Facial recognition: Now algorithms can see through face masks
This year, in response to the new imperatives brought by the COVID-19
pandemic, the rally has focused on evaluating the ability of AI systems to
reliably collect and match images of individuals wearing an array of different
face masks, with a view of eventually deploying the technology in
international airports around the country. ... The results, however, varied
greatly from one system to the other: for example, the best-performing
technology correctly identified individuals 96% of the time, even when they
were wearing a mask. The worst-performing system tested during the rally, for
its part, only identified 4% of masked individuals. "This isn't a perfect
100% solution," said Arun Vemury, director of S&T's Biometric and Identity
Technology Center, "but it may reduce risks for many travelers, as well as the
frontline staff working in airports, who no longer have to ask all travelers
to remove masks." Facial recognition is currently used in a select
number of US airports as part of a program called Simplified Arrival, which is
deployed by the Customs and Border Protection (CBP). Under Simplified Arrival,
the identity of international travelers who enter and exit the country can be
verified at inspection points in the airport by the snap of a picture, rather
than having to present a travel document.
How to make sure the switch to multicloud pays off
The first thing you need to think about before adopting the multicloud
approach is whether you are actually ready for it. There are a number of
things you need to have in place. For example, one non-negotiable element of
your IT team is a DevOps culture. By being committed to agile processes and
cross-team collaboration, you can make sure that you’re able to continuously
make any necessary changes or updates to your product while the transition is
underway. Not to mention, having a DevOps culture will enable teams to quickly
adopt cutting-edge technologies made available by multicloud, like Spinnaker
or Kubernetes. Next, you need to understand how to achieve high availability,
resilience, and zero downtime strategies within your existing architecture. In
addition, any legacy architecture will need to be modernized before launching
a multicloud strategy. This will allow you to make use of modern cloud
features like microservices and containerization, as well as achieve
interoperability between clouds. For instance, applications that need to be
split into multiple parts to run in separate clouds must be modernized, as
legacy architectures would be unlikely to enable this.
AI Council advises government to do artificial intelligence moonshots
The roadmap document is partly based on 450 responses to a call, in October
2019, for input from what is described as an AI “ecosystem” of individuals
interested in artificial intelligence. The introduction states “we need to
‘double down’ on recent investment the UK has made in AI [and] we must look to
the horizon and be adaptable to disruption”. It says the council stands ready
“to convene workshops with the wider ecosystem to capture more detail and work
together to ensure that a future National AI Strategy enables the whole of the
UK to flourish”. The Alan Turing Institute has a central place in the
document. The council advises the government to “provide assured long-term
public sector funding that will give the Turing Institute and others the
confidence to plan and invest in strategic leadership for the UK in AI
research, development and innovation”. On the skills front, the council
advocates a decade-long programme of “research fellowships, AI-relevant PhDs
across disciplines, industry-led masters and level 7 apprenticeships”. And it
suggests that tracking diversity data to “invest and ensure that
underrepresented groups are given equal opportunity and included in all
programmes”.
Using Microsoft 365 Advanced Audit and Advanced eDiscovery to minimize impact
The Microsoft 365 Advanced Audit solution makes a range of data available that
is focused on what will be useful to respond to crucial events and forensic
investigations. It retains this data for one year (rather than the standard
90-day retention), with an option to extend the retention to ten years. This
keeps the audit logs available to long-running investigations and to respond
to regulatory and legal obligations. These crucial events can help you
investigate possible breaches and determine the scope of compromise. ... In an
account takeover, an attacker uses a compromised user account to gain access
and operate as a user. The attacker may or may not have intended to access the
user’s email. If they intend to access the user’s email, they may or may not
have had the chance to do so. This is especially true if the defense in-depth
and situational awareness discussed above is in place. The attack may have
been detected, password changed, account locked, and more. If the user’s email
has confidential information of customers or other stakeholders, we need to
know if this email was accessed. We need to separate legitimate access by the
mailbox owner during the account takeover from access by the attacker.
5 New Year's Resolutions To Improve How Organizations Work With Data in 2021
To ensure successful data democratization and extract the maximum value from
an organization’s investment in data and analytics, data literacy should no
longer be ignored. We wouldn’t let people drive cars without passing a test.
So, let’s exercise some caution to ensure employees have the necessary
training and understanding of data, analysis, and foundational statistical
knowledge before reaching conclusions from their data. Building data
literacy within an organization will require resources and a structure for
ongoing training and development. Upskilling employees and ensuring their
knowledge is current should be at the top of the agenda if businesses want to
remain competitive. This is critical, especially when you want to use an
employee’s analysis and the resulting insights as the basis for making
business decisions. ... We often read and hear that artificial intelligence
(AI) and machine learning will deliver significant advances in automation and
replace jobs in many industries. And while this is certainly a possibility,
there are still humans behind the algorithms. And humans carry biases – we all
do – so there’s a chance that biases are introduced into the algorithms we are
exposed to on a daily basis.
