Quantum computers will disrupt almost every industry and could contribute greatly in the fields of finance, military affairs, intelligence, environment, deep-space exploration, drug design and discovery, aerospace engineering, utilities like nuclear fusion, polymer design, artificial intelligence, big data search, and digital manufacturing. Quantum computers will not only solve all of life’s most complex problems and mysteries, but will soon empower all A.I. systems, acting as the brains of these super-human machines. Teachers can use quantum computing as an object lesson to introduce high-level concepts e.g., the physics behind quantum machines offers avenue of exploration. Quantum computers will personalize higher education. The power and speed of quantum computing may best serve the individualized needs of the students in visualizing adaptive learning models. It constrains the space to make it more understandable and provides theoretical concepts a practical application. In broader picture, quantum computing will raise the bar in digital literacy. For students, quantum technologies are their future and they must have an early understanding of the fundamentals.
It is an automated process that helps DevOps teams in the early detection of compliance issues that occur at different stages of the DevOps process. As the number of applications deployed on the cloud grows, the IT security team must adopt various security software solutions to mitigate the security threats while maintaining privacy and security. Continuous Monitoring in DevOps is also called Continuous Control Monitoring (CCM). It is not restricted to just DevOps but also covers any area that requires attention. It provides necessary data sufficient to make decisions by enabling easy tracking and rapid error detection. It provides feedback on things going wrong, allowing teams to analyze and take timely actions to rectify problematic areas. It is easily achievable using good Continuous Monitoring tools that are flexible across different environments – whether on-premise, in the cloud, or across containerized ecosystems – to watch over every system all the time. At the time of the production release of the software product, Continuous Monitoring notifies the Quality analysts about any concerns arising in the production environment.
Data fabrics offer organisations, both within and outside the retail sector, centralised access and a single, unified view of data across their entire enterprise. This can be taken one step further with the use of ‘smart’ data fabrics, which embed a wide range of analytics capabilities, making it faster and easier for brands and retailers to gain new insights and power intelligent predictive and prescriptive services and applications. For retail organisations reluctant to replace siloed systems due to the expectation that the cost would be prohibitive, smart data fabrics mark a way for them to continue to leverage their existing investments by allowing existing legacy applications and data to remain in place. This means enterprises can bridge legacy and modern infrastructure without having to “rip-and-replace” any of their existing technology. When it comes to adopting a D2C model, this approach will allow brands and retailers to harness data from across their different channels to better understand their customers. This will empower them to provide the right types of experiences and interactions and to gain a more informed understanding of the types of products their customers desire, for example.
The tech ecosystem had already embraced the Fourth Industrial Revolution in terms of advancing technologies. But the outsourcing community was still a step behind. It still relied on humans for the majority of work. As the pandemic ushered in the future of work, outsourcing changed. A new digital outsourcing model emerged to help outsourcing approaches be at par with the Fourth Industrial Revolution. As the majority of businesses have embraced the technology revolution, outsourcers are also gearing up for the same. These technologies in outsourcing will enable both parties to become more flexible, resilient, efficient, and productive while driving stable revenue. More organizations are strategically incorporating these evolving technologies into their policies in the coming times. ... Businesses are now looking forward to more sustainable practices in outsourcing to continue having a long-term relationship. The pandemic forced businesses to revoke their outsourcing contracts with companies mostly because they couldn’t trust their project during uncertain times.
The major benefit of AI security tools is how they can address the needle in the haystack problem, Kler says. Humans cannot handle the proliferation of data points and the massive amounts of data pouring into the system, but AI is very good at identifying, filtering, and prioritizing threat warnings. “It replaces the two overwhelmed SIEM guys trying to filter the millions of alerts in your SOC center,” Kler says. “AI can prioritize and correlate alerts, then direct your attention to the next urgent task.” In the future, AI will also help us in threat hunting in the network, uncovering fine correlations and statistical anomalies to highlight them for security teams. AI can also be used for overall threat intelligence, predicting when, where, and what kind of attacks your organization might be facing next — predictive maintenance, in other words, to determine what’s going to go wrong next. For instance, if attacks on medical facilities ramp up, it can warn you that your own medical facility is now at increased risk. But remember that AI is not a silver bullet that’s going to solve every security issue, Kler says.
