partner on DropBox, so people end up working off the non-master version of the document, meaning that out-of-date documents such as terms and conditions, price lists and contracts could still be in use. Mistakes can then arise from multiple people working on different versions of a document, which could mean that important updates are missed. How many times have you seen “version 7” or “final version” added to a file name? But can you really trust this? When there is a need to cross reference information in multiple areas then the organisation becomes inefficient – time is wasted searching, decisions are made using outdated information and there’s extra work in consolidating various versions of content. There are also regulatory and legal restrictions that require companies to centralise content.
“In software engineering, the singleton pattern is a software design pattern that restricts the instantiation of a class to one “single” instance. This is useful when exactly one object is needed to coordinate actions across the system. The term comes from the mathematical concept of a singleton.”— Wikipedia ... The singleton pattern should be used when: There must be a single instance of a class, and this class must be accessible by clients from an access point known to them; and The singleton class can be extended by inheritance, and clients must be able to use extended classes without making any changes to it. The singleton pattern has several advantages, summarised in the following points: You have strict control over how and when clients access a singleton instance. You have controlled access because the singleton class encapsulates its instance; It’s useful when we need to restrict the number of instances that we create from a class in order to save the system resources; The singleton pattern is an improvement over global variables because it avoids polluting the namespace with global variables that only store the singleton instances; and The code is easier to use, understand, and test since the singleton simplifies the code.
Quote for the day:
"I think failure is nothing more than life's way of nudging you that you are off course." -- Sara Blakely