Artificial intelligence accelerated by light
With the rise of AI, conventional electronic computing approaches are
gradually reaching their performance limits and lagging behind the rapid
growth of data available for processing. Among the various types of AI,
artificial neural networks are widely used for AI tasks because of their
excellent performance. These networks perform complex mathematical operations
using many layers of interconnected artificial neurons. The fundamental
operation that uses most of the computational resources is called
matrix–vector multiplication. Various efforts have been made to design and
implement specific electronic computing systems to accelerate processing in
artificial neural networks. In particular, considerable success has been
achieved using custom chips known as application-specific integrated circuits,
brain-inspired computing and in-memory computing, whereby processing is
performed in situ with an array of memory devices called memristors. Electrons
are the carriers of information in electronic computing, but photons have long
been considered an alternative option. Because the spectrum of light covers a
wide range of wavelengths, photons of many different wavelengths can be
multiplexed (transmitted in parallel) and modulated (altered in such a way
that they can carry information) simultaneously without the optical signals
interfering with each other.
Five real world AI and machine learning trends that will make an impact in 2021
Computer vision trains computers to interpret and understand the visual world.
Using deep learning models, machines can accurately identify objects in
videos, or images in documents, and react to what they see. The practice is
already having a big impact on industries like transportation, healthcare,
banking and manufacturing. For example, a camera in a self-driving car can
identify objects in front of the car, such as stop signs, traffic signals or
pedestrians, and react accordingly, said Jung. Computer vision has also been
used to analyze scans to determine whether tumors are cancerous or benign,
avoiding the need for a biopsy. In banking, computer vision can be used to
spot counterfeit bills or for processing document images, rapidly robotizing
cumbersome manual processes. In manufacturing, it can improve defect detection
rates by up to 90 per cent. And it is even helping to save lives; whereby
cameras monitor and analye power lines to enable early detection of wildfires.
At the core of machine learning is the idea that computers are not simply
trained based on a static set of rules but can learn to adapt to changing
circumstances. “It’s similar to the way you learn from your own successes and
failures,” said Jung. “Business is going to be moving more and more in this
direction.”
DevOps: Watch Out for These 5 Common Snags
Traditionalists often cling to waterfall methodology, which has long been
favored in enterprise environments for its rigorous requirements of capture,
documentation and governance. While there are times when waterfall may be
appropriate, such as instances where customers want to see a clear product
roadmap over a set time period, this is rarely the way the world works today.
Upstarts are disrupting traditional business models at breakneck speed, with
innovative, cutting-edge software applications being rolled out quickly. If an
organization is to compete in this climate, it cannot afford the time spent
using waterfall to manage and implement DevOps methods and features. That’s
like trying to learn to speed row on a frozen lake. We believe that using
agile and DevOps practices will help you transition to a faster and higher
quality software delivery organization. The faster you can deliver new
capabilities and features, the more competitive you’ll be. So, it’s best not
to waste time using waterfall to implement DevOps if your ultimate goal is to
produce software products that delight customers, ahead of your competition.
The goal should always be progress, not perfection. There are many features
and capabilities you can implement that will yield positive benefits.
Are No Code and Low Code Answers to the Dev Talent Gap?
The use of no-code and low-code platforms might give organizations ways to
finally catch up on the talent gap that threatens to stall growth, says
Katherine Kostereva, CEO and managing partner of low-code platform provider
Creatio. She says there are almost 1 million IT jobs that remain unfilled in
the UK alone. “The demand for IT staff is going to grow,” Kostereva says. “The
only way out is to get technology into the hands of the employees of power
users and that is exactly what low-code is doing.” Giving people who primarily
come from the business operations side access to these platforms can help
narrow the talent demand and address a common point of discord in many
organizations. Kostereva says there is a continued misalignment where business
teams have their own ideas on how interfaces and business processes should
work, while IT teams must contend with limitations on resources and growing
backlogs of change requests. The emerging market for low code, she says, can
help business professionals take on more developer duties to a certain extent.
This may be an inevitable trend as more organizations explore ways to use
no-code and low-code platforms.
The nation state threat to business
As the threat grows, it’s important to take action to prevent state sponsored
cyber-attacks. For some companies, surviving the impact of this type of
cyber-assault simply isn’t possible, says Amanda Finch, Chartered Institute of
Information Security CEO. This is partly because fines that come in the wake of
an attack can be “crippling”, she warns, adding: “The incident can lead to a
loss of confidence from investors and stakeholders. Being cut off from financial
resources can stall a company into inactivity, and even cause a collapse.” To
protect themselves, organisations need to construct threat models to drive their
cyber threat intelligence (CTI) collection plan, says Thornton-Trump. At the
same time, Thornton-Trump says, a firm’s CTI team should be equipped to analyse
threat actor activity against the organisation’s security controls. “Knowing
what a threat actor may use to target the organisation and applying that
knowledge can provide a massive defensive advantage.” He explains how the
ultimate goal of a CTI program is to understand key mistakes, exploits or
unfortunate circumstances that have occurred in the past. “This information can
be used to prevent similar attacks on the organisation.”
Quote for the day:
"What good is an idea if it remains an idea? Try. Experiment. Iterate. Fail. Try again. Change the world." -- Simon Sinek
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