Era of Quantum Computers
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.
Role of Continuous Monitoring in DevOps Pipeline
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.
Why data is the real differentiator in D2C retail
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.
How Outsourcing Practices Are Changing in 2021: an Industry Insight
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.
How AI is helping enterprises turn the tables on malicious attacks
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.
McKinsey: These are the skills you will need for the future of work
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.”
Beginner’s Guide To Lucid: A Network For Visualizing Neural Networks
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.
4 ways the coder community can help fix its diversity problem
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.
What really is consumable analytics?
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.
CISA Emphasizes Urgency of Avoiding 'Bad' Security Practices
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
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