Computer vision's next breakthrough
Beyond quality and efficiency, computer vision can help improve worker safety
and reduce accidents on the factory floor and other job sites. According to the
US Bureau of Labor Statistics, there were nearly 400,000 injuries and illnesses
in the manufacturing sector in 2021. “Computer vision enhances worker safety and
security in connected facilities by continuously identifying potential risks and
threats to employees faster and more efficiently than via human oversight,” says
Yashar Behzadi, CEO and founder of Synthesis AI. “For computer vision to achieve
this accurately and reliably, the machine learning models are trained on massive
amounts of data, and in these particular use cases, the unstructured data often
comes to the ML engineer raw and unlabeled.” Using synthetic data is also
important for safety-related use cases, as manufacturers are less likely to have
images highlighting the underlying safety factors. “Technologies like synthetic
data alleviate the strain on ML engineers by providing accurately labeled,
high-quality data that can account for edge cases that save time, money, and the
headache inaccurate data causes,” adds Behzadi.
Five years on: the legacy of GDPR
Five years on, “the European regulation has inspired data protection around the
world and many countries have put privacy standards in place. These include
countries in South America such as Argentina, Brazil, and Chile, and in Asia,
such as Japan and South Korea. In Australia, the Privacy Act has been in place
since 1988, but was recently amended to mirror GDPR concepts. GDPR has also had
a strong influence in the US where several states introduced data protection
legislation, including California with the California Consumer Privacy Act, and
Colorado with the Colorado Consumer Protection Act. On a federal level, the
draft American Data Privacy and Protection Act is another example of where
regulation is heading.” So what impact has it had on how organisations are run
and data is handled? Aditya Fotedar, CIO at Tintri, a provider of auto adaptive,
workload intelligent platforms, explains that while GDPR has ushered in
significant changes, they are built upon existing regulations: “GDPR was a
progression on the existing EU privacy laws, main changes being the sub
processor contractual clauses, right to forget, and size of the fines.
Embracing Privacy by Design as a Corporate Responsibility
Companies are increasingly realizing the immense importance of a paradigm shift
towards Privacy by Design. This is because this approach significantly reduces
the cost of adapting to new legislation, builds consumer trust, and carries
fewer risks. Data protection is here to stay, and this is a realization that
everyone – from companies to legislators to consumers – is becoming more and
more aware of and acting upon. The important thing now is to approach data
protection more proactively – and to make it a general corporate responsibility.
Data protection rights are also human rights! So far, the advertising industry
has viewed data protection as a drag, but this perception will have to change as
we move through2023. After all, data protection is no longer a limitation, but a
selling point. As a result, industry players are beginning to view it as a
worthwhile investment rather than a cost. Companies are doing this proactively
because they want to stay competitive and keep their brand privacy-centric, and
to ensure that customers continue to trust them.
4 reasons cloud data repatriation is happening in storage
Moving storage to another location means disconnecting on-site storage
resources, such as SANs, NAS devices, RAID equipment, optical storage and other
technologies. But how likely is it that an IT department making a push to cloud
storage clears out the storage section of its data center and makes constructive
use of the newly empty space? Not always likely, and the organization is still
paying for every square foot of floor space in that data center. Assuming IT
managers performed a careful, phased migration from on site to the cloud, they
probably would have analyzed the use of space made available from the migration.
If the company owns the displaced storage assets, managers must consider what
happens to them after a department or application moves out of the data center.
From a business perspective, it may make sense to retain these assets and have
them ready for use in an emergency. This approach also ensures that storage
resources are available if cloud data repatriation occurs, but it doesn't save
space -- or money. Continual advances in computing power can mean that
repatriation may not require as much physical space for the same or greater
processing speeds and storage capacity.
10 digital transformation questions every CIO must answer
Am I engaging people on the front lines to formulate DX plans? According to
Rogers, the answer should be yes. “You need people on the front lines, because
it is the business units who have people out there talking to customers every
day,” he says, adding that while C-suite support for transformation is crucial,
the front-line perspectives offered by lower-tier employees are those that can
identify where change is needed and can truly impact the business. ... Am I
identifying and using the right business metrics to measure progress? Most CIOs
have moved beyond using traditional IT metrics like uptime and application
availability to determine whether a tech-driven initiative is successful. Still,
there’s no guarantee that CIOs use the most appropriate metrics for measuring
progress on a DX program, says Venu Lambu, CEO of Randstad Digital, a digital
enablement partner. “It’s important to have the technology KPIs linked to
business outcomes,” he explains. If your business wants to have faster time to
market, improved customer engagement, or increased customer retention, those are
what CIOs should measure to determine success.