Our research suggests governments could consider reviewing and updating curricula to focus more strongly on the DELTAs. Given the weak correlation between proficiency in self-leadership and interpersonal DELTAs and higher levels of education, a strong curricula focus on these soft skills may be appropriate. Governments could also consider leading further research. Many governments and academics have started to define the taxonomies of the skills citizens will require, but few have done so at the level described here. Moreover, few, if any, have undertaken the considerable amount of research required to identify how best to develop and assess such skills. For instance, for each DELTA within the curriculum, research would be required to define progression and proficiency levels achievable at different ages and to design and test developmental strategies and assessment models. The solutions for different DELTAs are likely to differ widely. For example, the solutions to develop and assess “self-awareness and self-management” would differ from those required for “work-plan development or “data analysis.”
Lucid is a library that provides a collection of infrastructure and tools to help research neural networks and understand how neural networks make interpretations and decisions based on the input. It is a step up from DeepDream and provides flexible abstractions so that it can be used for a wide range of interpretability research. Lucid helps us know the how and why of a given prediction. This makes the end-user understand the reasons for the occurrence of such. There is a growing keen interest that neural networks need to be interpretable to humans for research purposes and better understanding. The field of neural network interpretability has formed to help with these concerns. Lucid makes use of convolutional neural networks, which have many convolutional layers. At first glance, the early layers look for basic lines and simple shapes and patterns from the input image. The results from this layer keep propagating forward and further respond to more understandable inputs; this information then goes forward to generate the output from the final layers.
Open source, by design, welcomes diversity because anyone can contribute to software code from anywhere in the world. Teams are often geographically distributed, which leads to more diversity, and that correlates with positive results to team output, research shows. We witnessed open source’s diversity-powered resilience in action last year. As the pandemic bore down, GitHub, the largest open source developer platform with more than 50 million developers, found the developer activity remained consistent—or even increased. If the pandemic reduced developer activity in one region more than another, at one time or another, the geographic diversity of the community may have mitigated the impact. To some extent, that happens every year as different regions go more quiet than others for holidays, such as Christmas in the Western world and Lunar New Year in China. In the past three decades, open source has moved from the fringe of software development to the core, and it has transformed how software is built and made.
Put simply, consumable analytics visualises data. It brings together vast amounts of information and presents it in a straightforward and easy-to-understand format, so that as the user navigates the business system, they are exposed to the patterns and trends they need without having to manually search for that data. Every record becomes a dashboard that can be easily interpreted by the user, alerting teams to key data insights in real time and allowing them to take appropriate action quickly. Let’s take a change in total monthly revenue. This could indicate a variety of issues, such as inaccurate forecasting or a poor sales period, much in the same way that a sharp increase in customer help desk requests could indicate a faulty product line or technical problems online. This kind of information would take considerable time and man-power and can easily be caught too late if there is not a specialist team consistently monitoring these reports. Consumable analytics flag these changes as they happen, saving time and resources to identify the problem and focus on a solution.
The continued use of outdated and unsupported hardware is a long-standing cybersecurity problem, says Erich Kron, a former security manager for the U.S. Army’s 2nd Regional Cyber Center. "End-of-life and old software often lacks the ability to be patched, leaving known vulnerabilities for attackers to exploit," he says. "Hard-coded passwords, or the inability to handle complex or secure passwords, is a significant risk in both the private and public sectors." Kron, a security awareness advocate for the security firm KnowBe4, adds that the bad practices catalog from CISA "makes for good overall guidance for improvements in cyber hygiene. There is power in the government setting the example for the private sector by bringing light to these bad practices." Frank Downs, a former U.S. National Security Agency offensive analyst, offers a similar perspective. "This collection of practices can act as a single point of truth for the field … a universal touchstone that can provide a baseline for all organizations.
Quote for the day:
"Integrity is the soul of leadership! Trust is the engine of leadership!" -- Amine A. Ayad