Unlocking the Value of Cloud Services in the AI/ML Era
As cloud complexity and maturity grow, the goal for businesses should be more
than just “lift and shift’’ scenarios, especially when such migrations can
result in higher costs. The key is understanding how to unlock the real value of
cloud services to meet specific organizational needs. For example, with a clear
view of how a vendor’s PaaS and SaaS strengths map to business objectives,
organizations can release new features, cut costs, and gain powerful new
capabilities to support long-term outcomes using predefined ML models. Success
demands that systems be continually evaluated to seek out iterative improvements
not be considered a one-off implementation. After all, technology is constantly
evolving so there’s no room to be complacent or ignore the environment in which
infrastructure operates. This is where human insight and expertise play a
crucial role. For example, consider the matter of determining the right public
or private cloud vendors for the business. Companies operating in highly
regulated regions will need to consider how a cloud vendor can ensure data is
compliant to localized regulations.
Insights from launching a developer-led bank
Traditional banks tend to treat policies as their primary tool for
problem-solving. While policies are part of the source code that defines how a
business operates, they do not define culture. An organisation’s real culture is
found in the values and behaviours of the people who work there - how they
interact, how they work towards their goals, and how they handle challenges.
Culture is defined by who a company chooses to hire, fire, and promote. ...
Unfortunately, traditional banks don't place much emphasis on core values and
culture during hiring, preferring to focus solely on qualifications and
experience. This is why many banks end up with a culture that is at odds with
the one they claim to have - which is both misleading to the outside world and a
source of strain and cognitive dissonance internally. Your focus should be on
building a culture that goes beyond policy documents. You need a holistic
recruitment strategy that assesses the candidate’s core values—how they work
with others, their perception of accountability, and whether they display
kindness and thoughtfulness.
How global enterprises navigate the complex world of data privacy
Some of the strategies for balancing the need for personalized data analytics
against ethical and legal data privacy responsibilities include:Data
minimization: As per the previous response, avoid collecting excessive data that
could pose a privacy risk and only collect and use that which is specific to the
business objective. Transparency: Be transparent in your policies about what is
collected, how it’s collected and how it will be used. Ensure explicit consent
from your end users. Strong data governance: Ensure strong oversight in areas
not only such as data security, but also privacy by design, customer education,
audits and reviews to enable data privacy posture to constantly evolve. The
balance between customer analytics and privacy is a delicate one that requires
an ongoing commitment to fostering a culture of privacy and respect for data and
end users within your organization. ... As AI and machine learning
technologies continue to evolve, the challenges include ethical, considerations,
bias and legal compliance to name a few but the opportunities are also
significant.
Unmasking the MGM Resorts Cyber Attack: Why Identity-Based Authentication is the Future
As seen from the MGM cyber attack, relying on single-factor authentication is a
glaring example of outdated security. This method must be revised today when
cyber threats are increasingly sophisticated. Although a step in the right
direction, multi-factor authentication can fall short if not implemented
correctly. For instance, using easily accessible information as a second factor,
like a text message sent to a phone, can be intercepted and exploited. The
evolution of security measures has brought us from simple passwords to
biometrics and beyond. Yet, many businesses are stuck in the past, relying on
these half-measures. It’s not just about keeping up with the times; it’s about
safeguarding your organization’s future. One-size-fits-all solutions are
ineffective, and risk-based authentication should be the norm, not the
exception. ... Security half-measures, like using codes, devices, or unverified
biometrics as identity proxies, are more than just weak points; they open doors
for cybercriminals. The MGM breach is a stark reminder of the dangers of
compromised security.
Metrics-Driven Developer Productivity Engineering at Spotify
An engineering department could have an OKR on the lagging metric of MTTR and a
platform team supporting SREs would have a leading metric of log ingestion
speed. These would both be in support of the company-level OKR to increase
customer satisfaction, which is measured by things like net promoter scores
(NPS), active users and churn rate. This emphasizes one of the important goals
of platform engineering which is to increase engineers’ sense of purpose by
connecting their work more closely to delivering business value. “Productivity
cannot be measured easily. And certainly not with a single accurate number. And
probably not even with a few of them. So these metrics about SRE efficiency or
developer productivity, they need to be contextualized for your own company,
your tech stack, your team even,” he said, emphasizing that the trends are
typically more important than the actual values. “That does not mean that we
cannot have a productive conversation about them. But it does mean there is no
absolute way to measure” developer productivity, knowing that proxy metrics will
never capture everything.
Quote for the day:
''A good plan executed today is better
than a perfect plan executed tomorrow.'' -- General George Patton
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